Zero Energy Buildings Theoretical investigation and applied analysis for the design of zero energy building in hot climate countries.
A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy (PhD) in the Faculty of Engineering and Physical Science
2013
PARIS PITTAKARAS
SCHOOL OF MECHANICAL, AEROSPACE AND CIVIL ENGINEERING
Contents. Chapter 1: Introduction 1. Introduction 35 1.1 European background 36 1.2 The need to improve energy efficiency in buildings 37 1.3 Hypothesis and objectives of the project 37 1.4 Research motivation and scope 38 1.5 The Importance of the project (Zero Energy Buildings) 40 1.6 Publications 41 1.7 A brief description of Cyprus 42 1.8 Cyprus energy system and electricity analysis 44 1.8.1 Power (MW) and Energy (GWh) forecast for 2011-2019 48 1.8.2 Cyprus and Europe energy statistics 49 1.8.3 Households energy demand 55 1.9. Energy supply and demand - impact of growth and climate change 62 1.10. Theoretical research conclusions 63
Chapter 2: Methodology of the project and yearly work description. 2. Introduction 64 2.1 Background 65 2.2 Outline the project steps 66 2.3 Project methodology and approach to the problem 67 2.4 Yearly work description 71
Chapter 3: Building types and characteristics 3. Introduction 77 3.1 The building as an energy system 78 3.2 Building Categories: Commercial Buildings 79 3.3 Building Categories: Residential Buildings 80 3.4 Current Building Stock Situation in Cyprus 82
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Chapter 4: A critical look at European building energy regulations 4.1 Energy regulations in Europe 89 4.2 EU legislative action 90 4.3 Provisions, impact and implementation of the recast EPBD. 93 4.3.1 Recast EPBD Provisions: 93 4.3.2 Predicted Impact assessment 94 4.3.3 Implementation of recast EPBD 95 4.4 EPBD impact in Building codes of the EU members. 96 4.5 In the direction of Zero energy as building code. 97 4.6 Implementation of the EPBD in Cyprus 98 4.6.1 The energy performance certificate 99 4.6.2 Inspections - Status of implementation 100 4.6.3 The Methodology for Assessing the Energy Performance of Buildings 101 (MAEPB) 4.6.4 European standards (CEN) used by MAEPB 103 4.6.5 Summarizing the impact of the EPBD at Cyprus national level 104 4.7 The need for further action 106
Chapter 5: The Zero energy building (ZEB) concepts 5.1 Introduction: 108 5.2 The zero energy idea 108 5.3 Europe steering towards Low energy buildings 110 5.4 Zero energy buildings definitions 112 5.5 The definition impacts in ZEB design 116 5.5.1 Net zero site building 118 5.5.2 Net zero source energy building 119 5.5.3 Net zero energy emissions building 120 5.6 The project development though the ZEB definitions 120
Chapter 6: Preparation of simulation weather data sets 6.1. Introduction. 122 6.1.1 Weather data effect on the preliminary simulations. 123 6.2 Weather data sets for building simulation 125
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6.3 Methodology of the weather analysis. 126 6.3.1 Methodology step 1-Explore the field of the simulation weather files 129 6.3.2 Methodology step 2-Extract the weather file data and convert it to the 130 Microsoft Excel program format 6.3.3 Methodology step 3-Contact with Cyprus Meteorological Services 131 6.3.4 Methodology step 4-Convert the hourly data and analyse 132 6.3.5 Methodology step 5-Compare the results and extract useful information 132 6.3.6 Methodology step 6-Construct new simulation weather files 133 6.3.7 Methodology step 7-Construct future weather files 133 6.3.8 Methodology step 8-Input the simulation weather files in IES 134 6.4 The Meteonorm software 134 6.4.1 Meteonorm Software description - Detailed software overview 135 6.4.2 Meteonorm Software-Import of own data 141 6.4.3 Climatological Databases-Ground stations. 143 6.4.4 Meteonorm Climate change data 144 6.4.5 Principles of methods used by the weather analysis software 144 6.4.6 Quality of interpolation data 147 6.4.7 Uncertainty of interpolation of ground measurements versus distance 148 6.4.8 Meteonorm Accuracy 149 6.4.9 The results from the Meteonorm program 151 6.5 CCWorldWeatherGen program 151 6.5.1 CCWorldWeatherGen program principle of the methods 152 6.5.2 CCWorldWeatherGen Calculation methods of the future weather files 154 6.5.3 Reliability of the models used to make projections of future Climate 158 Change 6.6 Climate Consultant program 160 6.6.1 Results presentation with Climate Consultant 161 6.7 Weather data and results 161 6.7.1 Weather data and results: IES weather data (CYP_Larnaca.176090_IWEC) 161 6.7.2 Weather data and results: IES weather data (LarnacaWYEC.fwt) 166 6.7.3 IES weather data: results and comments 166 6.7.4 Cyprus Meteorological Office weather data analysis 169 6.7.5 Cyprus Meteorological Office weather data: Results and comments 170
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6.8 Comparison of heating and cooling degree days 172 6.9 Weather data analysis-Conclusions. 174
Chapter 7: Building simulation theory 7. Modelling and Simulation tool 178 7.1 The aim of modelling or simulation development 178 7.2 Energy Analysis Programs 179 7.2.1 Building Energy Simulation Tools 180 7.3 The choice of the Integrated Environmental Solutions (IES) 182 7.4 The Project through the IES
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Chapter 8: The case of singe family house 8.1 Introduction 201 8.2 Single family house –Base case study (scenario 1) 204 8.2.1 Single family house-Results analysis 207 8.2.2 Single family house-Base case study results analysis 207 8.3 Single family house – Refurbishment case study (scenario 2) 209 8.3.1 Single family house-Refurbishment case study results analysis 210 8.4 Single family house –Best Practice case study (New buildings) 212 8.4.1 Renewable energy-Photovoltaic systems 214 8.4.2 Orientation of the Best Practice case study 217 8.4.3 Single family house-Best Practice case study results analysis 220 8.5 Comparison of the three case studies 223 8.6 Weather- Microclimate Effect 227 8.6.1 Future Weather files 229 8.6.2 Future Weather files- Limassol town 229 8.6.3 Future Weather files- Nicosia town 230 8.6.4 Future Weather files- Larnaca town 231 8.6.5 Weather data results 232 8.7 Conclusion 235
Chapter 9: Commercial Building-Office building case study. 9.1 Introduction 237 9.2 Cyprus Reference Building 239 9.3 Office Building –Base case study 241 9.3.1 Office Building -Base case study results analysis 243 9.4 Office Building –Refurbishment case study 244 9.4.1 Office Building -Refurbishment case study results analysis 246 9.5 Office Building–Best Practise case study (New buildings) 248 9.5.1 Renewable energy-Photovoltaic systems 250 9.5.2 Orientation of the Best Practice case study 253 9.5.3 Height effect of the Best Practice case study 256 9.5.4 Office Building -Best Practice case study results analysis 257 9.6 Comparison of the three case studies 260
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9.7 Weather- Microclimate Effect 268 9.8 Future Weather files 271 9.8.1 Future Weather files- Limassol town 271 9.8.2 Future Weather files- Nicosia town 272 9.8.3 Future Weather files- Larnaca town 273 9.8.4 Weather data results 274 9.9 Conclusion 276
Chapter 10: Residential Building -Olympic Residence case study. 10.1 Introduction 279 10.2 Olympic Residence building –Base case study 282 10.2.1 Olympic Residence building -Base case study results analysis 283 10.3 Olympic Residence building –Refurbishment case study 284 10.3.1 Olympic Residence building -Refurbishment case study results analysis 286 10.4 Olympic Residence building –Best Practice case study (New buildings) 287 10.4.1 Renewable energy-Photovoltaic systems 289 10.4.2 Orientation and height effect of the Best Practice case study 291 10.4.3 Olympic Residence building -Best Practice case study results analysis 297 10.5 Comparison of the three case studies 300 10.6 Weather- Microclimate Effect 311 10.7 Future Weather files 313 10.7.1 Future Weather files- Limassol town 314 10.7.2 Future Weather files- Nicosia town 315 10.7.3 Future Weather files- Larnaca town 316 10.7.4 Weather data results 317 10.8 Conclusion 318
Chapter 11-Discussion 11. Research summary 320 11.1 Input data and software settings 322 11.2 Important research findings 323 11.3 Findings: Single family house 326 11.3.1 Family house simulation results related to other research 328
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11.4 Findings: Office building 334 11.4.1 Commercial building- office building simulation results related to other 337 research 11.5 Findings: Olympic residence building 342 11.5.1 Findings: Olympic residence building- orientation and height simulation 346 results 11.5.2 Residential building- Olympic Residence simulation results related to other 347 research 11.6 Orientation of the case study buildings-simulation results 350 11.7 Simulation case studies- weather data results 352 11.8 Outcome of the research 356 11.9 Assessment of the project methodology and the building models 359
Chapter 12: Conclusion 12.1 Conclusions 361 12.2 Limitations of the project 363 12.3 Barriers and difficulties that may lead to delays in achieving zero energy 363 buildings in Cyprus 12.4 Suggestions for improving building performance in Cyprus 365 12.5 The most important elements identified for a future guidance 366 12.6 Project recommendations and contribution 367 12.7 Future work
References 13 References 371 Appendix Appendix A Reference Building Detailed definition of Reference Building in Cyprus 385 Calculation Methodology (MAEPB) Appendix B Gant chart – Three-Year Plan 388 Appendix C Results presentation with Climate Consultant 393 Appendix D IES program weather data 398 Appendix E IES weather data (LarnacaWYEC.fwt)-Weather data and results 400 Appendix F Cyprus Meteorological Office weather data analysis 403
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Appendix G Simulation data input for single family house 405 Appendix H Simulation data input for office building 409 Appendix I Simulation data input for residential building 414
e-Appendix (on cd) eAppendix 1 Chapter 6-Results presentation with Climate Consultant cd eAppendix 2 Chapter 6-IES program weather data cd eAppendix 3 Chapter 6-IES weather data (LarnacaWYEC.fwt)-Weather data and results cd eAppendix 4 Chapter 6 -Cyprus Meteorological Office weather data analysis cd eAppendix 5 Chapter 8- Simulation data input for single family house cd eAppendix 6 Chapter 9-Simulation data input for office building cd eAppendix 7 Chapter 10-Simulation data input for residential building cd eAppendix 8 Chapter 6- Weather simulation files for Cyprus cd
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List of Figures
Figure 1 Final energy consumption 2000-2010 45
Figure 2 Long Term Forecast of Annual Total Generated Energy (GWh) and Annual 47
Maximum Generation (MW) for the Years 2011 - 2020
Figure 3 Maximum system power and energy generation forecast for 2011-2019 48
Figure 4 Growth of dwelling stock between 1997 and 2007 49
Figure 5 Yearly energy efficiency improvement by country for 1997-2007 50
Figure 6 Energy efficiency improvements in the household sector in EU-27 by country 50
Figure 7 Heating consumption per dwelling in Europe 51
Figure 8 Increase in household energy consumption before and after 2002 51
Figure 9 Trends in the electricity consumption per country 52
Figure 10 Trends in electricity consumption per dwelling 52
Figure 11 Break down of household energy use for EU-countries 53
Figure 12 Policy measures targeted at dwelling related uses 53
Figure 13 Diffusion of solar water heaters: % of dwelling of solar water heaters 54
Figure 14 Diffusion of solar water heaters: % of dwellings of solar water heaters and solar 54
rate
Figure 15 Project methodology description 69
Figure 16 Final methodology description 70
Figure 17 Flow chart of the 3 years of planning 72
Figure 18 Age distribution of the European housing stock 77
Figure 19 The building as an energy system-Multidimensional approach 78
Figure 20 Project development diagram 121
Figure 21 The IES building model, six floors high, in Cyprus 124
Figure 22 Procedure for the construction of simulation files 128
Figure 23 The map of Cyprus and the three different towns, Limassol, Larnaca and Nicosia 131
Figure 24 Data form of the Meteonorm software 136
Figure 25 Meteonorm program interpolation procedure 136
Figure 26 Meteonorm program results presentation 137
Figure 27 Meteonorm weather stations location map 137
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Figure 28 Meteonorm data output format 139
Figure 29 Meteonorm program input weather data format tool 141
Figure 30 Parameters for monthly data import. The timestamp (Month) is mandatory, all 142
other parameters are optional
Figure 31 Parameters for data import 143
Figure 32 Uncertainty of interpolation of ground measurements vs distance 148
Figure 33 Uncertainty of satellite data in dependence of4latitude and source of satellite 149
Figure 34 GCMs depict the climate using a three dimensional grid over the globe 153
Figure 35 Comparison of percentage difference % for the average hourly statistics for dry 167 bulb temperatures °C. Figure 36 Comparison of percentage difference % for the average hourly statistics for 168
relative humidity %.
Figure 37 Comparison of percentage difference % for the average hourly statistics for Wind 169
Speed m/s.
Figure 38 5-year-average (2007 to 2011and 1969 to 1999) heating degree days for base 173 temperatures of 20oC Figure 39 5-year-average (2007 to 2011 and 1969 to 1999) cooling degree days for a base 174 temperature of 20oC. Figure 40 Annual temperature for 1901-2011 176
Figure 41 Major elements of building energy simulation 180
Figure 42 Early stage design-a detailed design 185
Figure 43 IES capabilities diagram 187
Figure 44 IES process flow chart 189
Figure 45 Ranking the ten tools 198
Figure 46 The case of single family house model 202
Figure 47 The case of single family house model plan view 202
Figure 48 The case of single family house in IES simulation software 202
Figure 49 The case of single family house model simulation software-sight view 202
Figure 50 The case of single family house in IES simulation software-ground floor plan 203 view Figure 51 The case of single family house in IES simulation software-first floor plan views 203
Figure 52 The Annual max dry bulb and max wet bulb temperature 206
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Figure 53 Solar collector and annual mean wind velocity 215
Figure 54 The photovoltaics system installation settings 215
Figure 55 Area Optimization of the PV systems on the house roof 216
Figure 56 House orientation and sun path during the summer and winter 217
Figure 57 Initial and final orientation of the house 217
Figure 58 Initial and final orientation of the house 218
Figure 59 Heating demand and orientation impact 218
Figure 60 Cooling demand and orientation impact 219
Figure 61 Percentage Difference (%) of energy consumption between the different 219
orientations
Figure 62 Monthly system energy comparison for the three case studies-Heating systems 225
Figure 63 Percentage Reduction (%) of Monthly Heating Energy Consumption 225
Figure 64 Monthly system energy comparison for the three case studies-Cooling systems 226
Figure 65 Percentage Reduction (%) of Monthly Cooling Energy Consumption 226
Figure 66 Heating demand and microclimate effect 228
Figure 67 Cooling demand and microclimate effect 228
Figure 68 Heating demand and Future weather files 229
Figure 69 Cooling demand and microclimate effect 230
Figure 70 Nicosia Heating demand and Future weather files 230
Figure 71 Nicosia cooling demand and microclimate effect 231
Figure 72 Larnaca Heating demand and Future weather files 231
Figure 73 Larnaca cooling demand and microclimate effect 232
Figure 74 Map of Cyprus showing the four major climatological zones 233
Figure 75 The original office buildings plans in AutoCAD softaware-3D and plan view 238
Figure 76 The Annual max dry bulb and max wet bulb temperature 242
Figure 77 The photovoltaics system installation settings 251
Figure 78 Area Optimization of the PV systems 252
Figure 79 Office building orientation and sun path during the summer and winter time 253
Figure 80 Initial and final orientation of the Office building 253
Figure 81 Initial and final orientation of the Office building 254
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Figure 82 Heating demand and orientation impact 254
Figure 83 Cooling demand and orientation impact 255
Figure 84 Percentage Difference (%) in energy consumption between the different 255
orientations
Figure 85 Peak Room Conditioning Loads (kW) and Building orientation 256
Figure 86 Monthly system energy comparison for the three case studies-heating systems 262
Figure 87 Percentage reduction (%) of monthly heating energy consumption 262
Figure 88 Monthly system energy comparison for the three case studies-cooling systems 263
Figure 89 Percentage reduction (%) of monthly cooling energy consumption 263
Figure 90 Heating peak room conditioning loads (kW) and building orientation 265
Figure 91 Cooling peak room conditioning loads (kW) and building orientation 266
Figure 92 Heating demand and microclimate effect 269
Figure 93 Percentage difference between the simulation weather files for heating demand 269
Figure 94 Cooling demand and microclimate effect 270
Figure 95 Percentage difference between the simulation weather files for cooling demand 270
Figure 96 Heating demand and Future weather files 271
Figure 97 Cooling demand and microclimate effect 272
Figure 98 Nicosia Heating demand and Future weather files 272
Figure 99 Nicosia cooling demand and microclimate effect 273
Figure 100 Larnaca Heating demand and Future weather files 273
Figure 101 Larnaca Cooling demand and microclimate effect 274
Figure 102 The Olympic residence buildings 280
Figure 103 The photovoltaics system installation settings 290
Figure 104 Area Optimization of the PV systems 290
Figure 105 Initial and final orientation of the Residential Building 291
Figure 106 Olympic Residence IES model and the selected floors- 3D and floor plan 292
Figure 107 Comparison of the total heating and cooling energy demand (kWh) for height 293
effect impact
Figure 108 Monthly system energy comparison for the three case studies-Heating systems 302
Figure 109 Percentage Reduction (%) of Monthly Heating Energy Consumption 302
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Figure 110 Monthly system energy comparison for the three case studies-Cooling systems 303
Figure 111 Percentage Reduction (%) of Monthly Cooling Energy Consumption 303
Figure 112 Monthly CO2 emissions comparison for the three case studies 304
Figure 113 Heating Peak Room Conditioning Loads (kW) and Building Orientation: 1st -6th 305
floor
Figure114 Heating Peak Room Conditioning Loads (kW) and Building Orientation: 7st -12th 306
floor
Figure 115 Heating Peak Room Conditioning Loads (kW) and Building Orientation: 13st -19th 307
floor
Figure 116 Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 1st -6th 308
floor
Figure 117 Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 7st -12th 309
floor
Figure 118 Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 13st - 310
19th floor
Figure 119 Heating demand and microclimate effect 311
Figure 120 Percentage difference between the simulation weather files for heating demand 312
Figure 121 Cooling demand and microclimate effect 312
Figure 122 Percentage difference between the simulation weather files for cooling demand 313
Figure 123 Predicted heating demand and Future weather files 314
Figure 124 Predicted cooling demand and microclimate effect 314
Figure 125 Nicosia heating (predicted) demand and Future weather files 315
Figure 126 Nicosia cooling (predicted) demand and microclimate effect 315
Figure 127 Larnaca Heating demand and Future weather files 316
Figure 128 Larnaca cooling (predicted) demand and Microclimate effect 316
Figure 129 Graph of daily consumption records- electricity production in house 329
Figure 130 Cyprus Energy Agency project-single family house 331
Figure 131 The Oval office building 338
Figure 132 Primary energy consumption of schools 339
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Figure 133 Measures to reduce the energy demand of the Net Zero energy Office building in 341 Germany. Figure 134 Monthly energy consumption and generation of nZEB Herten 342
Figure 135 Comparison of cooling loads for a building in different orientations on the hottest 351
day in August.
Figure 136 Comparison of cooling loads for building with and without sunshades 351
Figure 137 Comparison of cooling loads for buildings in different locations 353
Figure 138 Comparison of thermal losses of building in a different location 353
Figure 139 Map of Cyprus showing the four major climatological zones 354
Figure 140 Calculated final energy demand for 4 locations (zones) 354
Figure 141 Appendix C: Larnaca 2020 Monthly Diurnal Averages for Temperature and 393
Radiation
Figure 142 Appendix C: Larnaca 2020 Radiation Range, Hourly Averages 394
Figure 143 Appendix C: Larnaca 2020 Dry Bulb vs Humidity. 395
Figure 144 Appendix C: Larnaca 2020 Wind Speed 396
Figure 145 Appendix C: Larnaca 2020 Psychrometric chart 397
Figure 146 Appendix D: Average (arithmetic mean) hourly statistics for dry bulb 399
temperatures °C for Larnaca town, during the period 1969-1999
Figure 147 Appendix E: Comparison of average (arithmetic mean) hourly statistics for dry 401
bulb temperatures °C for May and Percentage difference %
Figure 148 Appendix E: Comparison of average (arithmetic mean) hourly statistics for dry 402
bulb temperatures °C for October and Percentage difference %
Figure 149 Appendix F: Comparison of mean temperature values and percentage difference 403
% for Nicosia and Limassol (1997-2008).
Figure 150 Appendix F:Comparison of mean precipitation values and percentage difference 404
% for Nicosia and Limassol (1997-2008).
Figure 151 Appendix G:Single family house simulation model in IES (front and site view) 405
Figure 152 Appendix G:Single family house simulation model in IES-plan view ground and 406
first floor
Figure 153 Appendix G:Single family house simulation model in IES- axonometric view 407
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Figure 154 Appendix G:Single family house simulation model in IES-dimensions view(front 408
site)
Figure 155 Appendix H:Office Building simulation model in IES (front view) 409
Figure 156 Appendix H:Office Building simulation model in IES (site view) 410
Figure 157 Appendix H:Office Building simulation model in IES (back view) 411
Figure 158 Appendix H: The original office building plans in autoCAD software- plan view 412
Figure 159 Appendix H:Office Building simulation model in IES (axonometric right view) 413
Figure 160 Appendix I: Olympic Residence building simulation model in IES (front view) 414
Figure 161 Appendix I:Olympic Residence building simulation model in IES (site view) 415
Figure 162 Appendix I:Olympic Residence building simulation model in IES (back view) 416
Figure 163 Appendix I:Olympic Residence building simulation model in IES (top view) 417
Figure 164 Appendix I:Olympic Residence building simulation model in IES (right view) 418
Electronic Appendices (cd)
Electronic Appendix (cd)- e-Appendix 1
Figure 165 e-Appendix 1: Larnaca 2050 Radiation Range, Hourly Averages cd Figure 166 e-Appendix 1: Larnaca 2050 Dry Bulb vs Humidity. cd Figure 167 e-Appendix 1: Larnaca 2050 Wind Speed cd Figure 168 e-Appendix 1: Larnaca 2050 Psychrometric chart cd Figure 169 e-Appendix 1: Larnaca 2080 Monthly Diurnal Averages for Temperature and cd Radiation Figure 170 e-Appendix 1: Larnaca 2080 Radiation Range, Hourly Averages cd Figure 171 e-Appendix 1: Larnaca 2080 Dry Bulb vs Humidity cd Figure 172 e-Appendix 1: Larnaca 2080 Wind Speed cd Figure 173 e-Appendix 1: Larnaca 2080 Psychrometric chart cd Figure 174 e-Appendix 1: Limassol 2020Monthly Diurnal Averages for Temperature and cd Radiation Figure 175 e-Appendix 1: Limassol 2020 Radiation Range, Hourly Averages cd Figure 176 e-Appendix 1: Limassol 2020 Dry Bulb vs. Humidity cd Figure 177 e-Appendix 1: Limassol 2020 Wind Speed cd Figure 178 e-Appendix 1: Limassol 2020 Psychrometric chart cd Figure 179 e-Appendix 1: Limassol 2050 Monthly Diurnal Averages for Temperature and cd Radiation Figure 180 e-Appendix 1: Limassol 2050 Radiation Range, Hourly Averages cd
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Figure 181 e-Appendix 1: Limassol 2050 Dry Bulb vs Humidity cd Figure 182 e-Appendix 1: Limassol 2050 Wind Speed cd Figure 183 e-Appendix 1: Limassol 2050 Psychrometric chart cd
Figure 184 e-Appendix 1: Limassol 2080 Monthly Diurnal Averages for Temperature and cd Radiation Figure 185 e-Appendix 1: Limassol 2080 Radiation Range, Hourly Averages cd Figure 186 e-Appendix 1: Limassol 2080 Dry Bulb vs Humidity cd Figure 187 e-Appendix 1: Limassol 2080 Wind Speed cd Figure 188 e-Appendix 1: Limassol 2080 Psychrometric chart cd Figure 189 e-Appendix 1: Nicosia 2020 Monthly Diurnal Averages for Temperature and cd Radiation Figure 190 e-Appendix 1: Nicosia 2020 Radiation Range, Hourly Averages cd Figure 191 e-Appendix 1: Nicosia 2020 Dry Bulb vs Humidity cd Figure 192 e-Appendix 1: Nicosia 2020 Wind Speed cd Figure 193 e-Appendix 1: Nicosia 2020 Psychrometric chart cd Figure 194 e-Appendix 1: Nicosia 2050 Monthly Diurnal Averages for Temperature and cd Radiation Figure 195 e-Appendix 1: Nicosia 2050 Radiation Range, Hourly Averages cd Figure 196 e-Appendix 1: Nicosia 2050 Dry Bulb vs Humidity cd Figure 197 e-Appendix 1: Nicosia 2050 Wind Speed cd Figure 198 e-Appendix 1: Nicosia 2050 Psychrometric chart cd Figure 199 e-Appendix 1: Nicosia 2080 Monthly Diurnal Averages for Temperature and cd Radiation Figure 200 e-Appendix 1: Nicosia 2080 Radiation Range, Hourly Averages cd Figure 201 e-Appendix 1: Nicosia 2080 Dry Bulb vs Humidity cd Figure 202 e-Appendix 1: Nicosia 2080 Wind Speed cd Figure 203 e-Appendix 1: Nicosia 2080 Psychrometric chart. cd
Electronic Appendix (cd)- e-Appendix 2
Figure 204 e-Appendix 2: Average (arithmetic mean) hourly relative humidity % for cd Larnaca town, during the period 1969-1999 Figure 205 e-Appendix 2: Monthly (arithmetic mean) wind direction % for Larnaca town, cd during the period 1969-1999 Figure 206 e-Appendix 2: January-February-March wind direction % for Larnaca town, cd during the period 1969-1999 Figure 207 e-Appendix 2: April-May- June wind direction % for Larnaca town, during the cd period 1969-1999
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Figure 208 e-Appendix 2: July-August-September Wind Direction % for Larnaca town, cd during the period 1969-1999 Figure 209 e-Appendix 2: October-November-December Wind Direction % for Larnaca cd town, during the period 1969-1999 Figure 210 e-Appendix 2: Average (arithmetic mean) hourly statistics for direct normal solar cd radiation (Wh/m² )for Larnaca town, during the period 1969-1999 Figure 211 e-Appendix 2: Monthly Statistics for Solar Radiation (Direct Normal, Diffuse, cd Global Horizontal) Wh/m² for Larnaca town, during the period 1969-1999
Electronic Appendix (cd)- e-Appendix 3
Figure 212 e-Appendix 3:Comparison of average (arithmetic mean) hourly statistics for dry cd bulb temperatures °C for May and Percentage difference % Figure 213 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for March and Percentage difference % Figure 214 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for June and Percentage difference % Figure 215 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for November and Percentage difference % Figure 216 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for April and Percentage difference % Figure 217 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for February and Percentage difference % Figure 218 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for July and Percentage difference % Figure 219 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for Dry cd Bulb temperatures °C for August and Percentage difference %. Figure 220 e-Appendix 3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Dry Bulb temperatures °C for August and Percentage difference % Figure 221 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for May and Percentage difference %. Figure 222 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for December and Percentage difference %. Figure 223 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for October and Percentage difference %. Figure 224 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for January and Percentage difference %. Figure 225 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for March and Percentage difference %.
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Figure 226 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for June and Percentage difference %. Figure 227 e-Appendix 3: Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for November and Percentage difference %. Figure 228 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for April and Percentage difference %. Figure 229 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for February and Percentage difference %. Figure 230 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for July and Percentage difference %. Figure 231 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for April and Percentage difference %. Figure 232 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Relative Humidity % for September and Percentage difference %. Figure 233 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for May and Percentage difference %. Figure 234 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for December and Percentage difference %. Figure 235 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for October and Percentage difference %. Figure 236 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for January and Percentage difference %. Figure 237 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for March and Percentage difference %. Figure 238 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for June and Percentage difference %. Figure 239 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for November and Percentage difference %. Figure 240 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for February and Percentage difference %. Figure 241 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for July and Percentage difference %. Figure 242 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for April and Percentage difference %. Figure 243 e-Appendix3:Comparison of Average (arithmetic mean) Hourly Statistics for cd Wind Speed (m/s) for April and Percentage difference %.
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Electronic Appendix (cd)- e-Appendix 4
Figure 244 e-Appendix 4:Comparison of Mean Precipitation Values and Percentage cd difference % for Nicosia and Limassol (1997-2008). Figure 245 e-Appendix 4:Comparison of Mean Relative Humidity Values at 08:00 hrs and cd Percentage difference % for Nicosia and Limassol (1997-2008). Figure 246 e-Appendix 4:Comparison of Mean Relative Humidity Values at 13:00 hrsand cd Percentage difference % for Nicosia and Limassol (1997-2008). Figure 247 e-Appendix 4:Comparison of Mean Daily Sunshine Duration Values and cd Percentage difference % for Nicosia and Limassol (1997-2008). Figure 248 e-Appendix 4:Comparison of Maximum and Minimum Daily Sunshine Duration cd Values and Percentage difference % for Nicosia and Limassol (1997-2008). Figure 249 e-Appendix 4:Sun radiation falling on surfaces per month Values cd Figure 250 e-Appendix 4:Limassol Wind Speed monthly mean values. cd Figure 251 e-Appendix 4:Nicosia Wind Speed monthly mean values. cd Figure 252 e-Appendix 4:Comparison of Wind Speed Mean Values and Percentage cd difference % for Nicosia and Limassol (1997-2008). Figure 253 e-Appendix 4:Comparison of Maximum and Minimum Wind Speed Values and cd Percentage difference % for Nicosia and Limassol (1997-2008). Figure 254 e-Appendix 4:Monthly Mean Wind direction for Nicosia and Limassol, for 2006- cd 2009 Electronic Appendix (cd)- e-Appendix 5
Figure 255 e-Appendix 5:Single family house simulation model in IES cd Figure 256 e-Appendix 5:Single family house simulation model in IES-back site cd Figure 257 e-Appendix 5:Single family house simulation model in IES-plan view cd Figure 258 e-Appendix 5:Single family house simulation model in IES-dimension view cd Figure 259 e-Appendix 5:Single family house simulation model in IES-dimension view(back cd site) Figure 260 e-Appendix 5:Single family house simulation model in IES- sun path view (from cd above) Figure 261 e-Appendix 5:Single family house simulation model in IES- sun path view (front cd view) Figure 262 e-Appendix 5:Single family house simulation model in IES- sun path view (from south-west) Figure 263 e-Appendix 5:Single family house simulation model in IES- sun path view(from cd north-east) Figure 264 e-Appendix 5:Single family house Boilers and Chillers load (kW) cd Figure 265 e-Appendix 5:Single family house Heating demand (kW) cd Figure 266 e-Appendix 5:Single family house heating demand (kW) vs Dry bulb temperature cd
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Figure 267 e-Appendix 5:Single family house Cooling demand (kW) cd Figure 268 e-Appendix 5:Single family house cooling demand (kW) vs Dry bulb temperature cd
Figure 269 e-Appendix 5:Single family house Dry bulb temperature vs System electricity cd demand (kW) Figure 270 e-Appendix 5:Single family house-Refurbishment case study Boilers and Chillers cd load (KW) Figure 271 e-Appendix 5:Single family house-Refurbishment case study Heating demand cd (kW) Figure 272 e-Appendix 5:Single family house-Refurbishment case study heating demand cd (kW) vs Dry bulb temperature Figure 273 e-Appendix 5:Single family house-Refurbishment case study Cooling demand cd (kW) Figure 274 e-Appendix 5:Single family house-Refurbishment case study cooling demand cd (kW) vs Dry bulb temperature Figure 275 e-Appendix 5:Single family house-Refurbishment case study Dry bulb cd temperature vs System electricity demand (kW) Figure 276 e-Appendix 5:Single family house-Best practise case study Boilers and Chillers cd load (KW) Figure 277 e-Appendix 5:Single family house- Best practise case study Heating demand cd (kW) Figure 278 e-Appendix 5:Single family house- Best practise case study heating demand (kW) cd vs Dry bulb temperature Figure 279 e-Appendix 5: Single family house- Best practise case study cooling demand cd (kW) Figure 280 e-Appendix 5:Single family house- Best practise case study cooling demand (kW) cd vs Dry bulb temperature Figure 281 e-Appendix 5:Single family house- Best practise case study Dry bulb temperature cd vs System electricity demand (kW).
Electronic Appendix (cd)- e-Appendix 6
Figure 282 e-Appendix 6: Office Building simulation model in IES (front view) cd Figure 283 e-Appendix 6: Office Building simulation model in IES (site view) cd Figure 284 e-Appendix 6: Office Building simulation model in IES (back view) cd Figure 285 e-Appendix 6: Office Building simulation model in IES (above view) cd Figure 286 e-Appendix 6: Office Building simulation model in IES (axonometric right view) cd Figure 287 e-Appendix 6: Office Building simulation model in IES (axonometric front view) Figure 288 e-Appendix 6:Office Building simulation model in IES (axonometric above view) cd
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Figure 289 e-Appendix 6:Office Building simulation model in IES-dimensions view(front cd site with first floor) Figure 290 e-Appendix 6:Office Building simulation model in IES-dimension view(floors cd design) Figure 291 e-Appendix 6:Office building Boilers and Chillers load (kW) cd Figure 292 e-Appendix 6:Office Building Heating demand (kW) cd Figure 293 e-Appendix 6:Office Building heating demand (kW) vs Dry bulb temperature cd Figure 294 e-Appendix 6:Office Building Cooling demand (kW) cd Figure 295 e-Appendix 6:Office Building cooling demands (kW) vs Dry bulb temperature cd Figure 296 e-Appendix 6:Office Building Dry bulb temperature vs System electricity demand cd (kW) Figure 297 e-Appendix 6:Office building Boilers and Chillers load (kW)-Refurbishment case cd study Figure 298 e-Appendix 6:Office Building Heating demand (kW) -Refurbishment case study cd Figure 299 e-Appendix 6:Office Building heating demand (kW) vs Dry bulb temperature- cd Refurbishment case study Figure 300 e-Appendix 6:Office Building Cooling demand (kW) -Refurbishment case study cd Figure 301 e-Appendix 6: Office Building cooling demand (kW) vs Dry bulb temperature - cd Refurbishment case study Figure 302 e-Appendix 6:Office Building Dry bulb temperature vs System electricity demand cd (kW) -Refurbishment case study Figure 303 e-Appendix 6:Office building Boilers and Chillers load (kW)-Best practise case cd study Figure 304 e-Appendix 6:Office Building Heating demand (kW) - Best practise case study cd Figure 305 e-Appendix 6:Office Building heating demand (kW) vs Dry bulb temperature- cd Best practise case study Figure 306 e-Appendix 6:Office Building Cooling demand (kW) - Best practise case study cd Figure 307 e-Appendix 6:Office Building cooling demand (kW) vs Dry bulb temperature – cd Best Practise case study Figure 308 e-Appendix 6:Office Building Dry bulb temperature vs System electricity demand cd (kW) –Best Practise case study
Electronic Appendix (cd)- e-Appendix 7
Figure 309 e-Appendix 7: Olympic Residence building simulation model in IES (back view) cd Figure 310 e-Appendix 7: Olympic Residence building simulation model in IES (top view) cd Figure 311 e-Appendix 7:Olympic Residence building simulation model in IES (right view) cd Figure 312 e-Appendix 7:Olympic Residence building simulation model in IES (back view) cd Figure 313 e-Appendix 7: Olympic Residence building simulation model in IES cd (axonometric view)
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Figure 314 e-Appendix 7:Olympic Residence building simulation model in IES (dimensions cd view -ground floor) Figure 315 e-Appendix 7:Olympic Residence building simulation model in IES (dimensions cd view -1st-17th floor view) Figure 316 e-Appendix 7:Olympic Residence building simulation model in IES (dimensions cd view -18th-19th floor view) Figure 317 e-Appendix 7:The Annual max dry bulb and max wet bulb temperature cd Figure 318 e-Appendix 7:Olympic Residence building Boilers and Chillers load (kW) cd Figure 319 e-Appendix 7:Olympic Residence Building Heating demand (kW) cd Figure 320 e-Appendix 7:Olympic Residence Building heating demand (kW) vs Dry bulb cd temperature Figure 321 e-Appendix 7:Olympic Residence Building Cooling demand (kW) cd Figure 322 e-Appendix 7:Olympic Residence Building cooling demands (kW) vs Dry bulb cd temperature Figure 323 e-Appendix 7:Olympic Residence Building Dry bulb temperature vs System cd electricity demand (kW) Figure 324 e-Appendix 7:Olympic Residence Building Boilers and Chillers load (kW)- cd refurbishment case study Figure 325 e-Appendix 7:Olympic Residence Building heating demand (kW) -refurbishment cd case study Figure 326 e-Appendix 7:Olympic Residence Building heating demand (kW) vs Dry bulb cd temperature-Refurbishment case study Figure 327 e-Appendix 7:Olympic Residence Building Cooling demand (kW) - cd Refurbishment case study Figure 328 e-Appendix 7:Olympic Residence Building cooling demand (kW) vs Dry bulb cd temperature -refurbishment case study Figure 329 e-Appendix 7:Olympic Residence Building Dry bulb temperature vs System cd electricity demand (kW) -refurbishment case study Figure 330 e-Appendix 7:Olympic Residence Building Boilers and Chillers load (kW)-Best cd practise case study Figure 331 e-Appendix 7:Olympic Residence Building Heating demand (kW) - Best practise cd case study Figure 332 e-Appendix 7:Olympic Residence Building heating demand (kW) vs Dry bulb cd temperature- Best practise case study Figure 333 e-Appendix 7:Olympic Residence Building Cooling demand (kW) - Best practise cd case study Figure 334 e-Appendix 7:Olympic Residence Building Cooling demand (kW) vs Dry bulb cd temperature –Best Practise case study Figure 335 e-Appendix 7:Olympic Residence Building Dry bulb temperature vs System cd electricity demand (kW) –Best Practise case study
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Figure 336 e-Appendix 7:Flat 1 orientation comparison of heating energy demand cd Figure 337 e-Appendix 7:Flat 1 orientation comparison of cooling energy demand cd Figure 338 e-Appendix 7:Flat 2 orientation comparison of heating energy demand cd Figure 339 e-Appendix 7:Flat 2 orientation comparison of cooling energy demand cd Figure 340 e-Appendix 7:Flat 3 orientation comparison of heating energy demand cd Figure 341 e-Appendix 7:Flat 3 orientation comparison of cooling energy demand cd Figure 342 e-Appendix 7:Flat 4 orientation comparison of heating energy demand cd Figure 343 e-Appendix 7:Flat 4 orientation comparison of cooling energy demand cd Figure 344 e-Appendix 7:Flat 1 height effect comparison of heating energy demand cd Figure 345 e-Appendix 7:Flat 1 height effect comparison of cooling energy demand cd Figure 346 e-Appendix 7:Flat 2 height effect comparison of heating energy demand cd Figure 347 e-Appendix 7:Flat 2 height effect comparison of cooling energy demand cd Figure 348 e-Appendix 7:Flat 3 height effect comparison of heating energy demand cd Figure 349 e-Appendix 7:Flat 3 height effect comparison of cooling energy demand cd Figure 350 e-Appendix 7:Flat 4 height effect comparison of heating energy demand cd Figure 351 e-Appendix 7:Flat 4 height effect comparison of cooling energy demand cd Figure 352 e-Appendix 7:Comparison of the total heating and cooling energy demand (kWh) cd for height effect impact
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List of Tables
Table 1 Energy Generated by the three Power Stations of EAC after the 11th of July 45
Table 2 Characteristics of the buildings for 2009-2011 55
Table 3 Energy consumption by surface area of the house 57
Table 4 Energy consumption by end use category 57
Table 5 Energy consumption for space heating 58
Table 6 Energy consumption for space cooling 60
Table 7 Energy consumption for water heating 61
Table 8 Building permits authorized by type of project 2009-2010 83
Table 9 Building permits authorized by district and area 2009-2010 84
Table 10 Number of dwellings units authorized by size of project and district 2009-2010 85
Table 11 Building permits authorized by type of the project and area size 2010 85
Table 12 Building permits authorized by type of the project 2010 86
Table 13 Construction and housing in Cyprus for 1995-2010 87
Table 14 Calculated impacts and benefits to be achieved with the EPBD recast reinforcements 94
Table 15 Frequency of inspections of air-conditioning systems 100
Table 16 Summary of CEN standards used by MAEPB 104
Table 17 Minimum energy performance requirements for new building and all buildings above 1,000 m2 that 105
undergo a major renovation (2007 regulations)
Table 18 U-values for the reference building in Cyprus 105
Table 19 Different definitions for Low energy building 110
Table 20 Low energy target by country 111
Table 21 ZEB Definitions Summary 117
Table 22 Definition of output formats for Building simulation software 140
Table 23 Quality of the ground bases interpolation 148
Table 24 Summary of principal data for interpolation validation where rmse is the root mean square error 150
Table 25 The new weather simulation files for Larnaca, Limassol and Nicosia. 151
Table 26 The future weather simulation files for Larnaca, Limassol and Nicosia 158
Table 27 The Larnaca IES weather data average (arithmetic mean) hourly statistics for dry bulb temperatures 162 °C during the period 1969-1999.
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Table 28 Monthly statistics for dry bulb temperatures °C 163
Table 29 Monthly statistics for relative humidity % 163
Table 30 Larnaca Monthly Statistics for Wind Speed m/s during the period 1969-1999 164
Table 31 Larnaca IES weather data monthly heating/cooling degree days/hours during the period 1969-1999. 164
Table 32 Larnaca IES weather data for average hourly statistics for direct normal solar radiation Wh/m² 165
Table 33 Annual precipitation in the past twenty years (1991-2011) 175
Table 34 Comparison of the three different case studies 204
Table 35 Family house(Base case study scenario) construction simulation values 205
Table 36 U-values for the reference building in Cyprus 207
Table 37 Family house(Refurbishment case scenario) construction simulation values 209
Table 38 Family house(Best Practice case scenario) construction simulation values 213
Table 39 Photovoltaic systems input data 216
Table 40 U-value comparison between the Reference Building and the Best Practice case study 220
Table 41 Comparison of the three case studies 223
Table 42 The minimum energy performance requirements-2007 regulations 239
Table 43 New minimum energy requirements -2009 regulations 239
Table 44 Predetermined U values for the reference building 240
Table 45 Office building (Base case study scenario) construction input simulation values 241
Table46 Max dry-bulb temperature and max et-bulb temperature 242
Table 47 Office building (Refurbishment case study scenario) construction input simulation values 245
Table 48 Office Building (Best Practice case scenario) construction input simulation values 249
Table 49 Photovoltaic system input data 252
Table 50 U-value comparison between the Reference Building and the Office Best Practise case study 257
Table 51 Comparison of the three case studies 260
Table 52 Predetermined U values for the reference building 281
Table 53 Olympic Residence building (Base case study scenario) construction input simulation values 282
Table 54 Olympic Residence building (Refurbishment case study scenario) construction input simulation 285 values Table 55 Olympic Residence building (Best Practice case scenario) construction input simulation values 288
Table 56 Photovoltaic system input data 291
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Table 57 Total heating demand Comparison between the selected floors 295
Table 58 Total Cooling demand comparison between the selected floors 296
Table 59 U-value comparison between the Reference Building and the Office Best Practice case study 297
Table 60 Comparison of the three case studies 300
Table 61 Comparison of the Base and Refurbish case studies input U-values 326
Table 62 Comparison of the Base and Best practise case studies U-values 326
Table 63 Comparison of the Best practice and Refurbishment case studies input U-values 327
Table 64 Show the single family house U-values comparison between the projects 330
Table 65 Show the single family house U-values comparison between the projects 331
Table 66 Show the single family house U-values comparison between the projects 333
Table 67 Office comparison of the Base and Refurbish case studies input U-values 335
Table 68 Office comparison of the Base and Best practice case studies input U-values 335
Table69 Office comparison of the Best practice and Refurbishment case studies input U-values 336
Table 70 Thermal conductivity of the buildings components and Electromechanical systems in schools in each 339 climatic zone. Table 71 Energy savings from different retrofitting scenarios 340
Table 72 Olympic Residence comparison of the Base and Refurbish case studies input U-values 343
Table 73 Olympic Residence comparison of the Base and Best practice case studies input U-values 344
Table 74 Olympic Residence of the Best practice and Refurbishment case studies U-values 344
Table 75 Investigation of the effect of the location of erection on the energy demand 355
Table 76 Suggested technology and equipment aspects of future zero energy buildings 358
Table 77 Appendix B: U-values in the reference building 388
Table 78 Appendix B: Effective thermal capacity (KJ/m2.K) of construction elements in the reference building 389
Table 79 Appendix B: Solar and daylight transmittances 390
Table 80 Appendix B: Opening areas in the Reference building 391
Table 81 Appendix B: HVAC Seasonal system efficiencies in the Reference building Residential Building 392
Table 82 Appendix B: Specific fan power for different ventilation systems 392
Table 83 Appendix D: Statistics for CYP_Larnaca.176090_IWEC 398
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Electronic Appendices (cd)
Electronic Appendix (cd)- e-Appendix 5
Table 84 e-Appendix 5: Single family house –Base case study External Walls cd Table 85 e-Appendix 5: Single family house –Base case study Internal Partitions cd Table 86 e-Appendix 5: Single family house –Base case study Ground contact/exposed floors cd Table 87 e-Appendix 5: Single family house –Base case study Internal Ceilings/Floors cd Table 88 e-Appendix 5: Single family house –Base case study Roofs cd Table 89 e-Appendix 5: Single family house –Base case study External Windows cd Table 90 e-Appendix 5: Single family house –Refurbishment case study External wall cd Table 91 e-Appendix 5: Single family house – Refurbishment case study Internal Partitions cd Table 92 e-Appendix 5: Single family house – Refurbishment case study Ground contact/exposed floors cd Table 93 e-Appendix 5: Single family house – Refurbishment case study Internal Ceilings/Floors cd Table 94 e-Appendix 5: Single family house – Refurbishment case study Roofs cd Table 95 e-Appendix 5: Single family house – Refurbishment case study External Windows cd Table 96 e-Appendix 5: Single family house – Best Practise case study External Wall cd Table 97 e-Appendix 5: Single family house – Best Practise case study Internal Partitions cd Table 98 e-Appendix 5: Single family house – Best Practise case study Ground contact/exposed floors cd Table 99 e-Appendix 5: Single family house – Best Practise case study Internal Ceilings/Floors cd Table 100 e-Appendix 5: Single family house – Best Practise case study Roofs cd Table 101 e-Appendix 5: Single family house – Best Practise case study External Windows cd
Electronic Appendix (cd)- e-Appendix 6
Table 102 e-Appendix 6: Office Building –Base case study External Wall cd Table 103 e-Appendix 6: Office Building –Base case study Internal Partitions cd Table 104 e-Appendix 6: Office Building –Base case study Ground contact/exposed floors cd Table 105 e-Appendix 6: Office Building –Base case study Ground contact/exposed floors to air cd Table 106 e-Appendix 6: Office Building –Base case study Internal Ceilings/Floors cd Table 107 e-Appendix 6: Office Building –Base case study Roofs cd Table 108 e-Appendix 6: Office Building –Base case study External Store Windows cd Table 109 e-Appendix 6: Office Building –Base case study External Office Windows cd Table 110 e-Appendix 6: Office Building – Refurbishment case study External Wall cd Table 111 e-Appendix 6:Office Building – Refurbishment case study Internal Partitions cd Table 112 e-Appendix 6:Office Building – Refurbishment case study Ground contact/exposed floors cd Table 113 e-Appendix 6:Office Building – Refurbishment case study Ground contact/exposed floors to air cd Table 114 e-Appendix 6:Office Building – Refurbishment case study Internal Ceilings/Floors cd
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Table 115 e-Appendix 6:Office Building – Refurbishment case study Roofs cd Table 116 e-Appendix 6:Office Building – Refurbishment case study External Store Windows cd Table 117 e-Appendix 6:Office Building – Refurbishment case study External Office Windows cd Table 118 e-Appendix 6:Office Building– Best Practise case study External Wall cd Table 119 e-Appendix 6:Office Building– Best Practise case study Internal Partitions cd Table 120 e-Appendix 6:Office Building– Best Practise case study Ground contact/exposed floors cd Table 121 e-Appendix 6:Office Building– Best Practise case study Ground contact/exposed floors to air cd Table 122 e-Appendix 6:Office Building– Best Practise case study Internal Ceilings/Floors cd Table 123 e-Appendix 6:Office Building– Best Practise case study Roofs cd Table 124 e-Appendix 6:Office Building– Best Practise case study External Store Windows cd Table 125 e-Appendix 6:Office Building– Best Practise case study External Office Windows cd
Electronic Appendix (cd)- e-Appendix 6
Table 126 e-Appendix 7:Olympic Residence building –Base case study External Wall cd Table 127 e-Appendix 7:Olympic Residence building –Base case study Internal Partitions cd Table 128 e-Appendix 7:Olympic Residence building –Base case study Ground contact/exposed floors cd Table 129 e-Appendix 7:Olympic Residence building –Base case study Internal Ceilings/Floors cd Table 130 e-Appendix 7:Olympic Residence building –Base case study Roofs cd Table 131 e-Appendix 7:Olympic Residence building –Base case study External Store Windows cd Table 132 e-Appendix 7:Olympic Residence building –Base case study External Apartments Windows cd Table 133 e-Appendix 7:Max Dry-Bulb Temperature and Max Wet-Bulb Temperature cd Table 134 e-Appendix 7:Olympic Residence building – Refurbishment case study External Wall cd Table 135 e-Appendix 7:Olympic Residence building – Refurbishment case study Internal Partitions cd Table 136 e-Appendix 7:Olympic Residence building–Refurbishment case study Ground contact/exposed floors cd Table 137 e-Appendix 7:Olympic Residence building – Refurbishment case study Internal Ceilings/Floors cd Table 138 e-Appendix 7:Olympic Residence building – Refurbishment case study Roofs cd Table 139 e-Appendix 7:Olympic Residence building – Refurbishment case study External Store Windows cd Table 140 e-Appendix 7:Olympic Residence building – Refurbishment case study External Apartments cd Windows Table 141 e-Appendix 7:Olympic Residence building – Best Practise case study External Wall cd Table 142 e-Appendix 7:Olympic Residence building – Best Practise case study Internal Partitions cd Table 143 e-Appendix 7:Olympic Residence building – Best Practise case study Ground contact/exposed floors cd Table 144 e-Appendix 7:Olympic Residence building – Best Practise case study Internal Ceilings/Floors cd Table 145 e-Appendix 7:Olympic Residence building – Best Practise case study Roofs cd Table 146 e-Appendix 7:Olympic Residence building – Best Practise case study External Store Windows cd Table 147 e-Appendix 7:Olympic Residence building – Best Practise case study External Apartments Windows cd
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Abstract
Name of the University: The University of Manchester Author: Pittakaras Paris Supervisor: Dr Rodger Edwards Degree Title: Doctor of Philosophy (PhD) Thesis Title: Zero Energy Buildings: Theoretical investigation and practical analysis for the design of Zero Energy Building in hot climate countries
Problem description: The buildings consume significant amounts of energy and are therefore major contributors to the overall CO2 emissions at the present time. The reduction of energy consumption in buildings is a major contribution to the overall control of global warming and to the improvement of sustainability. These reductions are essential as the world faces economic and energy crisis. An important key to the world’s energy problem is sustainable development.
Taking the island of Cyprus as a case study, this thesis explores the different building categories and types, analyse building energy models and propose guidelines for the success development of Zero energy buildings in hot climates without compromising the comfort levels of the buildings.
Purpose: The ultimate target is to be able to design and operate a building which requires no fossil fuel consumption – the so called “zero energy/carbon (emissions)” building. It is important for all countries to set a national goal in order to achieve zero energy consumption in the building sector and reduce the energy demands.
Method: Through the theoretical research the project explored the causes of the problem of building energy, the different types of buildings, the definitions of zero energy buildings in various countries, regulations and standards concerning the buildings energy and all the available technology, methods and materials that can be used in the building sector. In this way the analysis presents the needs of the project and the point of focus during the practical part of the research with simulation of building models.
The practical part of the project was the simulation of different building models in order to apply and check the theoretical findings and finally reach conclusions on the development of Zero energy buildings in hot climate countries. During the building simulation a variety of parameters such as the weather, the orientation, the shading methods, the insulation methods, the buildings materials, the glazing, the HVAC systems and building operation profiles were checked in order to find the appropriate combination of factors and achieve the zero energy building goals.
Conclusions: This new approach to zero energy building, gives a new perspective to the energy consumption of the building and the indoor environment while also taking environmental impact from the building sector into account. This change in approach is a crucial part of the overall problem of how to achieve the ultimate goal of Zero Energy Buildings and how to convert buildings into “producers” of energy and help solve the world energy problem/crisis.
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Declaration
It is hereby declared that no portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.
COPYRIGHT STATEMENT
i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester the right to use such Copyright for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trademarks and any other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property Rights and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://www.campus.manchester.ac.uk/medialibrary/policies/intellectualpro perty.pdf), in any relevant Thesis restriction declarations deposited in The University Library’s regulations (see http://www.library.manchester.ac.uk/aboutus/regulations/ ) and in the University’s
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Acknowledgements
I would like to express my deep gratitude to my supervisor Dr. Rodger Edwards for his guidance, encouragement and advice throughout my work on this research. His expert opinion has been valuable and I greatly appreciate the time he has dedicated all these years to advise me and support me.
Many thanks to Miss Palaiogianni Artemis and Mr Nikos Petrides for taking an interest in my project and for sharing their expert opinions.
My deepest thanks to my parents above all for their constant support and encouragement and their financial support.
Finally, the author would like to thank The School of Mechanical, Aerospace and Civil Engineering and the University of Manchester for their financial support of this project.
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“Towns should be built in order to protect the inhabitants and at the same time to make them happy.” -Aristotle, EthicaNicomachea-
“The only true wisdom is in knowing you know nothing.” -Socrates-
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This thesis is dedicated to my beloved family, Andreas, Anastasia and Ioli, for their love and support.
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Chapter 1: Introduction 1. Introduction Man has always needed protection from dangers such as exposure to torrential rains, temperature extremes and wild animal attacks and survived by taking shelter first in caves and then in houses. The ‘house’ gradually evolved and developed so now it no longer represents protection against outdoor conditions but has become a way of life with today’s houses offering a high level of comfort and convenience through architectural design and innovation.
To achieve certain levels of essential comfort all building types need energy to function; for instance, householders need energy in order to use appliances and gadgets and enjoy the desired comfort and commercial buildings (industry and offices) need energy in order to provide users with various services. All these functions need electrical/technical systems that use energy. Over time, energy demands have increased due to socioeconomic, industrial and technological development. During the oil crisis in the early 1970s, issues such as energy demand and efficiency were of enormous political, economic and technical concern worldwide. Consequently, several governments introduced certain measures in an effort to improve energy efficiency and reduce energy consumption.
Unfortunately, the building sector, one of the sectors with the highest energy demands, was not included in the first measures [1]. Only relatively recently scientists worldwide have become aware of the high energy demands of the building sector and its contribution to the increase of greenhouse gases. The realisation that the building sector uses more energy than any other single sector prompted the introduction of various energy efficiency measures and building regulations aimed at reducing energy demands. These first active measures were positive but in some cases improvements in comfort increased buildings’ energy demands. [2]
The aims were to reduce the energy demand and target energy efficiency to create sustainable building development, save natural resources, help the economy and reduce greenhouse gas emissions and consequently decrease global warming. These are crucial issues as rapid climate change and an increasing world population will have an immense impact on natural resources and the number of buildings required. A building sector without transformation and innovation will make huge demands on energy for satisfying people’s needs and cause even more problems for the already problematic energy sector.
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Scientists now have a new challenge: to reduce buildings’ energy demand without compromising on their comfort and to create buildings able to face the conditions of a changing climate in the years ahead. The challenge is growing as buildings’ energy demands account for 40-50% of the world’s energy and in recent years energy demands in the domestic sector have increased at a rate of 1% per year. [3]
More energy efficiency measures and innovative technologies are needed in order to eliminate or at least reduce buildings’ ever increasing energy demands. Moreover, energy efficiency measures should be applied to both new and existing buildings. Over the last few years governments worldwide have been increasing efforts to improve energy saving and energy efficiency of the building sector; for instance, a major step in Europe is the European Building Energy Performance Directive (2002/91/EC, 2010/31/EU), aiming to reduce energy demand of the building sector and promote energy efficiency. [4]
As more information about the impact of the building sector on energy demand becomes known, behind the scenes there are new studies highlighting the need to consider a building as a whole.[5] Experts are discussing the ‘whole building approach’, a new building procedure whereby heating and cooling losses are minimized, improved comfort and indoor environment for the occupants is important factor.
This gives a new perspective of the building’s energy consumption and the indoor environment while also taking the environmental impact into account. This new approach tackles the problem of how to achieve the ultimate goal of zero energy buildings and convert buildings into “producers” of energy.
1.1. European background
According to Commissioner Piebalgs [6] buildings in Europe consume 40% of the total primary energy use and are responsible for 36% of CO2 emissions. The European Community responded with the publication of The European Energy Performance of Buildings Directive EPBD [7] through which the European Union aimed to achieve the Kyoto protocol goal whilst continually upgrading the directive targets to the Low or Zero Energy buildings concept.
However, global awareness of the impact of building energy consumption on the economies generated the new concept of zero energy buildings which will totally transform the building sector and help sustainable development.
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1.2. The need to improve energy efficiency in buildings
Two crucial questions need to be addressed before the development of this research. Why improve buildings’ energy efficiency? Who needs this improvement? The building sector produces high levels of greenhouse gases and consumes high levels of energy: hence, it is clear that this sector badly needs improvement and transformation. In recent years scientists, governments and other interested parties have made significant contributions to the issue of energy improvement of the building industry, there is still considerable scope for further improvement of the sector.
The following can be considered the benefits (social and private benefits) of improving the energy efficiency of buildings:
1. Support for efforts to reduce greenhouse gases and improve people’s environment. 2. Making a major contribution to climate change strategies. 3. Making a major contribution to sustainable development. 4. Securing energy supplies for future generations. 5. Helping to fill the predicted energy gap due to population increase. 6. Investing in not only fossil fuels but also renewable sources. 7. Improving occupant comfort in buildings 8. Reducing operational costs of buildings by reducing energy demand
The real challenge for this research is the investigation of an idea combining the previous benefits and providing guidelines to support the zero energy buildings with the potential for developing new ideas.
1.3. Hypothesis and objectives of the project
This project aims to explore the development of zero energy buildings in hot climate countries through theoretical analysis and building simulation. As the term ‘zero energy buildings’ is not clearly defined and has no common definition, a theoretical approach had to be taken before a practical approach, through the simulation of building models.
The project objectives were formulated taking into account both global and Cyprus energy problems, as well as the latest scientific progress in building sectors and renewable resources. First, the technical scopes are evaluated so that the widest possible range of measures can be taken for the integration into zero energy building, including fabric thermal performance,
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heating and air-conditioning equipment, renewable and developing technologies. Another important factor was identifying possible combinations of measures which produced a better energy performance of buildings according to the current weather profile based on the latest weather analysis. Moreover, through the use of computer simulation, the effectiveness of the combination measures produced useful results. Finally, the computer simulation project results formed a basis of recommendations and guidelines on how zero energy/carbon buildings performance may be achieved.
The main project objectives were to:
1. Create simulations of different types of buildings, e.g. residential and commercial. 2. Reduce building energy demand to a minimum and cover the remaining needs from renewable energy sources. 3. Use and combine available materials, technology and methods to achieve the ZEB concept. 4. Create guidelines for successfully developing zero energy building in hot climate countries and help manufactures develop and construct compliant indoor climate for ZEB. 5. Influence current building standards, contribute to a better understanding of the different standards between countries and describe possible shortcomings.
1.4. Research motivation and scope
The motivation for this research is that buildings consume significant amounts of energy and
are therefore major contributors to overall CO2 emissions. Reducing energy consumption in buildings greatly contributes to the overall control of global warming and to improved sustainability. These reductions are essential as the world faces an energy crisis and sustainable development is the solution the problem. The ultimate target is to design and operate a building requiring no fossil fuel consumption – the so called “zero energy/carbon (emissions)” building.
Climate change, energy and economic crisis are drivers for improvement within the building sector which uses more energy than any other single sector in the developed world. [8] In many countries, the energy required to construct and operate a building is extremely high and this why the way in which buildings are constructed and operated is in urgent need of change.
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Building energy efficient buildings is the quickest way to solve the future problem of the energy gap in Europe and the rest of the world. According to the Mediterranean Energy Observatory (OME), the demand for energy will increase 40% over the next 20 years.[8]Another team of the European Commission, the EU Market Observatory for Energy, reports that the energy produced by the European Union meets less than half its needs and so the EU imports around 54%. Of this 54%, 60% corresponds to oil imports, 26% to gas, 13% to solid fuels and less than 1% to electricity and renewable energy. Moreover, energy dependency will continue to rise in a context of high and volatile prices caused by increased demand for hydrocarbons. [9]
With the aim of achieving better performance, the cause and the need for building transformation must be examined. Using Cyprus as a case study, this thesis explores the different building categories and types, analyses the building models and proposes guidelines for the successful development of zero energy buildings in hot climates without significant extra costs. In addition, a further aim was to understand the operation of zero energy buildings in a broader sense.
The development of the zero energy building concept demands a multidimensional approach; consequently, building evaluation was carried out using different perspectives and simultaneously with different systems limitations. Firstly, the examination of the buildings in question focused on lower energy consumption with significant reductions compared to other ordinary buildings. Therefore, using this concept, new available technologies had to be combined with renewable energy systems for better energy efficiency. Furthermore, the building’s design and construction was intended to offer better facilities and comfort with lower energy consumption and cost meaning that the building’s envelope and orientation played an important role in the efficiency of the heating and cooling systems. Finally, included in the simulation procedure were various innovative materials which affected the energy performance and the CO2 emissions of the building.
The thesis used as case studies three different types of building which belong in the two main categories, residential and commercial buildings. It should be noted that all the case study buildings are real and were selected because they were not low energy buildings. The evaluation of these buildings examined the energy demand, thermal comfort, insulation, the glazing, the systems operation profiles, the systems type and performance, the orientation, the carbon emissions and the use of renewable energy systems.
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1.5. The Importance of the project (zero energy buildings)
This project focuses on the building energy problem in relation to the effects of climate change. Nowadays buildings account for nearly a third of the world’s energy use and this is expected to rise together with population growth and levels of prosperity. Residential and commercial buildings worldwide accounted for approximately 40 % of primary energy use. [10][11].
In terms of electricity buildings consume approximately 73 % of all electricity used and in developed countries such as the U.S 55 % of natural gas consumption (including natural gas for electricity production) [12]. If current trends continue, buildings may conceivably consume more than industry and transport combined [13] and without dramatically reducing building sector energy consumption, governments will find it difficult to make significant reductions in the fast-growing demand for electricity, water, and/or gas.
A significant question arising from this research is whether it is possible to establish a set of design criteria for building types encountered in Cyprus that will deliver zero energy performance under the weather conditions likely to be experienced? To identify the most appropriate solutions for the building sector is the primary target of this project while also presenting the guidelines for a zero energy building. According to the literature review, net- zero energy buildings (NZEB) buildings that produce as much energy as they consume over a defined period - offer the potential⎯ to substantially decrease building energy use and enable buildings to become energy self-sufficient- energy producers.[14] By achieving the vision of zero energy buildings this project will suggest the pursuit of multiple strategies, including the development of new, cost-effective technologies and practices, revision of building codes, integration of renewable energy into building designs, and adoption of innovative strategies for using energy and resources within the building community.
However all countries need to set national goals in order to achieve zero energy consumption in the building sector and reduce energy demands. Moreover, the increased use of existing technologies plays a key role in achieving this goal. Studies have shown that, by using currently available technologies, a building’s energy consumption can be reduced by 30 % to 50% [15] [16][17]. Existing technologies alone, however, are not able to achieve dramatic energy reduction goals for the buildings sector.
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Buildings can be characterized as complex systems with many interacting elements, but past improvements in the energy performance of integrated and interacting materials, components, and systems within buildings have not produced the expected reductions in overall energy use. An integrated portfolio of advanced technologies is needed that not only supports performance improvements in the design and manufacturing of individual components, but also captures system complexities and interactions seen in real buildings. Additional reductions of 20 % to 40 % can be achieved using advanced technologies integrated holistically with the building design [16]. Additional energy requirements, once current and advanced energy saving technologies are in place, must be met through the use of renewable energy systems.
The environment in which technologies are employed must also be addressed. Challenges include a complex industry and regulatory structure, imperfect information, high first costs, technical and market risks, and lack of a trained and experienced workforce. Technological advances combined with new policies that address or eliminate some of these challenges are needed to achieve dramatic improvements in building energy efficiency.
1.6. Publications
Another purpose of this project was the writing of papers and their submission to various conferences and journals and it was also intended to make scientific contributions through the publication of the various results in conferences and journals. This project has already participated with a paper and presentation in an international conference - ‘Environment, Innovation and Sustainable Development’- which took place in Marseille-France from 6th to 10th October, 2010. Furthermore, the project participated in Manchester University Postgraduate Conference 2010 and 2011 with a poster titled ‘zero energy buildings in hot climate countries: Performance of zero energy buildings in Cyprus.’ Also in 2012 on the World Sustainable Energy Days, the project’s paper titled "Demonstration of the microclimate effect on the simulated load of a ZEB” was selected from among 100 papers from over 30 countries for presentation by the scientific committee. Furthermore, the scientific committee rewarded the paper by covering all the expenses for the conference. Moreover, the submission of a journal paper titled is ‘zero energy buildings in hot climate countries: Weather data sets for the simulation of the performance of zero energy buildings in Cyprus’ is underway.
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1.7. A brief description of Cyprus
As research into zero energy buildings continues globally, the challenge for engineers is to design and build buildings which will be of low energy consumption and make use of energy from alternative sources such as lighting or even body heat as well as from renewable energy sources. Research in the building sector will soon enable governments to introduce changes which will reduce CO2 emissions and energy demands for building needs. Meanwhile, there is a pressing need for more research into the issue of zero energy buildings taking into account all the facts, needs and changes which affect today’s world.
The Zero Energy Building (ZEB) goals are achievable and provide the only means of reducing the huge amounts of greenhouse gases emitted by buildings. Hence today’s generations are responsible for adopting the concept of Low Energy Buildings which will in turn help towards the stabilization of the Earth’s climate.
This research focuses on hot climates taking as a case study the island of Cyprus situated in the Mediterranean. The Cyprus weather presents a very real challenge for the development of the Zero Energy Building due to the wide differences in temperature between seasons and times of day. The extreme variations in temperature between day and night are a significant factor - for instance, in summer the daytime temperature may occasionally reach 450C and fall to 240C at night.
Cyprus is situated in the north-eastern part of the Mediterranean and is the third largest island with an area of 9250 square kilometres and a population of 862.000[18]. Since ancient times Cyprus has been called the “island of the sun” because the sun shines for 340 days a year. It shines continuously and average yearly temperatures rise to 35° C. This is due to the island’s proximity to southwest Asia which makes it one of the hottest parts of the Mediterranean, and high pressure comes from North Africa in summer keeping the temperatures high. [19]
Nevertheless, one important issue affecting the Cypriot economy and development is the problem of energy. Energy production is more or less completely dependent on imported fuels, with Cyprus’ power plants being more than 90% dependent on oil products while the remaining 9% is covered by coal imports (4,5%) and solar energy(4,5%)[20][21].The cost of the country’s oil imports accounts for 62% of Cyprus’s export earnings.
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Predictions concerning the rapidly increasing demand for energy also include a degree of uncertainty since the world energy market is both in crisis and in transformation, while the energy future at national level will change dramatically. However, all studies on the issue of the energy future of Cyprus indicate that without the implementation of significant energy conservation policies electricity demand is expected to triple over the next 15-20 years. [22][23]
The future increase is expected to go beyond 12000 GWh in 2030 while the consumption of the residential and commercial sectors will increase to 86%. Buildings now account for nearly a third of the world’s energy use, a share expected to rise with population growth and levels of prosperity. Residential and commercial buildings worldwide consume approximately 40 % of primary energy used, or about 38.7 quadrillion BTUs (40.8 exaJoules) [11][24][25][26]. In Cyprus residential and commercial buildings consume about 45-55% of primary energy. In terms of electricity, they consume approximately 73 % of all electricity used and in developed countries such as the U.S 55 % of natural gas consumption (including natural gas for electricity production) [12]. If current trends continue, buildings may consume more than industry and transportation combined [13]. Without dramatically reducing building sector energy consumption governments will find it very difficult to significantly reduce the fast-growing demand for electricity, water, and/or gas.
However, Cyprus was possibly the only Member of the European Union to recently adopt mandatory regulations related to building insulation, building energy efficiency and building heat/cooling system efficiency. This is why the building sector consumes a large amount of electricity. Analysis of electricity consumption reveals the need for immediate action to reduce the building energy demands and avoid the possible future energy gap. There is huge potential for substantial savings in electricity consumption in buildings and costing much less than extending the existing power stations.
The Cyprus weather, the fast growing building market - a new market compared with other European countries - and general economic growth enable the transformation of the building sector by adopting the Zero Energy Building idea. These buildings will not only reduce energy demand, but will also produce their own energy and cover the building’s needs. Already the development of renewable systems in the residential sector has led to energy savings of over 9930 toe for 2010 and is estimated to reach 13220 toe in 2016. [17]
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Additional reductions of from 20 % to 40 % can be realized by using advanced technologies integrated holistically with the building design. [26] The development of zero energy buildings may slow down the increasing energy demand and offer a long-term solution to the energy problem of Cyprus.
The future energy sustainability of Cyprus demands immediate action and commitment from policy makers so that far-sighted measures can transform crucial sectors such as the island’s building sector.
1.8. Cyprus energy system and electricity analysis
Another essential issue for the project concerns Cyprus’s electric power supply and its ever increasing energy requirements. The use of primary energy per capita is 90% of the EU-25 average but energy intensity is higher by 30% of the EU-25 average[27][28][29][30]. According to the U.S department of energy, the energy intensity is a measure of the energy efficiency of a nation’s economy. The energy intensity is calculated as units of energy per unit of Gross domestic product (GDP).[31] Electricity consumption per capita in Cyprus is at 75% of the EU-25 average[28][29][30]. Energy intensity has increased over the last 15 years due to the increasing use of electricity in buildings and the tertiary sector. Moreover, the use of electricity is expected to grow over the next ten years at rates slightly above GDP growth, as has already been the case over the last fifteen years [28][29][30]. However, if the building sector turns to zero energy buildings policies, there is a significant potential for more rational use of energy in buildings. At present, Cyprus is totally dependent on imports of oil and an increasing amount of gas for its supply of conventional energy, the only national resources being solar and wind energy (moderate potential) [28][29][30].
It should be mentioned that in July 2011 an explosion in the vicinity of the Vassilikos Power station resulted in extensive damage to the power station which was taken out of operation. [32[33] As the Vassilikos station normally provides 50% of the energy supply of Cyprus [33], the disaster had a strong impact on the electricity supply, especially since Cyprus is not interconnected to other power systems from neighbouring countries. After the 11th July 2011 the total electricity generation of Cyprus was as shown in Table 1.
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Table 1: Energy generated by the three Power Stations of EAC after the 11th of July [33]
Power Station Capacity (MW) Installed capacity Available Generation (MW) Capacity (MW) Vassilikos Power 3 x 130ΜW Steam units 793MW 0MW Station 1 x 38MW Gas Turbine out of operation 53% of the total capacity 1 x 220MW CCGT out of operation 1 x 145MW CCGT Dhekelia Power 6 x 60MW Steam Units 460MW 460MW Station 2 x 50MW ICE Moni Power 6 x 30MW Steam Units 350MW 229MW Station 1 x 20MW Steam Unit 4 x 37,5MW Gas Turbines
According to the Electricity Authority of Cyprus (EAC), during the decade 2000-2010 the final energy consumption (Figure 1) in Cyprus increased by 1.7% on an average annual basis and electricity consumption increased by 6.0% on an average annual basis.[33][34]
Figure 1 :Final energy consumption 2000-2010[33] The transmission system operator prepared a long term forecast of annual maximum generation (MW) and annual total generated energy (GWh) for Cyprus. [34]According to transmission system operator data, the forecast for 2010 was accurate with a deviation of less than 1%, where the predicted value for adverse weather conditions was 1.145 MW and the recorded annual maximum generation was 1.154 ΜW.
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Additionally, the Annual Total Generated Energy (lower limit value) predicted value for 2010 was 5.275 (GWh) and the recorded value was 5.272 (GWh), with a deviation of less than -0,1%. [33][34]
Figure 2 shows the long term prediction for the decade 2011-2020 created by transmission system operator for annual maximum generation and annual total generated energy. In addition, the graph shows the recorded annual historic values since the general electrification of Cyprus from 1953 until today. In Figure 2 the red line shows the Upper limit of Annual total generated energy, the green line shows the predicted value of annual total generated energy, the blue line shows the lower limit of annual total generated energy and the black line is the recorded annual values since 1953.[34]
The data indicates that there is an increasing tendency of annual total generated energy which means that Cyprus will need to increase power generation or/and decrease energy consumption through efficiency measures. However, the solution will be somewhere in the middle with a need for a changed Cyprus energy policy and for renewable energy sources to be deployed in advance scale. This project’s main contribution is to propose how building transformation and the development of zero energy buildings will give the authorities time to decide on future power generation plans on the one hand and will contribute positively to the reduction of energy consumption in the building sector on the other.
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Figure 2: Long Term Forecast of Annual Total Generated Energy (GWh) and Annual Maximum Generation (MW) for the Years 2011 – 2020 [33]
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1.8.1. Power (MW) and Energy (GWh) forecast for 2011-2019 Based on annual recorded data and taking into account 2010 (when the forecast study was prepared), the EAC created a forecast for the subsequent years until 2019. The power maximum demand was recorded on 3rd August 2010 as 1148 MW where the demand forecast was 1105MW. In addition, the total electricity generation for the whole year was 5272 GWh and the forecast value was 5380 GWh. According to the EAC, the power maximum demand average annual rate increased by 7.09% in recent years and the average annual rate of increase in generated energy was around 3.65%. [33] [34]
Based on statistical evidence, however, the levels of annual maximum demand and the annual energy generated are expected to continue to increase. The forecast of maximum demand for electricity is 1200 MW for 2012, 1250 MW for 2013, 1295 MW for 2014, 1340 MW for 2015 and 1385 MW for 2016. [33] [34]
Figure 3 presents data for the period 2000-2008 and the forecast quantities for the period 2011-2020.
Figure 3 : Maximum system power and energy generation forecast for 2011-2019. [34] The author believes that Cyprus needs to act quickly with energy sufficiency measures in sectors having the greatest impact on consumption. Once again the building sector is a key area since climate change, people‘s comfort zone and energy consumption are strongly interrelated.
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Buildings’ energy consumption impacts significantly on power generation and considerable reductions may be achieved with appropriate policies and measures for the building sector. Transformations of the building sector with energy saving measures can take immediate effect and, compared with other solutions, could be achieved within a short period of time. For instance, building a new power station will take longer and cost more than a policy of energy saving and energy efficiency of the building sector. However, the development of new generation buildings or the refurbishment of old buildings and transformation into zero or low energy could be effective for both the short and long term.
This brief outline of the Cyprus energy problem reveals that Cyprus energy power stations are dependent on oil products and are therefore vulnerable to fluctuations in oil prices. Furthermore, the production of electricity from oil is expensive and results in a higher cost of living. Climate change is affecting energy consumption in the building sector as people try to achieve a better comfort zone through HVAC systems and this is reflected in increasing energy demands from the sector. Also the forecast for maximum system power and energy generation for the period 2011-2019 shows the need for transformation in the energy sector and the use of renewable energy sources.
1.8.2. Cyprus and Europe energy statistics
Figure 4 shows the growth of dwelling stock in European countries between 1997 and 2007 and Figure 5 shows the yearly energy efficiency improvement by country for 1997-2007. Cyprus held the second place of dwelling growth among the European countries in contrast with the non-sufficient yearly energy efficiency improvements.
Figure 4: Growth of dwelling stock between 1997 and 2007 [35]
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Figure 5: Yearly energy efficiency improvement by country for 1997-2007 [35] Figure 6 shows the energy efficiency improvements in the household sector in EU-27 by country where Cyprus presents 0.8%/year on average in the EU-27 indicating a need for more energy efficiency measures to improve the household sector of Cyprus.
Figure 6: Energy efficiency improvements in the household sector in EU-27 by country.[35]
Figure 7 shows the heating consumption per dwelling in Europe. Cyprus presents low heating consumption compared to other European countries. Hence, due to the Cyprus climate heating demand could be further reduced by using proper insulation and more energy efficient systems.
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Figure 7: Heating consumption per dwelling in Europe. [35] Figure 8 shows the increase in household energy consumption before and after 2002. Generally the lack of strict energy efficiency regulations resulted in high energy consumption in Cyprus households.
Figure 8: Increase in household energy consumption before and after 2002 [35]
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Figure 9 shows the trends in electricity consumption per country where Cyprus presents a trend over 4% per year. In addition, Cyprus presents an increasing trend in electricity consumption per dwelling which decreased slightly for the period 2000 to 2006.
Figure 9: Trends in the electricity consumption per country [35]
Figure 10: Trends in electricity consumption per dwelling [35]
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Figure 11: Break-down of household energy use for EU-countries [35] According to Figure 11, the energy consumed by EU-27 households is used mainly for space heating (70%), appliances/lighting (13%), hot water (14%) and cooking (4%). However, there is a significant difference in energy use among the EU-members. The climate is related to the use of energy and the high percentage of space heating correlates with cold winters. Cyprus shows a small amount of energy consumption for space heating as the climate is the hottest of the EU-members.[35] It should also be noted that for 1997-2006 the percentage for appliances/ lighting (including the air conditioning) increased by 1-2% while the percentage for space heating decreased. This could be the result of climate changes that were recorded in the previous weather data analysis.
Figure 12: Policy measures targeted at dwelling related uses. [35]
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Figure 13: Diffusion of solar water heaters: % of dwelling of solar water heaters [35]
Figure 14: Diffusion of solar water heaters- % of dwellings of solar water heaters and solar rate. [35]
Figures 12,13,14 describe the Cyprus energy sector and show a relationship between the different factors such as the measures, policies, use of developing technologies, improvements in energy efficiency, solar water heaters and growth of dwelling stock. The conclusion is that Cyprus needs to take further immediate action to improve energy efficiency in the building sector. As Cyprus is a new EU member and harmonization occurred just a few years ago, its market is at an early stage compared with other European countries and transformation of the building sector could be easily achieved. It is hoped that this research will contribute significantly to the transformation of the building sector.
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1.8.3. Households energy demand
Energy demands within houses are a significant part of the energy analysis as they are key energy points which impact considerably on energy consumption. An important motive for this research was the considerable impact of the building sector on energy demands due to the lack of appropriate measures and policies for the sector. As previously mentioned, Cyprus did not apply any building energy regulations prior its accession to the European Union.
In analysing and understanding household consumption, there was an issue with the data collection. During the theoretical research data was available from the Statistical Services of Cyprus, but the data was upgraded in 2011 and the new tables and data are presented in this section. The data referred to the annual energy consumption in households for 2009-2011. Table 2 shows the building characteristics focusing on such factors as type of building, type of building tenure, building surface area, year of construction and the proportion of total buildings having different types of heat insulation installed.
Table 2: Characteristics of the buildings for 2009-2011[36][37]
CHARACTERISTICS OF BUILDINGS
HOUSING TYPE OF BUILDINGS (%)
Single House 50.0
Semi-detached or duplex 20.1
Apartment 21.7
Row House 6.7
Other (e.g. back yard house) 1.5
TYPE OF TENURE OF BUILDINGS (%)
Owned 78.0
Rented 10.2
Provided for free 11.8
SURFACE AREA OF BUILDINGS (%)
< 51 m2 3.7
51 - 100 m2 24.8
101 - 150 m2 34.7
151 - 200 m2 18.8
201 - 250 m2 9.5
251 - 300 m2 4.7
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301 - 350 m2 2.0
> 350 m2 1.8
YEAR OF CONSTRUCTION OF BUILDINGS (%)
Earlier than 1971 17.9
1971 - 1980 18.8
1981 - 1990 23.9
1991 - 2000 20.2
2001 - 2003 6.0
2004 - 2006 9.2
Later than 2007 4.0
PROPORTION OF TOTAL BUILDINGS HAVING DIFFERENT TYPES OF HEAT INSULATION INSTALLED (%)
Heat insulation of external walls 7.5
Loft/roof heat insulation 5.5
Floor heat insulation 0.8
Double glazing 43.2
Other type 0.4
None 54.4
Table 2 shows that 50% of the buildings are single houses and 21.7% are apartments. 71.7% of household buildings belong to these two categories indicating that the proposed energy measures of this research will impact greatly on energy reduction in the building sector. Moreover, this was why the research did not focus on only one building type and thus the effectiveness of the research results will be more realistic and effective for the Cyprus building sector.
Another important issue is the building-house tenure where owned houses are 78% and rented are 10.2%. The owners of a house/building understand better the benefits and apply energy efficiency measures to their properties and thus invest in saving energy. However, people who rent a property do not care or do not want to spend money on the property for energy efficient measures. In Cyprus the percentage of owned buildings is high and so it should be easier to transform the building sector. Regarding the surface area of the houses, Table 3 shows that 24.8% are between 51-100m2, 34% are 151-200m2 and 18.8% are 201- 250m2. The fact that 34% of the houses are between 151-200m2 shows one aspect of the energy problem of the building sector: very large houses without any energy measures
56 | Page signifies high energy consumption and losses (Table 4). Most of these houses were constructed in 1981-1990 (23.9%) and 1991-2000 (20.2%) and during those periods energy measures were non-existent. Furthermore, table 3 shows that 54.4% of the houses/buildings have no heat insulation installed.[36][37]
Table 3: Energy consumption by surface area of the house [36]
Surface Area of Dwelling Annual Energy (m2) Consumption (kgoe)
< 51 406 51 - 100 639 101 - 150 998 151 - 200 1,470 201 - 250 1,731 251 - 300 1,946 301 - 350 2,157 > 350 2,745
Table 4: Energy consumption by end use category [36]
Energy Unit of Space Water Space Cooking Electrical TOTAL Source Measure- Heating Heating Cooling Appliances ment & Lighting Electricity KWh 642 382 1,107 554 3,603 6,288 Heating oil litres 331 24 - - - 355 Kerosene litres 42 2 - - - 44 Liquefied kg 50 8 - 67 - 125 petroleum gas Biomass kg 231 2 - 11 - 244 (e.g. wood) Charcoal kg - - - 48 - 48
Electricity kgoe 55 33 95 48 310 541 Heating oil kgoe 284 20 - - - 304 Kerosene kgoe 35 2 - - - 37 Liquefied kgoe 55 9 - 74 - 138 petroleum gas Biomass kgoe 83 1 - 4 - 88 (e.g. wood) Charcoal kgoe - - - 34 - 34
TOTAL kgoe 512 65 95 160 310 1,142
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Table 4 shows that the primary energy source in Cyprus is electricity with heating oil the second most important. From the total of 6.288 KWh, 642KWh is for space heating, 382 KWh is for water heating, 1.107 KWh is for space cooling and 3.603 for electrical appliances and lighting. [36]These numbers affect the project development as the consumption categories determine the main factors affecting energy consumption in a Cyprus house. High cooling demand and lighting performance impact considerably on energy consumption and part of the success of the proposed energy measures was to reduce the energy impact of these two categories.
Table 5: Energy consumption for space heating [36]
SURFACE AREA OF DWELLINGS HEATED DURING THE COLD SEASON OF THE REFERENCE YEAR (%)
< 51 m2 41.0
51 - 100 m2 25.9 101 - 150 m2 15.6
151 - 200 m2 10.1
201 - 250 m2 4.0 251 - 300 m2 2.4
301 - 350 m2 0.7
> 350 m2 0.3
MAIN TYPE OF EQUIPMENT/SYSTEM USED FOR SPACE HEATING (%)
Central heating system 29.2 Solar central heating system 0.1
Heat pump 0.0
Split units 16.9 EAC electric storage heaters 4.8
Fireplace 7.3
Portable heater 39.3 Stove 0.6
Other 0.2
No use of space heating 1.6
MONTHS OF OPERATION OF THE MAIN EQUIPMENT/SYSTEM USED FOR SPACE HEATING DURING (%) THE REFERENCE YEAR < 1 month 0.3
1 month 1.4
2 months 11.0
3 months 26.2
4 months 41.8
5 months 14.9
6 months 4.1 > 6 months 0.3
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HOURS OF DAILY OPERATION OF THE MAIN EQUIPMENT/SYSTEM USED FOR SPACE HEATING (%) DURING THE PERIOD OF USE <= 2 hours 9.6
3 - 5 hours 46.2 6 - 8 hours 29.7
9 - 11 hours 10.1
12 - 14 hours 2.5 15 - 17 hours 0.6
> 17 hours 1.3
TYPE OF ENERGY SOURCE USED FOR THE OPERATION OF THE MAIN EQUIPMENT/SYSTEM USED (%) FOR SPACE HEATING Electricity 37.8
Heating oil 27.0 Kerosene 5.2
Liquefied petroleum gas 22.1
Biomass (e.g. wood) 7.9
ANNUAL ENERGY CONSUMPTION FOR SPACE HEATING PER HOUSEHOLD
Electricity 642 KWh Heating oil 331 litres
Kerosene 42 litres
Liquefied petroleum gas 50 kg Biomass (e.g. wood) 231 kg
ANNUAL ENERGY CONSUMPTION FOR SPACE HEATING PER HOUSEHOLD (kgoe) (in kilograms of oil equivalent) Electricity 55
Heating oil 284 Kerosene 35
Liquefied petroleum gas 55
Biomass (e.g. wood) 83 Total 512
Table 5 stresses three main facts, the first being that the three main types of equipment /systems used for space heating in Cyprus are central heating 29.2%, split units 16.9% and portable heaters 39.3%. Portable heaters are high energy consumption equipment which can impact considerably on electricity consumption of a house. The project tackled this problem during the research and development by suggesting alternative more energy efficient types of heating system. The second point is that heating demands in Cyprus last for 4 months per year (41.8%) and the daily hours of operation are 3-5 hours (46.2%).[35][36][37]
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During the simulation of the buildings in this project special attention was paid to the system working profile hours which mean that the heating systems work only when necessary and not all the time. The third one is that the annual energy consumption for space heating per household is 642 KWh (electricity) and 331litres (heating oil). [35][36][37]
Table 6: Energy consumption for space cooling [35][36][37]
PROPORTION OF HOUSEHOLDS HAVING AIR CONDITIONING EQUIPMENT 80.8%
SURFACE AREA OF DWELLINGS COOLED DURING THE HOT SEASON OF THE REFERENCE (%) YEAR < 51 m2 64.1 51 - 100 m2 24.2 101 - 150 m2 7.8 151 - 200 m2 2.6 201 - 250 m2 0.8 251 - 300 m2 0.3 301 - 350 m2 0.1 > 350 m2 0.1
MONTHS OF OPERATION OF THE AIR CONDITIONING EQUIPMENT DURING THE REFERENCE (%) YEAR < 1 month 2.1 1 month 4.5 2 months 27.7 3 months 25.4 4 months 34.1 5 months 5.0 6 months 1.2 > 6 months 0.0
HOURS OF DAILY OPERATION OF THE AIR CONDITIONING EQUIPMENT DURING THE PERIOD (%) OF USE <= 2 hours 17.7 3 - 5 hours 41.1 6 - 8 hours 26.8 9 - 11 hours 9.9 12 - 14 hours 3.6 15 - 17 hours 0.6 > 17 hours 0.3
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Table 6 shows that 80.8% of households use air conditioning systems with the largest percentage (64.1%) used for cooling areas smaller than 51m2. According to the statistics, however, use of air conditioning for three months is 34.1% which is the highest percentage among the other categories of use. The annual electricity consumption for space cooling per household is 1107 KWh [35][36][37]. It is noteworthy that Cyprus has a hot climate which is becoming hotter, based on the weather results of this research. This signifies an increasing demand of cooling load requiring more electricity during the year. During the research new methods and energy efficient measures were introduced to reduce cooling demand while leaving comfort levels unaffected.[35][36][37]
Table 7 shows the energy consumption for water heating revealing the potential for further development of solar base heating systems in houses(29.3% of systems connected with the central heating are and 91.6% of solar heaters). However, the proportion of households with hot water storage tanks is 95.9%. [38]Due to the hot climate and Cyprus sunshine solar heaters need to be employed more in the Cyprus building sector but not for water heating use alone. Developing technology such as photovoltaics or central heating systems offers new systems using solar power to satisfy energy demands in the house. These potential systems were examined and developed during the research and the simulation procedures[35][36][37].
Table 7: Energy consumption for water heating [35][36][37]
AVAILABILITY OF DIFFERENT TYPES OF SYSTEMS USED FOR WATER HEATING AS A (%) PERCENTAGE OF TOTAL HOUSEHOLDS System connected with central heating 29.3 Solar heater 91.6 Individual electric heater with storage tank 3.6 Individual LPG (gas) heater with storage tank 1.0 Electric continuous-flow water heater 6.7 LPG (gas) continuous-flow water heater 4.9 Other 2.1 PROPORTION OF HOUSEHOLDS HAVING HOT WATER STORAGE TANK(S) 95.9%
CAPACITY OF HOT WATER STORAGE TANK(S) (%) < 100 litres 2.7 100 - 149 litres 4.8 150 - 199 litres 79.4 200 - 249 litres 10.8 250 - 299 litres 1.3 >= 300 litres 1.0
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ANNUAL ENERGY CONSUMPTION FOR WATER HEATING PER HOUSEHOLD Electricity 382 KWh Heating oil 24 litres Kerosene 2 litres Liquefied petroleum gas 8 kg Biomass (e.g. wood) 2 kg
ANNUAL ENERGY CONSUMPTION FOR WATER HEATING PER HOUSEHOLD (in kilograms of oil (kgoe) equivalent) Electricity 33 Heating oil 20 Kerosene 2 Liquefied petroleum gas 9 Biomass (e.g. wood) 1 Total 65
According to the Cyprus Institute of Energy[37], in 1995 total energy consumption was 199,000 toe and had increased to 319,000 toe by 2007. Electricity consumption in 1995 was reported as 65,000 toe increasing to 138,000 toe in 2007, meaning 212% growth in 12 years. [37] The Cyprus Institute of Energy reports that this dramatic increase is mostly due to climate change in Cyprus and the installation of air conditioning systems in almost every household.[37] Due to the absence of building energy regulations in Cyprus prior to EU accession it was difficult to find data for energy performance of new buildings constructed under the new building directive (since 1/1/2008). After 2008 the new standard for a household is minimum B which means 140KWh/m2/year based on reference building (heating, cooling, hot water and lighting).[37]
1.9. Energy supply and demand - impact of growth and climate change
Of all the various issues arising when analysing the Cyprus energy market the future energy gap is the most significant due firstly to the continual growth and development on the island and secondly to climate change. Both problems must be faced as they impact strongly on energy supply and demand. The analysis of the climate and energy factors was essential in order to clarify the problem and for the proposed solution of ZEBs to be effective.
A recent study based on the hypothesis that the average temperature in the Eastern Mediterranean is expected to increase by 1oC by 2030 sought to quantify the likely impact upon electricity consumption in Cyprus.
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The impact of climate change on electricity consumption was estimated to be 2.9% higher in 2030 compared to the no climate change scenario. [38] Moreover, future climate change will affect the extra peak electricity load requirements possibly amounting to 65-75MW in 2020 and 85-95MW in 2030, showing increased requirements for reserve capacity. [38]
The economic crisis and oil fuel prices lead along a one-way street, i.e. the development of new types of building and renovation of the old ones. This method will offer solutions not only to the problems concerning electricity supply but will also create a new era where buildings will become energy producers instead of being consumers as they are now.
1.10. Theoretical research conclusions
The electricity analysis was essential for understanding the building sector’s impact on the energy supply. The analysis revealed future problems with the Cyprus electricity supplies due to growing demand and power plants unready or unable to cope, or if they can cope, the costs of satisfying electricity demands will be excessive. As the building sector has a strong impact on energy supplies, immediate measures should help Cyprus to reduce energy demand while creating more energy efficient buildings. This transformation will not only help to save energy but will also contribute positively to the generation of energy by developing renewable systems in buildings. To conclude, as Cyprus is dependent on oil imports and products for producing electricity, there will in the future (sooner rather than later) be a problem with electricity supplies in Cyprus due to increasing energy demands and climate change. This problem can be solved but at what cost to the consumers? A low cost solution is the transformation of the building sector in combination with other energy measures as described above and action needs to be taken if Cyprus is to be able to respond to future high demands for electricity.
The development of the concept of zero energy buildings in hot climate countries such as Cyprus has great potential and could offer multiple solutions related with energy sufficiency and adoption of buildings to climate change. The building transformation can be characterised as a long term investment but offering immediate results in energy saving.
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Chapter 2:Methodology of the project and yearly work description.
2. Introduction
Basic definitions and explanations were needed concerning the concept of zero energy buildings to enable the project to define the problem and produce a solution, The theoretical approach investigated the following issues:
1. The worldwide problem of energy with special focus on Cyprus, which comprises the case study. 2. The correlation between the economic and energy crisis, influenced by climate changes. 3. The history of building, building types and their impact on energy consumption. 4. Zero energy building concepts as a solution to economic and energy problems. 5. Building simulation as a tool to achieve zero energy buildings.
Through theoretical research the project explored the causes of problems of building energy, different types of buildings, definitions of zero energy buildings in various countries, regulations and standards for buildings energy and all available technology, methods and materials that can be used in the building sector. Thus the analysis presents the project’s requirements and the point of focus during the practical part of the research with simulation of building models.
Literary sources comprised publications and articles published by Universities, research groups, organizations, and brands of the building sector while eBooks and books related to the issue were also essential for an in depth exploration of buildings and energy consumption.
The practical part of the project was the simulation of different building models to apply and check the theoretical findings and reach conclusions on the development of zero energy buildings in hot climate countries. In order to produce useful results, the project used a computer based simulation program of the thermal performance of buildings, which is an established methodology for predicting the probable levels of energy consumption, associated carbon dioxide emissions and for assessing the impact of selected design options. During the building simulation various parameters such as weather, orientation, shading methods, insulation methods, buildings materials, glazing, the HVAC systems and building operation profiles were checked to discover the appropriate combination of factors for achieving zero energy building goals.
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However, large quantities of data are required to produce such simulations. Much of the information, e.g. regarding building form and fabric, was easy to assemble. Nevertheless weather data, consisting of statistically defensible assemblies of appropriate information, (so called “Test Reference Years” or “EPW weather files”) was more problematic. In contrast to many other countries, there are no such data sets in Cyprus or, where they do exist, they are not up-to-date. The geomorphological specificities of Cyprus are such that one standard set of weather data are not applicable to the whole island. However, at a number of sites in Cyprus ample weather data was available, which was processed into a form suitable for use in building simulations.
Both theoretical and experimental aspects were vital for the project’s success as the concept of zero energy buildings is relatively new.
2.1. Background
Creating a building simulation may be a difficult procedure due to the complexity of the building and interactions between the elements and the systems. During the analysis of the building many factors were involved and meticulous methodology was essential to achieve reduction of energy and the aim of the zero energy building. The development of the Zero Energy Building concept demands a multidimensional approach; hence, building evaluation had to be carried out from different perspectives and simultaneously with different system limitations with the multidimensional analysis of many factors being targeted to ensure simulation reliability.
Theoretical research revealed that the ZEB concept presents a multi-faceted problem so it was impossible to take a one-sided approach to the problem and so, after completing the theoretical research, the project determined which were the most crucial factors having the greatest impact on the energy consumption of the building.
The project focuses on the following factors most affecting energy consumption:
1. The current climate of the case study and the local microclimate 2. Building type and use 3. Building orientation and shape 4. Building construction materials 5. Different types and methods of insulation 6. Internal and external shading factors
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7. Glazing issues 8. The type of HVAC systems 9. Domestic hot water systems 10. Lighting and radiation from appliances, systems and people 11. Buildings operation profiles 12. Installation of photovoltaic systems on the building
These factors are listed in order of importance according to the factors most affecting the other building elements, systems and comfort conditions.
2.2. Outline the project steps
The project methodology included seven important phases that would provide reliable results and achieve the initial goal.
The first was to define the problem since an incorrect definition could waste time. During this step the project defined the research objectives, addressed the issues to be analyzed, determined the level of detail, estimated the resources needed to complete the project and created a planning chart.
Step two was the design of the study. Here, steps of the previous phase were analyzed in depth with more weight given to the technical aspects of the project. Information and data was also gathered and the number of required models estimated, the programs or tools were determined.
In step three conceptual models were created. This involved the modelling approach which included decisions concerning the representation of a system in terms of capabilities and elements supplied by the selected simulation tool. This approach needed to focus on how the development of the models fulfilled all the objectives of the project with each individual issue being examined.
Step four was the formulation of inputs, assumptions, and process definition. Data collection and task analysis were performed, all the assumptions listed, the input data analyzed, the runtime parameters specified and the conceptual models validated.
In step five the final simulation models were built, verified, and validated and the sixth step involved simulating the models and attempting to improve them.
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The final step of documentation and presentation of the results played a key role in the achievement of the simulation procedure and was often performed in parallel with the other phases. Due to the long term simulation and the huge amount of outcome data, detailed documentation was essential for recording the model’s input, possible changes, observations around the simulation procedure and comments on results. The end of this phase included the final results, discussion and explanation of the model’s results, further areas of study recommended and final project report and presentation.
To ensure success, this project needed a clear-cut definition of the problem and effective organization of the work to be done. The ambitiously planned project faced many challenges (factors affecting building design, two different building categories with three different building types and huge amounts of data to be analysed) all of which were dealt with good project programming and an accurate and robust methodology procedure.
2.3. Project methodology and approach to the problem
The challenges of this research involved the handling of huge amounts of different data and the factors needing to be analysed for a successful development of zero energy building in a hot climate country. First it was decided what type of buildings would be analysed based on the building category impacting most on the Cyprus energy system but the Cyprus building sector is developing and there is a need to transform all building types. Hence, it was decided to examine and simulate three different types of building:
i. One 19-storey residential building, which is the first tall residential building in the whole of Cyprus. ii. One 2-storey family house, which is very common in the Cyprus building market. iii. One 6-storey office building, which represents the new type of office building in Cyprus.
The significance of the residential building sector in terms of energy consumption is well acknowledged. In this view the knowledge of the way the residential building stock of Cyprus behaves in terms of energy consumption is quite valuable since it will assist policy makers to formulate targeted measures aiming the improvement of energy efficiency and setting current legal standards and benchmarks in the energy performance certificate, a requirement of the 2002/91/EC Directive.[4]
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Next, possible actions were defined for achieving the ZEB goal on these three building types starting by identifying the main factors that most influence energy consumption in Cyprus building. Theoretical research and previous experience led to the exploration of the following factors[45]:
1. Insulation materials and methods: it is comparatively recently that the building sector in Cyprus started using insulation and any research would be useful. 2. Glazing issues: determining the most suitable glazing for Cyprus was essential. 3. Shading factors: the benefits and the impact of shading factors on the energy demand need to be explored as Cyprus has considerable sunshine throughout the year. 4. HVAC systems: minimizing heating and cooling demand loads through climate responsive design and conservation practices. In addition it was necessary to deploy suitable efficient HVAC systems which respond to the building’s needs and occupants’ comfort. 5. Operation profiles: optimisation of building operation through simulation programs and optimising the building systems operation by using operation profiles according to the current weather. 6. New technologies: the involvement and combination of new more efficient technologies and different measures and strategies. 7. Renewable energy: utilisation of renewable energy sources/systems such as daylight, passive solar heating, photovoltaics and solar water heating systems.
These are seven vital factors needing to be addressed to reduce buildings’ energy use and transform buildings into producers of energy.
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Figure 15: Project methodology description After defining the building types and factors that most affect energy consumption (Figure 15), the next important step was to choose the programs to carry out the building modelling and the simulation procedure. The IES program[46], which is capable of carrying out this type of simulation, was available at the University. In addition, it helped that the IES has the Sketch Up as plug in program and so it was possible to develop the 3D modelling of the buildings.
Before the simulation procedure of the real models, a simple building was tested in order to explore the program abilities and possible limitations. The test results revealed essential issues.
The first issue concerned the problem of the simulation weather file used by the program. After extensive research and communication with the IES Program Company[46] it was concluded that the simulation weather file is based on outdated weather data and could not be used for the current simulation. Thus there arose a new need to create the necessary simulation weather files by obtaining 10 years meteorological data.
The second issue concerned problems with available materials as the IES material data of did not include some materials used in the Cyprus building sector. Consequently, these materials needed to be created to accurately simulate the building models and be as realistic as possible.
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The third issue concerned the geometry of the building models. The test building was developed in sketch up program and an issue arose during the development of the 3D when the plug in of the IES[46] program recognised the 3D model as boxes; thus it was necessary to keep the building design simple.
A revision of the methodology and the inclusion of another two important steps before the simulation procedure became necessary. These extra steps were not related directly with the initial goal but they are of vital significance for the project development and success.
The first step concerned the construction of simulation weather files. A new simulation weather file had to be created in order to input them in the IES program and to create these update files it was necessary to collect weather data from Cyprus meteorological stations.
The second step concerned creation of new materials. Data collection about the construction materials being used in the building sector of Cyprus was essential and helped to create the materials for an accurate simulation.
Figure 16 shows the final methodology and approach to the problems of the project after the problems with the simulation were discovered.
Figure 16: Final methodology description.
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2.4. Yearly work description.
A first step towards achieving the project goals was the so called Gantt chart (Appendix A). Figure 17 is a brief description of the three-year plan describing how the initial objectives were developed for achieving the final aim of Zero energy building.
The first year’s work involved defining the problem and goals, the set of hypotheses and objectives, literature research and review, collection of weather and materials data, weather analysis, and establishing collaboration with a building company as a source to provide the necessary information.
The first year’s target was the thorough investigation of the weather data from three different towns, Limassol and Larnaca (coastal towns) and Nicosia (situated inland) as a priority for the current research.
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Figure 17: Flow chart of the 3 years of planning
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The lack of essential hourly climate data, referred to as test reference year (TRY) or EPW weather simulation file, is the main barrier to the wider use of TRY in developing countries. The problem is that TRYs - which are common in Europe - are frequently unavailable because the raw hourly climate data is difficult to obtain and presents comparatively short measuring periods and a limited set of climate parameters. There was no up-to-date TRY file for Cyprus and the only available data relates to hourly temperature, wind speed and direction and humidity ratio. The weather stations are situated in Nicosia, Limassol and Larnaca and the data covers about 11 years.
Weather data for analysis had to be collected from various sources such as the Meteorological Service of the Ministry of Agriculture, Natural Resources and Environment of Cyprus, the US Department of Energy and the American Society of Heating, Refrigerating and Air- Conditioning Engineers (ASHRAE). The analysis is based on 11 years hourly data including temperatures, wind speed and direction, solar radiation and relative humidity values the outcome was a detailed comparison between the two towns of Nicosia and Limassol indicating variations between the two places. The final target was the development of weather simulation files (EPW or TRY) for the two towns which do not yet exist in the Cyprus Government Meteorological Services. Moreover, useful information about the weather of Cyprus over the last 11 years was collected and will be used in the building design and simulation.
Various programs and TRY files from CIBSE and the US department of Energy provided useful information for the simulation but this was not enough. The accuracy of the files was problematic as most were based on data collected at only the airport station in Larnaca and so the different climatic conditions in the other towns could not be recorded in the file. For instance, Larnaca is coastal whereas Nicosia is situated inland so it is impossible for both towns to experience the same weather conditions. The second problem concerned the lack of up-to-date data: most of the records stop in 1999 and the weather conditions in Cyprus may have changed over the last 10 years, so a simulation based on dates before 1999 may be unreliable.
The purpose of the first year’s research was to identify the problem of the weather data records and to generate weather simulation files representative of the climate zone of Cyprus, meaning that values of main climate parameters will be as close as possible to long term mean values.
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True correlation between different parameters, especially temperature and solar radiation, was essential for the project.
The final outcome of the two years’ research and analysis of weather data showed the differences and variations between the towns of Cyprus. This provided the opportunity for further study and understanding of the weather effect on the simulation. Moreover, the research and results contributed to the creation of up-to-date weather simulation files. Comparison of such files reveals issues with the weather data files used by the simulation program and also with the range of locations for which weather files are available. Preliminary simulation demonstrates significant percentage differences between the three towns of Nicosia, Larnaca and Limassol with respect to energy consumption by boilers and chillers and the total carbon emissions of the exemplar building. These differences indicate that weather records for Larnaca are not representative of the whole island and that individual weather files for each town are needed. The analysis of the weather records helps to understand the behaviour of thermal loads and energy demands of buildings in Cyprus and directs designers to apply measures to reduce energy demands. According to the findings, the weather file of the simulation program and its update need special attention to ensure accurate and representative results.
Concurrently with weather research and analysis, the building models were in process of being developed as the new weather data files needed to be tried and different comparisons made. The IES simulation program
In order to apply sustainable strategies resulting in better buildings, issues needed to be considered and addressed from the earliest concept stage as the entire design process was based on sustainable and low energy strategies. As previously stated, the project target was one sustainable, low energy/carbon building which would comply with European standards and legislation and so building performance analysis and energy modelling together with high quality information about the building energy consumption and emissions were essential. To ensure the detail and accuracy of the models, they were developed in parallel with the design and all other areas of performance analysis.
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Furthermore, there was a comparative analysis at an early stage to check feasibility and quantify and extract information that would influence final decisions.
During the second year the focus was on weather data comparison, the collection and analysis of the electric power supply of Cyprus, development of the exemplar building and the building models, revision of the initial schedule and meeting with the engineers of the case study buildings. That time also saw the further collection and analysis of the different weather data completed and final comparisons between the files initiated. The air temperature, the relative humidity, wind speed and direction and sun radiation were analyzed with Excel® and Origin 8 and comparisons made between data sets for Limassol and Nicosia. Furthermore, the data from the Meteorological Services of Cyprus from 1997 to 2008 was compared with the US Department of Energy data from 1985 to 1995 for the two towns. The aim of the analysis was to reveal the weather data sets related to variations of weather data in the different towns. The objective of the analysis was to also ascertain the effect of climate change on the microclimate as the weather conditions in Cyprus may have changed over the past 11 years and a simulation based on that period may not be reliable.
Another important issue concerned the electric power supply of Cyprus and its high and ever increasing energy requirements. Based on the results, the use of electricity is expected to grow over the next ten years at rates slightly above GDP growth, as was the case over the last fifteen years. There is a significant potential for more rational use of energy in buildings if the building sector turns to zero energy buildings policies. At the moment Cyprus is totally dependent on imports for its supply of conventional energy.
As the analysis of electricity was closely related to the weather data analysis, there were significant results regarding the connection between the microclimate and its effect on buildings energy consumption. The final target of the analysis was to correlate energy demands (electricity demand) with different weather profiles in Cyprus in order to understand buildings and people’s behaviour whilst simultaneously identifying the areas requiring improvement once the shortcomings were identified. In addition, these results enabled the project to set proper guidelines and take correct decisions for the performance of Zero Energy Building in countries with hot climates,.
The establishment of cooperation with Meteorological Service of Cyprus and construction companies and organizations was a significant step. The first contact was with the Meteorological Service of Cyprus, cooperation being based on two different criteria: firstly,
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on the exchange of experiences and knowledge around the issue of the weather files and the climate change of Cyprus, and secondly, the possible contribution of the Meteorological Service of Cyprus to issues concerning data, updates of weather data or the need for measuring instruments. Furthermore, cooperation was established with a large Cypriot construction company based on the fact that the company in question is constructing one of the largest buildings in Cyprus and that this building would be used as a case study for the project. Additionally, meetings were held with the company project engineers who gave useful advice concerning the research.
The third year project focused on the actual problem of developing ZEB’s in a hot climate. Different types of buildings, i.e. one commercial, one residential building and one ordinary Cypriot dwelling were analysed. The tall residential building was the primary case study of this project and was analyzed in detail. The three buildings models were simulated with an IES simulation package and the use of building simulation technology helped to evaluate a variety of envelope thermal characteristics and low carbon technologies, in an integrated manner at the early design stage, in order to assist in the delivery of sustainable Zero Energy Building with high rating of energy performance. To achieve these aims, a building energy simulation software IES Virtual Environment (VE) was used to conduct a series of sensitivity analyses on a set of design parameters which had good prospects of influencing building performance. During the final year, to determine effective design solutions for comfortable and energy efficient buildings involved identifying how the parameters interact and how the interaction influenced the building’s performance.
Throughout the third year, extensive research of the literature focused on the available renewable sources that can be used in zero energy building. Renewable technology played an important role in developing the project as it helped to reduce CO2 emissions while also reducing or eliminating demand for electricity. This combination of suitable design, choice of the right materials and insulation and the use of renewable technology proved the key to reducing energy demand and improving building performance in hot climatic conditions.
The final outcome of this research was the in-depth and comprehensive investigation around the issue of zero energy buildings, proposed guidelines for a successful zero energy carbon building in hot climates, and the scientific contribution to the scientific community through publications and conferences.
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Chapter 3: Building types and characteristics
3. Introduction
Around the world, many different types of buildings can be found and each individual type has its own multiple and varying needs. It is therefore essential at this point to present the different types of buildings in general, as this report will focus on the building sector and its energy demands. Despite the fact that in the literature review there is a substantial amount of terminology relating to various building types, the general idea of this division of buildings into categories is the same. Usually the buildings are categorised according to their use.
At this point it is essential to additionally mention that many of the buildings in most countries were built before the introduction of energy regulations and these buildings will be around for at least the next 40 years. As Figure 18 shows, in Europe, 50% of the buildings were built before 1975.[47] [48]
Figure 18:Age distribution of the European housing stock. [48]
The research aim concerns the building sector and therefore the study of building types and characteristics was important. Dissimilar building uses and operation demand different approaches to decreasing energy consumption. This research investigated three types of buildings and provided useful results for each category. The following paragraphs focus on the building types, characteristics and profiles and relate them to energy demands based on their operation.
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3.1. The building as an energy system
As previously mentioned, building types varied but most important for this study is the fact that the buildings are complex systems. Hence a multidimensional approach would give considerably different results related to aspects of energy. These results influence the development of the project and affect the final outcome.
Figure 19: The building as an energy system-Multidimensional approach.
Figure 19 shows the important factors that affect the operation of any building type and at the same time impact on the energy demands of the building. The main function of a building over a period of time is to offer people protection, safety and comfort. Moreover, the comfort level of the building is achieved through the energy consumption for various functions, such as the lighting, the heating and cooling, the ventilation systems and other operations. All these are related with indoor environment but the external building environment is also important.
The building’s external environment interacts and affects the indoor environment and therefore it is necessary to see these two environments as a whole system. For example, the surrounding buildings and trees strongly influence the energy demand of a building by shading; this is something that will affect the cooling and the heating processes. In addition, the climate and microclimate conditions also influence the energy needs and will need to be taken into account.
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To sum up, all these factors affect the energy balance of the building and its performance. In general incoming energy needs to be in balance with outgoing energy losses; energy losses could be in different forms such as heat. The balance between outgoing and incoming energy is an essential key to achieving low energy building performance. Unfortunately this balance is affected not only by the building systems operation but also by the building’s construction. Obviously the calculation of the energy building needs is complicated and to simplify the process a building simulation is used during the development of the research. More about the building simulation can be found in the following chapters.
3.2. Building categories: Commercial Buildings
The commercial building type can include an office, a shop or a factory. There are differences between these subcategories of building types from the point of view of energy demand and operation. However, this research focuses on the office building which will be studied in detail.
Office buildings are usually located in the city centres because these buildings offer people public services, including transportation. It is well known that urbanization in most countries carries negative consequences for the city centres, for example, high land prices. Consequently, the design and use of these buildings must be compact and offer the maximum possible service. The use of the building is generally defined by the services that are offered and the space is then separated into offices and support facilities.[49]
Quite frequently, another characteristic of office buildings is their old-fashioned style as well as other limitations due to the fact that many countries conserve the old buildings in city centres. Thus improvements for energy conservation or better energy performance in these buildings are limited and therefore it is difficult to apply low energy strategies. In addition, the development of the surrounding area and new tower blocks are a significant factor that influences the energy performance of building due to the shade provided. [49]
On the other hand, new office buildings have great potential to save energy as new technologies and design can be used and have capacity for development. Another point which helps low energy designs to be applied to office buildings is the wide use of curtain walls, mainly in most of the downtown buildings.
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Some problems which can arise from the use of this kind of building are lack of thermal comfort, lack of orientation and the overuse of glass, where are not compatible with low energy buildings design. New approaches to office buildings have begun to be applied and they are now being transformed into high technology buildings which offer better services to the people who work there.
The creation of the energy profile of an office building is a very real challenge as the building is mostly occupied during working weekdays mainly and only during the day(depending on the region). In addition electrical equipment such as computer screens, photocopiers and other office equipment consume energy while at the same time contributing to the overheating of the building. This is the main reason why even in cold countries there is high demand for cooling during a large part of the year. Unfortunately, heat from the office equipment cannot be controlled but it can be evaluated, calculated and reduced with the use of air conditioning systems. On one hand, air conditioning systems are solving the problem and providing people with indoor comfort, but on the other hand they are increasing the energy demands of the building. The overheating problem in this specific category can be dealt within various ways such as early stage design which would deploy solar control windows and shading devices to prevent overheating from the sun (especially in hot climate countries) or passive methods of natural ventilation of the building which will extract the hot air from the building.
A key factor of successful low energy office buildings is the positioning of the private office at the rear of the building. As a result of this design, the artificial lighting will be reduced as natural lights are directed further into the building. This will have a significant impact not only on energy demands but also on the HVAC systems. Nevertheless, Office Buildings require a careful design which takes into account the climate, the orientation, the facade design, the HVAC, shading from the surrounding buildings and the complex interactions between lighting. [49][50][51]
3.3.Building categories: Residential buildings
Residential buildings can be divided into several subcategories. According to the literature review, the main categories are single family house (detached and semi-detached), terraced house and apartment blocks.[51][52]However, big and small differences can be found in all of them depending on the climatic variations of each country.
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For example, in hot climates the essential requirement is for cooling and keeping temperatures comfortable all over the house. This is achieved by the use of control systems, high insulation materials, shading systems and double or triple glazing. Additionally, in this way, energy demands and costs remain under control. In addition, there is a high use of passive or active solar systems in these hot climate countries. On the other hand, buildings in cold climates have different needs to achieve temperature comfort. In these climates, the need for heating is essential but this is directly related with other parameters, such as low emissivity windows, good insulation materials and good design. When designing in these climates, it is essential to consider the thermal mass of the building, as this may contribute to the heating during the night.[53]
Residential buildings are an indispensable type of building as people spend most of their time there; as a result, these building need to provide satisfactory degrees of comfort. At the same time the operation, the energy demand and the comfort levels are based on the occupants’ behaviour. However, the heating and cooling systems, the building envelope insulation, the shading factors and window types cannot be discounted as important components of the building. As a result it is vital to design and construct buildings that need as little energy as possible throughout their lifetimes.
All this leads to the conclusion that the building needs to be faced and developed as an energy system at an early stage of design. Only in this way will it be possible to achieve energy efficient building with low energy demands but at the same time high quality standards of comfort. Additionally, where residential buildings are concerned, it is easy to use renewable sources and cover the energy needs of a house because the demand is not so high. For example, photovoltaic systems can be used as the main source of energy, minimizing the
CO2 emissions and the operational costs of the building.
All the above types of buildings constitute the common categories that serve the different human needs. However, there are many subcategories which are adapted specifically for each different climate and different needs.
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3.4. Current building stock situation in Cyprus
The research around the building stock and characteristics reveals significant and useful results since the study analyzes three different types of buildings. This subchapter reviews the literature concerning the case study building stock and investigates the building sector tendencies.
According to the most recent report of the Cyprus Statistical Service [54] in 2010 there are important key points (Table 8 to 13)which are related to this research. The new residential buildings accounted for 46,4% of the total gross output of the subsector of building construction and civil engineering, new non-residential buildings (offices, shops, hotels, factories, airport buildings, etc.) for 20,9%, new civil engineering projects (roads and bridges, water supply and sewerage networks, telecommunications and electricity lines etc.) for 24,5% and repairs and maintenance for the remaining 8,2%.[55] The total number of new dwellings completed fell by 19.3% to 13,434 dwelling units compared to 16,644 in the previous year.[55] By administrative district, the number of new dwellings is distributed as follows: Lefkosia (Nicosia) 3,921, Ammochostos (Famagusta) 1,221, Larnaka 2,378, Lemesos (Limassol) 3,108 and Pafos 2,806.[55] The average area per dwelling completed in 2010 was 205 square metres for houses and 125 square metres for apartments, compared to 203 and 122 square metres, respectively, in 2009.[55]The cost of construction per square metre (excluding the value of land) rose from €896 in 2009 to €920 in 2010 for houses and from €783 to €808 for apartments.[55]The dwelling stock at the end of the year amounted to 409 thousand dwelling units, of which 62.7% were in urban areas. [55] The labour costs in construction increased by 3.5% compared to an increase of 4.8% in 2009. The price index of construction materials recorded a rise of 2.7% compared to a decline of 3.5% in 2009. [55]
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Table 8: Building permits authorized in Cyprus by type of project 2009-2010 [56][57]
2 0 0 9 2 0 1 0 Code CC TYPE OF PROJECT 1996 Number Area Value Dwelling Number Area Value Dwelling (m²) (€000΄s) Units (m²) (€000΄s) Units
11 Residential buildings 6,482 2,723,777 2,282,514 16,688 6,426 2,448,379 2,092,275 14,312 111 Single houses 4,988 1,298,410 1,133,925 6,233 5,036 1,252,538 1,117,236 5,511 112 Buildings with two or more housing units 1,491 1,419,835 1,143,739 10,455 1,386 1,189,575 970,009 8,801 113 Residencies for communities 3 5,532 4,850 4 6,266 5,030 12 Non-residential buildings 1,532 403,787 333,984 1,221 447,599 374,668 121 Hotels and similar buildings 143 7,774 16,656 152 10,410 17,522 122 Office builidngs 106 103,545 82,892 137 172,140 147,198 123 Wholesale and retail trade buildings 131 58,847 46,902 109 35,560 29,824 124 Transport and communication buildings 2 2,727 2,205 3 13,657 26,800 125 Industrial buildings and warehouses 281 166,337 98,055 237 148,434 81,944 126 Public entertainment buildings and buildings used for recreational, educational or medical purposes 116 26,089 36,416 134 44,526 46,470 127 Other non-residential buildings 753 38,468 50,858 449 22,872 24,910 2 Civil engineering projects 319 8,895 137,344 409 21,927 103,892 3 Plots division 543 55,746 641 62,903 4 Road construction 74 6,237 80 5,762
Total 8,950 3,136,459 2,815,825 16,688 8,777 2,917,905 2,639,500 14,312 Big Contsructions 1,023 1,767,808 1,521,225 9,744 946 1,628,332 1,378,365 8,160 Small Constructions 7,927 1,368,651 1,294,600 6,944 7,831 1,289,573 1,261,135 6,152
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Table 9: Building permits authorized by district and area 2009-2010[56][57]
2 0 0 9 2 0 1 0
DIS TRICT
Number Area Value Dwelling Number Area Value Dwelling (m²) (€000΄s) Units (m²) (€000΄s) Units
LEFKO S IA 3,111 1,088,007 908,065 4,712 2,891 1,054,645 900,895 4,142 Urban 1,764 737,497 609,781 3,531 1,684 734,682 623,280 2,948 Rural 1,347 350,510 298,284 1,181 1,207 319,963 277,615 1,194
AMMOCHOSTOS 535 275,358 228,595 1,890 474 198,451 170,227 1,177 Urban Rural 535 275,358 228,595 1,890 474 198,451 170,227 1,177
LARNAKA 1,327 472,174 478,005 2,463 1,371 526,188 497,789 2,904 Urban 702 268,301 225,866 1,278 699 284,408 235,148 1,436 Rural 625 203,873 252,139 1,185 672 241,780 262,641 1,468
LEMES O S 2,556 803,030 719,625 4,054 2,600 742,101 714,678 3,627 Urban 1,393 590,262 509,900 2,959 1,302 500,020 474,292 2,302 Rural 1,163 212,768 209,725 1,095 1,298 242,081 240,386 1,325
PAFOS 1,421 497,890 481,535 3,569 1,441 396,520 355,911 2,462 Urban 642 280,622 234,803 1,831 605 186,040 163,554 1,088 Rural 779 217,268 246,732 1,738 836 210,480 192,357 1,374
TOTAL 8,950 3,136,459 2,815,825 16,688 8,777 2,917,905 2,639,500 14,312 Urban 4,501 1,876,682 1,580,350 9,599 4,290 1,705,150 1,496,274 7,774 Rural 4,449 1,259,777 1,235,475 7,089 4,487 1,212,755 1,143,226 6,538
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Table 10: Number of dwellings units authorized by size of project and district 2009-2010 [58]
2 0 0 9 2 0 1 0 S IZE O F PRO JECT Urban Rural Total Urban Rural Total
Big projects 5,935 3,809 9,744 4,718 3,442 8,160
Lefkosia 2,323 387 2,710 1,959 492 2,451 Ammochostos 1,478 1,478 840 840 Larnaka 691 733 1,424 875 993 1,868 Lemesos 1,754 265 2,019 1,275 373 1,648 Pafos 1,167 946 2,113 609 744 1,353
Small projects 3,664 3,280 6,944 3,056 3,096 6,152
Lefkosia 1,208 794 2,002 989 702 1,691 Ammochostos 412 412 337 337 Larnaka 587 452 1,039 561 475 1,036 Lemesos 1,205 830 2,035 1,027 952 1,979 Pafos 664 792 1,456 479 630 1,109
ALL PRO JECTS 9,599 7,089 16,688 7,774 6,538 14,312
Lefkosia 3,531 1,181 4,712 2,948 1,194 4,142 Ammochostos 1,890 1,890 1,177 1,177 Larnaka 1,278 1,185 2,463 1,436 1,468 2,904 Lemesos 2,959 1,095 4,054 2,302 1,325 3,627 Pafos 1,831 1,738 3,569 1,088 1,374 2,462
Table 11: Building permits authorized by type of the project and area size 2010[59]
Number of Permits by Area Size (m²) Code CC TYPE OF PROJECT 91- 181- 361- 631- 901- 1351- 1801- Total 0 1-90 2701 + 1996 180 360 630 900 1350 1800 2700
11 Residential buildings 1,551 524 783 1,794 845 296 293 134 113 93 6,426 111 Single houses 1,108 522 771 1,704 645 139 58 37 31 21 5,036 112 Buildings with two or more housing units 440 2 12 90 200 157 235 97 82 71 1,386 113 Residencies for communities 3 0 0 0 0 0 0 0 0 1 4 12 Non-residential buildings 754 98 55 67 70 37 41 26 40 33 1,221 121 Hotels and similar buildings 112 17 6 11 2 2 0 0 2 0 152 122 Office builidngs 50 6 6 11 8 5 10 9 15 17 137 123 Wholesale and retail trade buildings 59 10 4 9 11 5 5 1 2 3 109 124 Transport and communication buildings 0 0 0 0 0 0 0 0 1 2 3 125 Industrial buildings and warehouses 104 6 5 18 32 21 17 13 12 9 237 126 Public entertainment buildings and buildings used for recreational, educational or medical purposes 79 5 12 11 10 2 6 1 6 2 134 127 Other non-residential buildings 350 54 22 7 7 2 3 2 2 0 449 2 Civil engineering projects 283 106 6 7 2 3 0 0 1 1 409 3 Plots division 641 0 0 0 0 0 0 0 0 0 641 4 Road construction 80 0 0 0 0 0 0 0 0 0 80
Total 3,309 728 844 1,868 917 336 334 160 154 127 8,777
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Table 12: Building permits authorized by type of the project 2010[60]
1212 Other tourist accommodation 0 0 0 Camping sites and labour rest houses 0 0 0 122 Office buildings 137 172,140 147,198 1220 Office buildings 137 172,140 147,198 Offices 41 16,139 17,695 Office blocks 64 143,951 117,479 Banks, co-operative institutions and insurance offices 11 3,528 3,509 Local government offices 15 7,155 7,485 Offices of associations and other services 6 1,367 1,030 123 Wholesale and retail trade buildings 109 35,560 29,824 1230 Buildings used in trade 109 35,560 29,824 Shops 74 17,604 13,986 Department stores and commercial centres 9 11,640 9,722 Show rooms 8 3,821 3,080 Kiosks 7 482 396
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Table 13: Construction and housing in Cyprus for 1995-2010 [60]
CONSTRUCTION AND HOUSING 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Gross output at current market prices (€mn) 1,221.2 1,293.3 1,310.5 1,364.0 1,424.0 1,498.8 1,600.8 1,799.0 2,067.5 2,369.8 2,739.3 3,123.8 3,778.1 4,277.5 3,376.3 3,048.8
Buildings construction and civil engineering 1,049.0 1,106.3 1,117.4 1,155.2 1,197.1 1,221.0 1,312.2 1,437.3 1,605.9 1,835.0 2,098.3 2,358.4 2,787.6 3,109.1 2,656.6 2,492.7
Land and buildings development 172.2 187.0 193.1 208.8 226.9 277.8 288.6 361.7 461.6 534.8 641.0 765.4 990.5 1,168.4 719.7 556.1
Value added at current market prices (€mn) 715.1 756.0 771.7 805.2 828.0 853.9 924.2 1,001.2 1,139.7 1,268.3 1,417.7 1,636.9 1,939.8 2,168.1 1,731.2 1,556.4
Buildings construction and civil engineering 580.9 609.6 617.1 638.8 652.7 657.0 714.2 785.1 865.4 972.6 1,062.5 1,197.3 1,380.1 1,506.4 1,316.6 1,250.5
Land and buildings development 134.2 146.4 154.6 166.4 175.3 196.9 210.0 216.1 274.3 295.7 355.2 439.6 559.7 661.7 414.6 305.9
New construction (€mn) 951.3 998.7 993.0 1,022.8 1,054.4 1,053.4 1,136.2 1,253.6 1,421.9 1,640.9 1,870.4 2,121.2 2,545.6 2,840.3 2,346.3 2,287.1
Residential buildings 503.0 564.7 534.3 503.9 525.7 534.3 554.8 620.9 750.9 931.7 1,123.0 1,252.0 1,414.9 1,573.9 1,237.1 1,156.4
Non-residential buildings 201.4 233.4 235.4 261.1 275.8 268.1 304.1 333.7 344.5 373.1 375.4 452.1 646.5 718.7 570.6 519.9
Civil engineering projects 246.9 200.6 223.3 257.8 252.9 251.0 277.3 299.0 326.5 336.1 372.0 417.1 484.2 547.7 538.6 610.8
Other receipts, incl. repairs and maintenance (€mn) 97.7 107.6 124.4 132.4 142.7 167.6 176.0 183.7 184.0 194.1 227.9 237.2 242.0 268.8 310.3 205.6
Price index of main construction materials (2005=100) 76.6 78.4 80.1 80.3 77.5 80.2 82.4 84.3 88.2 95.4 100.0 105.1 110.7 121.5 117.2 120.4
Labour cost index (2005=100) 60.3 64.2 68.7 72.1 74.6 78.4 82.3 86.4 91.4 95.1 100.0 105.3 110.1 116.7 122.3 126.6
Local sales of cement (thousand tonnes) 1,017 1,014 905 926 935 945 1,055 1,183 1,303 1,537 1,589 1,627 1,790 1,940 1,439 1,335
Dwelling stock (thousand) 255 261 268 275 282 288 293 299 305 314 325 341 358 374 392 409
New dwellings completed (number) 6,891 7,157 7,148 6,599 6,327 5,083 6,641 6,059 8,734 11,013 16,416 16,647 16,501 18,195 16,644 13,434
Average area per new dwelling (square metres) 183 190 188 184 192 189 186 195 172 162 153 149 152 151 154 159
Average cost per square metre of new dwellings completed in the private sector (€) 473 501 521 541 554 571 580 598 624 654 692 736 772 808 842 869
Building permits authorized
Number of permits 7,259 7,156 6,614 6,558 6,429 6,096 6,499 6,856 7,548 8,252 9,098 9,794 9,521 8,896 8,950 8,777
Value of permits (€mn) 992.6 1,076.2 999.7 1,037.4 983.9 1,055.1 1,330.8 1,503.1 1,760.7 1,994.6 2,288.9 2,473.4 2,782.3 2,904.6 2,815.8 2,639.5
Area of permits (thousand square metres) n.a. n.a. n.a. n.a. n.a. 1,651.3 1,992.8 2,178.0 2,590.5 3,015.7 3,417.0 3,507.5 3,612.8 3,689.1 3,136.5 2,917.9 Number of dwelling units 8,776 8,474 7,024 6,370 5,625 6,087 6,895 8,127 11,955 15,743 18,770 18,915 20,486 20,082 16,688 14,312
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Generally the building stock in Cyprus consists of apartments and single family houses. However, over the past three years the economic crisis, the increase of the labour costs, the increasing cost of construction materials as well as the fact that the price of land continuously rises, semi-detached houses and apartments are becoming more commonplace. In addition, the building sector seeks cheaper methods of construction beyond the traditional standard methods, which is one of the keys to transforming the building sector and developing zero energy buildings.
Zero energy building aims to decrease costs, increase efficiency and utilize solar energy. The benefits of the development of zero energy building will not only be in the primary costs but will also reduce operational costs as energy prices rise and will increase comfort levels. Further statistical analysis relating to information on the existing building stock, on used heating systems in multifamily houses and on refurbishment and new construction activities in the multifamily housing sector will be presented in the following chapters.
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Chapter 4: A critical look at European building energy regulations
4.1.Energy regulations in Europe
An important component of this current study is the consideration of European building sectors and policies. Obviously, the study targets worldwide influences and contributions but it is mainly the European facts which will affect the development of the research of the study and fortunately the European members have already accomplished a lot related to energy issues, low energy buildings, renewable energy technologies and environmental problems. [61] In Europe residential and commercial buildings consume 40% of the total final energy and this percentage is the largest single share. In addition, the EU economy is affected by various activities related to buildings; these activities represent about 9% of EU GDP and 7-8% of EU employment of the EU economy. [61] The impacts of the buildings sector in the EU are significant considering the social, cultural and historic values. The EU’s growth, energy and climate objectives can be achieved via the EU building sector as it plays an important role to the energy consumption and economy. However, the improvement of the sector will result in an improvement in the level of comfort and possibly lower energy bills for European citizens. [61] Due to the significant impacts of buildings on the EU economy and energy policies, the European members have prepared regulations which relate to the energy efficiency of buildings. The Commission Communication Energy policy for Europe have stated that “…energy efficiency of buildings is an important part of broader initiatives on achieving EU energy and climate change objectives and plays a role in limiting the negative impact of high energy prices.” [61]
European members and the Commission urged the European Council and the European Parliament to follow a proactive approach towards realizing the energy savings potential. [61]The Commission responded immediately, whilst continuing the development of strategic initiatives on energy issues and energy efficiency, all focusing on the building sector. Through this policy economic, social and environmental benefits can be achieved in the future as the potentials for cost effective energy savings is about 30% of the whole sector’s expected energy consumption by 2020. [61] [62]Estimates show that savings of up to 15% of total energy are achievable with the current EU measures. In addition, further potentials for energy savings are identified at 15% and these potentials can be accomplished at very low
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CO2 decreased costs. According to the Commission, this is due to the relatively low cost of energy relevant investments (when combined with other construction and renovation works in a building) and the very high value of energy savings compared to the other sectors, making energy saving a very attractive approach for tackling the challenge of climate change. [61] [62]
In the opinion of the author, one of the greatest mistakes that all governments make is to consider buildings a “local” issue. Buildings all over the EU are a general issue and must concern all the members. In every country the energy consumption of buildings has a significant impact on its economy and ultimately on the EU economy as a whole. It is essential for the building sector to meet the EU policy objectives and in this way change the future of energy. Buildings are not a local issue; they are in fact an issue that concerns all EU members and consequently all EU citizens. One of the most important issues affecting EU citizens is high energy prices and the unpredictability of the future of energy, which is affected by a building’s energy consumption. The EU members have already taken action on buildings, providing more and better information on energy saving options.[61] [62]
4.2.EU legislative action
Through the efforts of the European Union for energy savings in the building sector, various types of legislation have been passed, such as the Energy Performance of Buildings Directive (EPBD), Eco-design of Energy-using Products Directive, and Energy End-use Efficiency and Energy Services Directive. One of the most important is the Energy Performance of Buildings Directive (EPBD) which is the “leading tool that provides for a holistic approach towards efficient energy use in the buildings sector.” [61] [62]
The EPBD considers local conditions and requirements whilst at the same time focusing on improving the cost effectiveness of the general energy building performance. Also in EPBD, issues such as energy needs for water and space heating, cooling, ventilation and lighting are considered and analysed. In addition, for the energy use of buildings the EPBD provides different regulatory (for example. minimum energy performance requirements) and information based instruments (for example. certificates and inspection requirements).[61] [62]
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According to the EPBD, the Member States have to set up minimum energy performance requirements for new buildings, as well as for large existing ones that need to undergo major renovation. This means that all of these buildings should meet certain national and regional determined minimum energy performance levels, with the aim of achieving improved energy performance, thermal comfort and lower energy bills, through the introduction of an energy performance certification scheme that provides information on the energy needs of a building and on what can be improved. This should be presented to potential buyers/tenants so that they have an independent assessment of the energy-use aspects of the buildings, thus enabling informed decisions to be made concern in the establishment of a system to inspect medium- and large-sized heating and air-conditioning systems at regular intervals so that their energy performance can be monitored and optimized. It is these systems that are mainly targeted as they have very high energy savings potentials. Promotion campaigns can be undertaken by Member States as an alternative to inspections provided that it can be stressed that this approach would be of equal importance. [61] [62]
The above actions which are provided by the EPBD will become effective at different times of a building’s life. For instance, during the construction stage the minimum energy performance requirements should be enforced. In addition, during the construction or the rent or sale of a new house, an energy performance certificate is a compulsory requirement, the certificate being valid for a maximum period of 10 years. Heating, ventilation, and air conditioning systems (HVAC) need to be inspected more frequently as these systems easily change their energy performance. As stated within the EPBD, “…in the case of medium-sized boilers and air conditioning systems Member States are entitled to decide on the frequency of inspections regardless of whether or not the building is for sale or rent (as is the case for the energy performance certificate), whereas for large boilers it should be every two years, etc..” [61] [62]
Through the EPBD the European members have a chance to develop methodologies for evaluation and calculation of the energy performance of buildings, always bearing in mind the European standards. Also, members have an obligation to make sure that inspection and certifications are carried out by qualified experts. However, the EPBD obliges Member States to lay down holistic methodologies, requirements, and inspection and certification regimes to rate the energy performance of buildings at a national/regional level, rather than fixing
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concrete EU-wide energy performance requirements. [62] Another important factor is that the European members have the chance to go further than the minimum guidelines provided by the EPBD, and develop more ambitious measures. [62]
In the past, before the revision of the EPBD, the concept of energy savings in buildings was developed by only a few countries. The energy efficient measures and the mechanism for the adjustment of these measures could not be found in any building codes or any other legislation within most European member states. The contribution of the EPBD was significant for most of the members whilst at the same time being a great challenge for quality improvements of the building sectors.
Generally, the EPBD managed to generate important changes with reference to the issues of the energy efficiencies of buildings, which from being a minor subject in the political agendas was transformed into a priority of governments and politicians. Additionally, the EPBD has had a significant impact on the building codes of EU members and has also come to the attention of European citizens. Considering the implementation costs of the EPBD, the EU members reported that they are moderate costs, but with significant improvements in terms of energy savings in the buildings sector stimulated by the Directive.[63]
It is obvious the EPBD have made a positive contribution to EU members’ attempts to change and reduce the energy demand from buildings as much as possible. The main and most important contributions are: the setting of energy performance requirements for the first time in some EU member states (Cyprus, Malta and Estonia), the majority of EPBD members have tightened the current standards; a change in approach to specifying building codes resulted in the previous code of a maximum permitted U-value being replaced by a code based on overall building performance which included requirements for technical systems such as HVAC plant and lighting; within some Member states with very different approaches to setting building codes, a certain amount of harmonisation was introduced; for the first time in most Member states, standards for building renovation were introduced; for the first time, requirements for certification of buildings, and for the inspection of boilers and air conditioning systems were introduced for all Member States whereas only one or two states has previously had such systems.
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4.3. Provisions, impact and implementation of the recast EPBD.
4.3.1. Recast EPBD Provisions
The EPBD was undoubtedly an important step for European building regulations and since then many measures have been undertaken by its members. However, there is great potential for further cost effective energy savings which can be achieved through the implementation of new measures and policies. The limitations of the first EPBD combined with sector complexity and the market failures were the main challenges and obstacles for the EPBD in recasting and introducing new policies.
In 2010, the European members decide to tackle the obstacles by suggesting improvements to the EPBD with the inclusion of more than a few new or strengthened requirements. The additional requirements of the so called recast EPBD are:
1. Strengthening of the energy certification of buildings: this requirement was already included in the first EPBD but without satisfactory results due to a weakness in its application. Hence the new EPBD demands that an energy performance certificate must be issued for any new building or for any building that is sold. 2. Heating and cooling systems inspection report: the heating and air conditioning systems must be checked regarding the energy performance of the system and probable cost effective improvements. After the inspection a report needs to be issued to the tenant or owner of the building. 3. Energy requirements at cost optimal levels need to be set up: all the members need to make certain minimum energy performance requirements for the building while the same time setting them at cost optimal levels. A comparative methodology framework will calculate the cost optimal levels and this methodology will be defined by the Commission. 4. Abolishment of the 1000 m² threshold for major renovations: In the previous EPDB there were limitations, the 1000m2threshold for major renovation, where this threshold left out 72% of the building stock. The new EPDB revised the requirement by insisting that all buildings, new or existing, which are undergoing major renovation, should be upgraded concerning the energy performance. This upgrade will aim to meet the minimum energy performance requirements of the building.
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5. National Plans improvement or development targeting the increase of zero energy buildings: the European members should increase the number of ZEB through the introduction and development of national plan, which will include information about policies, measures and targets on ZEB 6. Setting up EU–wide nearly zero energy buildings requirements: the recast EPBD targeting the end of the 2020 where all newly constructed buildings should be nearly zero energy and their energy should come to a large extent from renewable sources. 7. Independent control systems for EPC and inspection reports: the EU members’ authorities are responsible to check the quality of the energy performance certificates and inspection reports.
4.3.2.Predicted Impact assessment
It is estimated that the recast EPBD and the new requirements will achieve further savings among the European members. Some predictions of the potential savings are set out Table 14:
Table 14: Calculated impacts and benefits to be achieved with the EPBD recast reinforcements. [63]
Final energy savings CO2 emission Job creation in in 2020 (Mtoe/a) reductions 2020 in 2020 (Mt/a) Abolition of the 1,000 m² threshold 20 51 75000 for major renovations Setting up energy performance 5 (up to 10 in 2030) 13 (up to 24 in 2030) Up to 82000 requirements at cost optimal levels Setting up EU–wide nearly zero >15 >41 +++ energy buildings requirements and development of national plans Independent control systems for 21 57 60000 EPCs Requiring an inspection report for 5 15-20 46000 heating and air conditioning systems
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4.3.3.Implementation of recast EPBD
According to Article 5 of the recast EPBD all the EU members should calculate the energy performance of buildings with use of a new cost optimal methodology. The exact definition of the cost optimal level is given by the directive as the “…energy performance level which leads to the lowest cost during the estimated economic lifecycle…”[63] and “…shall lie within the range of performance levels where the cost benefit analysis calculated over the estimated economic lifecycle is positive”. [63]
However, a comparative methodology framework for the calculation of the cost optimal levels had been established by the EU commission.[63] This methodology will differ according to the different types and age of buildings and will calculate the cost optimal levels of minimum energy performance requirements for the buildings and building elements.
Once the methodology is published, the EU members need to report their specific application of the methodology to the Commission. In addition, these reports could be included in the National Energy Efficiency Action Plans above the Energy Services Directive (Directive 2006/32/EC).As previously mentioned, the EU members had calculated cost optimal levels of minimum energy performance requirements by the use of the methodology framework, but they will need to take into account other related parameters such as the climatic conditions and the practical accessibility of energy infrastructure. Finally, the results of the procedure can be used as a reference by EU members to compare with the minimum energy performance requirements.
Another important step of the recast EPBD is the target of 2020 where all new buildings should be nearly zero energy, starting from the governmental buildings which will be nearly zero energy by the end of 2018. According to the EPBD definition “nearly zero energy building means a building that has a very good energy performance where “…nearly zero energy building means a building that has a very high energy performance where ‘the nearly zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources, including energy from renewable sources produced on-site or nearby”.[63]
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However the EPBD recast introduced the obligation of members to set a national definition of zero energy buildings and methods in order to improve the energy performance of new buildings by 2015. The national definition will be followed by policies, financial and other measures, and renewable energy information in order to promote the idea of ZEB.
4.4. EPBD impact in Building codes of the EU members.
As previously mentioned, the EPBD was the first important step of the European Union to suggest to all members a general framework for the building energy demand. It needs to be mentioned that after the oil crisis, quite a few member states had already in cluded energy requirements or thermal performance requirements in their building codes. On the other hand, the requirements of the EPBD which is based on “whole building” approach was a real challenge for all the EU members to change their building codes and transform the building sectors. The most significant change in the building codes throughout these years is the fact that the requirements of the EPBD have begun to change from a descriptive to a performance based approach.
However, the recast EPBD aims at further changes in the energy performance requirements through the application of the cost optimality concept. According to Article 5 and annex III of the EPBD recast, all the EU members have to set up their national requirements regarding the cost optimal levels through the establishment of a calculation methodology. It is expected that the introduction of cost optimality into building regulations will make an important impact in many EU member states and will result in improved and strengthened requirements.
In the years to come all these changes will affect the building codes, giving them a dynamic phase which is essential for the transformation of the building sector. It is crucial that the environmental and climatic impacts are addressed through the EPBD requirements in the building codes. The transformation of building sector is not at all easy and demands an approach from a variety of perspectives such as political, technical and economical.
The development of this study depends on building regulations and standards as the case study is in Cyprus, a member of the European Union. In addition the building requirements constitute the guidelines of this project and at the same time present a very real challenge to search for further energy improvements in the building sector.
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4.5. In the direction of Zero energy as a building code.
As new products transform and improve the current market, the building sector is constantly changing and producing evermore efficient and cost effective buildings. Low energy windows, more efficient boilers, highly efficient heat pumps, passive house heating systems and photovoltaic systems are just a small sample of the market evolution and improvement which is affecting the building sector.
On the other hand, energy prices and different options for heating and cooling are changing the limits for what can be set as minimum requirements in building codes. Furthermore, climate change and the evolution of the market are introducing new comfort levels in buildings and hence new buildings codes.
The zero energy buildings concept is strongly based on the success of the market evolution and building transformation. New technology, energy efficiency solutions and products are the result of continuous interaction between the market, the building sector and building codes. The building codes should be targeted at removing the least efficient parts of new buildings and compelling them to be more efficient.
In order to achieve the ZEB idea and hence sustainable development, buildings energy consumption needs to be set at minimum or even at zero energy level. As previously mentioned, some countries have already taken action and initiatives by defining the zero energy as their target through the building codes.
In Denmark, new demands for energy efficiency in buildings codes were introduced in 2006 for different types of buildings. The concept of the building codes is based on the energy performance where special requirements were set for the building envelope. According to these requirements the new buildings need to have an annual energy demand of 55kWh/m2for heating and hot water. In the new building code two new low energy classes are defined at less than 75 % (class 2) and less than 50 % (class 1) of the building code. An action plan has been agreed on by Parliament whereby building codes will be strengthened to low energy class 2 in 2010 and to low energy class 1 in 2015. Thus in 2015 the demands in the building codes will be at correspond to the demands in the Passive House regarding both overall consumption and heating load in the building. [64]
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In the UK, the aim of a government decision in 2006 was that all the new buildings should be Zero Carbon by 2016. In order for this decision to be achievable, it is supported by various small actions. In 2010, a 25% improvement in the energy/carbon performance was set in building regulations; then in 2013, a 44% improvement; then, finally, in 2016, to zero carbon buildings (some of these targets have been changed or improved).[64] The tightening of building regulations is included in the UK action plan where by over the next decade a series of small steps aim to improve energy efficiency of new buildings.
In the main, in order to achieve the ZEB the zero idea needs to be passed into the building codes of the EU members. It is crucial to convert the idea into an action plan with set time limitations and standards for the buildings energy efficiency.
4.6. Implementation of the EPBD in Cyprus
While the general responsibility for the EPBD implementation in Cyprus belongs to the Ministry of Commerce, Industry & Tourism (MCIT), the MCIT is cooperating with other governmental bodies, private consultants, scientific institutions, engineering associations and land developers for the EPBD application and achievement.
Before the accession of Cyprus into the European Union, the building codes did not include any energy regulations or guidelines and therefore after the accession the adjustment of the EPBD required changes and development of the current legislation. Three legal documents have been approved by the House of Representatives in order to introduce and implement the EPBD requirements in Cyprus. These laws are:
1. The Law for the Regulation of the Energy Performance of Buildings of 2006, L.142 (I)/2006.[65][66][67] 2. The Amendment of the Law for the Regulation of Roads and Buildings, L.101 (I)/2006. [65][66][67] 3. The Roads and Buildings (Energy Performance of Buildings) Regulations, Κ.Δ.Π.429/2006. [65][66][67] 4. The Energy Certification for Buildings Regulations of 2008. [68][69][70] 5. The Inspection and Maintenance of Boilers and Air-conditioning systems Regulations 2008. [65][66][67] 6. The Inspection and Maintenance of Boilers and Air-conditioning systems Ministerial order. [65][66][67]
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The sub-committees are composed of representatives from Governmental Departments or Services, Non-Governmental Organisations, Technical Chamber Associations and other parties involved in the building sector. The Law for the Regulation of the Energy Performance of Buildings of 2006, L.142(I)/2006 is overseen by these members who are responsible for advising on and suggesting different methodologies for the calculation of energy performance of buildings to the Minister of Commerce, Industry and Tourism. In compliance this procedure, in 2007 two ministerial orders were issued. The first one relates to the methodology for the calculation of the energy performance of buildings, while the second one concerns the minimum requirements for the energy performance of buildings. Both of them target the enforcement of the Law for the Regulation of the Energy Performance of Buildings of 2006, L.142(I)/2006. The first ministerial order regarding the energy performance of buildings were targeted at the minimum requirements but were restricted to the envelope insulation of the building. [65][66][67]
4.6.1.The energy performance certificate
The introduction of the Energy Performance Certificate (EPC) aims to supply important information for building energy performance in relation to total energy. In order to classify the building, a calculation is made based on the building type and the typical use of the building, of primary energy consumption per year. The result is an energy label which classifies the buildings on an efficiency scale ranging from A, where there is high energy efficiency, to G, where there is poor efficiency. In addition, an estimation of CO2 emissions is provided by the EP, the estimation being a result of the calculation of energy consumption of the building and the renewable sources energy.
The most important point is that from 2010 residential and commercial buildings, new or under renovation must have an EPC in order to be approved and have permission to start the building process. Moreover, a building should be at least Class B in order to be approved for construction.
The certification and the advisory report are produced by experts using software for calculating the energy performance of buildings. In addition, the experts must plan the advisory report in advance making comments and suggestions for the improvement of the building’s energy performance. The Energy Service is responsible for checking the quality and validity of the issued certificate and giving the final approval. The cost of the certificate depends upon the type of building and is not restricted by law.
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The advisory report will be issued by the software based on a standard check of some of the results and there will be an option for the expert to add further comments and recommendations.
4.6.2. Inspections - Status of implementation
The Law for the Regulation of the Energy Performance of Buildings of 2006 includes the inspection and maintenance of boilers, central heating systems and air-conditioning systems. The law came into force on 4th of January 2009 and experts started the technical inspections.
With regard to the energy savings resulting from the implementation of the energy performance of buildings directive, the estimates are based on the calculation methodology used for the energy certification of the buildings (asset rating, standardised conditions). The reference value for a new house according to the asset rating of the EPBD will be 140kwh/m2/year. The energy savings will be around 30% compared with the existing building stock.
In 2010 under a Ministerial Order the inspection of air-conditioning started, introducing a crucial new requirement for the system inspections. The inspection requirement is compulsory for all systems larger than 12kW and for systems that total/add up to nominal power 50kW in the same building. Table 15 shows the frequency of inspections of air- conditions systems.
Table 15: Frequency of inspections of air-conditioning systems [65][66]
Nominal power of the Inspection Completion of first system frequency inspection
12kW – 250 kW Every 5 years 31st of December 2011
≥250 kW Every 3 years 31st of December 2011
>50 kW Every 5 years 31st of December 2010
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4.6.3.The Methodology for Assessing the Energy Performance of Buildings (MAEPB)
Article 3 of the EPBD requires a methodology to be applied at a local or Regional level to calculate the energy performance of buildings. [67][68][69] The Cyprus authorities response to the requirement was the development of the Methodology for Assessing the Energy Performance of Buildings (MAEPB). [67][68][69] An appendix to the EPBD states that the calculation must be based on a general framework, which includes at least the following factors:
1. Thermal characteristics of the building (shell and internal partitions, may include air tightness) 2. Heating installation and hot water supply, including their thermal characteristics 3. Air conditioning installation 4. Natural and mechanical ventilation 5. Built-in lighting installation (mainly in non-residential sector) 6. Position and orientation of buildings, including outdoor climate 7. Passive solar systems and solar protection 8. Indoor climatic conditions, including the designed indoor climate
The calculation should also relate to/include the influence on energy performance of the following aspects where relevant:
1. Active solar systems, and other heating and electricity systems based on renewable energy sources 2. Electricity produced by combined heat and power 3. District or block heating or cooling systems 4. Natural lighting
Buildings should be classified into different categories for the purposes of the calculation. Article 3 of the EPBD calls for the calculation to be transparent, that is, the way in which it works should be explained. The definition of “energy performance” in Article 2 of the EPBD refers to the estimation of energy needed for the “standardised use” [67][68][69] of the building; this estimation is intended to enable comparisons between buildings to be made on the basis of their intrinsic properties rather than being dependent on the user’s choice of operating patterns which may exist in practice. In addition Article 3 permits the use of CO2
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emissions or Primary energy as a means of comparison, rather than energy consumption, in the standard methodology.
At the core of the MAEPB, the calculation process compares the primary energy of the proposed building with those of a “reference building”. This constitutes setting the standards in order to satisfy the requirements of Article 4 of the EPBD. The characteristics of the reference building are given in Appendix B.
The MAEPB Cyprus requires the use of standard databases or information sources for:
1. Environmental conditions and operating/occupation patterns in each part of each building 2. Weather data 3. Heating and cooling generator efficiencies
The reason for this is to encourage consistency between repeated evaluations of the proposals. Standard databases are also available for Heating and cooling system efficiencies and for building component parameters
The MAEPB also requires that the U values of specific construction elements of the envelope in the proposed building are checked for compliance with minimum performance. It also requires that the output report adopts a standard format, so that officers of the Competent Authority will not have to interpret the ways in which different tools present the results. [67][68][69]
In the MAEPB buildings for evaluation should be defined in terms of:
1. the zones in which identifiable, standardised activities take place 2. the geometry of each zone; its floor area, the areas of the building fabric elements which surround it, and their location with respect to the exterior or other interior conditioned zones 3. the thermal performance characteristics of the building fabric elements surrounding each zone 4. the building services systems which serve each zone (or groups of zones) 5. weather location
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The performance requirement is for the proposed building to use less Primary Energy based on the U-values given, the HVAC efficiencies, the lighting and the HWS. This is derived from those of the Reference Building.
The reference building has:
1. The same geometry, orientation and usage as the evaluated building 2. The same standard operating patterns 3. The same weather data 4. Building fabric, glazing type, air tightness and HVAC and lighting plant substituted by specified standard items.
4.6.4.European standards (CEN) used by MAEPB
The CEN umbrella document, Standards supporting the Energy Performance of Buildings Directive (EPBD), PG-N37(Table 16) [68][69], contains an outline of a calculation procedure for assessing the energy performance of buildings. It includes a list of some thirty European standards both existing and yet to be written, which together form a calculation methodology (Published standards can be obtained from the Cyprus Organisation for Standardisation). Government policy is to adopt them generally, and MAEPB follows them as far as is practicable.
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A brief summary of all the CEN standards used by MAEPB is presented in Table 16.
Table 16: Summary of CEN standards used by MAEPB [69]
a/c CEN standards Description 1 PG-N37 Standards supporting the Energy Performance of Buildings Directive [69] 2 EN 15193-1 Energy requirements for lighting –Lighting energy estimation [69] 3 EN 15217 Methods of expressing energy performance and for energy certification of buildings [69] 4 EN 15243 Ventilation for buildings – Calculation of room temperatures and of load and energy for buildings with room conditioning systems [69] 5 EN ISO Review of standards dealing with calculation of heat transmission in buildings – 13786:2005 Thermal performance of building components – Dynamic thermal characteristics – Calculation methods [69] 6 EN ISO 13789 Review of standards dealing with calculation of heat transmission in buildings – Thermal performance of buildings –Transmission and ventilation heat transfer coefficients – Calculation methods [69] 7 EN ISO 13790 Energy performance of buildings – Calculation of energy use for space heating and cooling [69] 8 EN15316-3 Heating systems in buildings – Method for calculation of system energy requirements and system efficiencies –Domestic hot water systems [69] 9 EN 15316-4-3- Heating systems in buildings. Method for calculation of system energy requirements 2007 and system efficiencies -Heat generation systems, thermal solar systems [69]
4.6.5. Summarizing the impact of the EPBD at Cyprus national level
The Island of Cyprus was one of those European countries which were without any energy building regulations or policy. The implementation of the EPBD was the very first attempt to introduce measures and policies for the energy efficiency and consumption of the building sector. In 2007 the building regulations of Cyprus included requirements for thermal insulation of the building envelope. [70]
Subsequently, in 2009,new requirements for the minimum energy performance were issued by the Energy authority. The requirements for Building envelope U-values were the same, but this time were further strengthened as they regulate the building as a whole with the new requirements being the average U-value of the building envelope and the Energy Performance Certificate (EPC) with a B category.[70]
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According to the guidelines of the U-value calculation, the method includes the U-value of each element of the building and its corresponding area and averaged over the whole area of the building envelope. The roof and the floor are not included in this calculation. It should be noted that the maximum U-values for the residential and commercial buildings differ.[70]
Table 17: Minimum energy performance requirements for new building and all buildings above 1,000 m2 that undergo a major renovation (2007 regulations)[70]
Description U-value (W/m2K) Comments Horizontal structural elements of the shell ≤0.75 Wall and structural elements of the shell ≤0.85 Not applied to passive systems Windows and external doors ≤3.8 Not applied to shop windows Floor in contact with unheated spaces ≤2.0
The Energy Performance Certificate (EPC) with a B category was an important step for The Cyprus Building Regulations. In order to achieve the B energy category as a minimum requirement for the building’s needs, a building needs to have the same or less primary energy than the reference building. The reference building (Table 18) is defined as a building which already has thermal characteristics values for external walls, floors and windows. These values are slightly lower than the minimum requirement values for every individual element. In addition the reference building has values for the heating and air conditioning efficiency, hot water and lighting efficiency systems, that already have been determined. All these parameters are stricter when it concerns non-residential buildings.[70]
Table 18: U-values for the reference building in Cyprus [70]
Exposed element U-value (W/m2K) U-value (W/m2K) (residential) (non-Residential) Roofs1 (irrespective of pitch) 0.6375 0.6375 Walls 0.7225 0.7225 Floors (except for ground floors, below) 0.6375 0.6375 Ground floors 1.6 1.6 Windows, roof windows, roof lights, and pedestrian 3.23 3.23 doors Vehicle access and similar large doors Same as real Same as real building building 1 Any part of a roof having a pitch greater or equal to 70o is considered as a wall
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A crucial decision for the integration of renewable energy systems (RES) in new buildings was a Ministerial order of 2009 for the promotion of low energy buildings. According to the order the installation of solar thermal systems in order to cover the hot water need became mandatory for all new residential buildings. Most importantly, for the first time the size and efficiency of the systems are under regulation and have to be designed according to the “Technical Guide for the Installation of Solar Thermal Systems”. Additionally, all new buildings have to present the necessary infrastructure in case of a future decision for RES installation and production of energy. [70]
The efficiency of technical systems in the energy performance of buildings assumed more importance after the introduction of a minimum B-class requirement on the certificate. The outcome of this requirement is the increased interest of engineers in heat pumps and condensing boilers. In addition, the overall energy performance of the building calculation reveals the need for integrated solar strategies and external shading design.
4.7. The need for further action
As previously mentioned, the European Union has made important progress in the buildings sector. However, while the different legislations and directives contribute to the Members’ building codes, these positive steps are unfortunately not enough due to the rapid speed of technological progress and climatic changes. More action is needed from all EU members as the energy problems have global impacts. Undoubtedly, there are great potentials in terms of cost efficient savings which remain unutilized and must be used as soon as possible.
Another problem is the assessment of the impact of EPBD. At the moment, the short period of EPBD implementation has resulted in the collection of insufficient data to allow a complete evaluation of the impacts. According to the European Impact Assessment for the EPBD, “rough calculations show that, if fully and properly implemented, the energy savings from the EPBD can be as much as 96 Mtoe final energy in 2020, this being 6.5% of EU final energy demand.” [70][71] Some experts believe that the full impact of the EPBD may not be yet realized. Admittedly the potentials of social, economic and environmental benefits are not explored or exploited at EU level. The reasons for this, at some level, are the limitations of the current EPBD, but in addition, the current situation is also affected by the complexity of the building sector and market failures. Obviously more effort and action are needed for the utilization of further potentials. [70][71]
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There are still many challenges to be faced regarding the energy efficiency of buildings; it can be achieved through a variety of ways such as: the recall of the EPBD and replacing it with soft law instruments - information, voluntary activities, financing measures, etc; continuing the implementation of current measures - 'business as usual' or ‘do nothing more’; revising the EPBD - complement and improve the current version. [70][71]
Nevertheless, of all the proposed ways of reaching EU policy goals in general, the energy savings and energy efficiency of buildings the most real and at same time the most immediately achievable is the revision of EPBD –expansion and improvement of the current version. Already many of the members are adapting their building codes and legislation by considering the current EPBD and any wide changes that will cause confusion. With the revision of the current EPBD, the principles and their essence remain the same but the changes will target their effectiveness. In this case, the current Directive will be the starting point for the revised instrument and will constitute its 'backbone'. [70][71]
It is essential for Europe to support the EPBD because of its vital contribution to members. According to the European Impact Assessment,
“it should be emphasized that the solution is an integrated mix of policy instruments and thus other non-regulatory measures, although not sufficient on their own, are necessary to complement the implementation of the Directive.” [70][71]
In addition, EPBD already includes so called “soft law” instruments and there is a need to further develop them. Another crucial point is to strengthen all efforts to provide more financial and fiscal incentives, information, training of experts, and agreement on voluntary action.
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Chapter 5: The zero energy building (ZEB) concepts
5.1 Introduction.
The research proposal concerns the development of the idea of zero energy building in hot climate countries. Although the concept of low energy buildings is very common, there is still no exact definition of what a low energy building is and the absence of specific criteria around the notion of zero energy raises crucial questions: What exactly is a low energy or zero energy building? How well is it defined by law or by standards or measures? What criteria does the zero energy building need to meet? Finally and most important, do any European countries share common definitions?
All across Europe low energy or zero energy buildings are currently the subject of major interest, associated as they are with environmental protection and resource conservation. The concept of low or zero energy encompasses at the least a major reduction in the use of fossil fuels or at best the elimination of reliance. Based on this idea, there are various ways of reducing the energy demand of buildings, such as high insulation, efficient HVAC systems, air tightness, insulated windows and shading factors. All the measures are aimed at offering a better indoor environment with lower energy consumption and lower environmental impact.
The aim of this background research are to extract useful information from the multitude of different criteria, definitions and terminologies related to zero energy buildings and then to address the above mentioned questions in order to combine the common criteria of all these standards and their possible consequences.
5.2. The zero energy idea.
The concept of zero energy building (ZEBs)may not be something new. Over the past years, different engineers and scientists have proposed new ideas and technologies in their attempts to adopt new approaches for the contraction and designs of the buildings. Unfortunately, until now these new concepts have only been ideas which have been supported by only a few.
However, phrases like ‘a zero energy house’, ‘a neutral energy autonomous house’ or ‘an energy-independent house’ have appeared in articles since the late seventies, when the consequences of the oil crisis first became apparent. It was then that the big issue arose in reference to natural sources and fossil fuels which caused researchers to look for alternative energy sources and to start discussing energy use. Despite the seriousness of the energy problems, the first approaches of the buildings sector were only to talk about energy efficient
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technologies and passive solutions. Additionally, the word ‘zero’ involved/referred to only the energy for heating, cooling and domestic water. [72]
Over the years, ZEB definitions varied due to the differing approaches of all the engineers and scientists. Many articles and papers were published around this issue of ZEB, but lack of a common understanding and definition provoked wide discussion. During all these attempts to reach one common definition, a variety of different definitions were given, each involving different factors and approaches such as ‘how the zero energy goal is achieved’, ‘what is the building grid interaction’, ‘unequal energy qualities in the energy balance’, ‘what are the project boundaries for the balance?’[72]
In general, all the approaches from all over the world aim at creating new generation buildings which will be energy efficient with a low operation energy profile and energy that needs to be supplied from renewable sources. The issue of zero energy building is still under research, as scientists attempt to define in words what energy efficiency, renewable sources
technology, low CO2 emissions and the environmental impacts are. As stated in the “Zero Energy Buildings, A critical look at the definition report”,“the heart of the ZEB concept is the idea that buildings can meet all their energy requirements from low-cost, locally available, non-polluting, renewable sources.”[72]
A common definition of zero energy building is essential and needs to be adopted by all governments so that it will be possible to develop common strategies for the buildings sector and for all to follow the same principles. The transformation of the building sector, energy savings and the stabilization of the climate will be possible only when global action and cooperation are achieved.
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5.3. Europe steering towards low energy buildings
For many years now, a weak point of Europe’s directives has been the inability to set a complete definition of low/ zero energy building. Undoubtedly, over the years there have been many proposed definitions from all over Europe but the problem has always been the fact that the approaches differ, sometimes even within the same country. A list of definitions for EU countries is presented in Table 19. [76]
Table 19: Different definitions for Low energy building [73]
Country Official definition Austria 1. Low energy building = annual heating energy consumption below 60-40 KWh/m²gross area 30 % above standard performance) 2. Passive building = Feist passive house standard (15 kWh/m² per useful area (Styria) and per heated area (Tyrol) Belgium 1. Low Energy Class 1 for houses: 40 % lower than standard levels, 30 % lower for office and school buildings 2. Very low Energy class: 60 % reduction for houses, 45 % for schools and office buildings Czech 1. Low energy class: 51 – 97 kWh/m2 p.a. Republic 2. Very low energy class: below 51 kWh/m² p.a., also passive house standard of 15 kWh/m2 is used Denmark 1. Low Energy Class 1 = calculated energy performance is 50% lower than the minimum requirement for new buildings 2. Low Energy Class 2 = calculated energy performance is 25% lower than the minimum requirement for new buildings (i.e. for residential buildings = 70 +2200/A kWh/m² per year where A is the heated gross floor area, and for other buildings = 95+2200/A kWh/m² per year (includes electricity for building integrated lighting) Finland 1. Low energy standard: 40 % better than standard buildings France 1. New dwellings: the average annual requirement for heating, cooling, ventilation, hot water and lighting must be lower than 50 kWh/m² (in primary energy). This ranges from 40 kWh/m² to 65 kWh/m² depending on the climatic area and altitude. 2. Other buildings: the average annual requirement for heating, cooling, ventilation, hot water and lighting must be 50% lower than current Building Regulation requirements for new buildings 3. For renovation: 80 kWh/m² as of 2009 Germany 1. Residential Low Energy Building requirements = kfW60 (60kWh/(m²•a) or KfW40 (40 kWh/(m²•a)) maximum energy consumption 2. Passive House = KfW-40 buildings with an annual heat demand lower than 15 kWh/m² and total consumption lower than 120 kWh/m² England & Graduated minimum requirements over time: Wales 1. 2010 level 3 (25% better than current regulations), 2. 2013 level 4 (44% better than current regulations and almost similar to Passive House) 3. 2016 level 5 (zero carbon for heating and lighting), 4. 2016 level 6 (zero carbon for all uses and appliances
Progress and development of the low energy buildings concept can be achieved with direct or indirect actions that raise awareness of these buildings and make them more attractive. Loans with a low interest rate for financing low energy buildings, lower taxes for low energy buildings or the introduction of CO2 taxes are some of the proposed measures that will help promote Low Energy Buildings.
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Furthermore, mandatory certification schemes are expected to promote low energy buildings by the introduction of grades restricted to buildings with very high energy performance. [74]
At the moment, there is a need for a national or regional definition of low energy buildings and its adoption by Countries’ regulations is very important (already the first steps were made through the Energy Performance of Buildings Directive 2010/31/EU) [75]. The development of a national strategy for the energy performance of a building needs revision and improvement. Through this progression, the markets transformation is a challenge for partners in the building sector and has just started the “learning curve” from being a concept of very low energy houses as a “grass-root” concept to becoming an official requirement in a very short time. [76]
Another serious challenge is the improvement of energy performance of existing buildings. It is crucial to reduce their energy consumption and energy demands as the available time is limited. As is already known, a building’s life time ranges from 50 to 100 years, so the real challenge is to transform these buildings which have a higher energy impact than the new buildings. A positive step is the fact that most of the EU countries are planning to revise their legislation within the next 4 years and several other countries are also trying to achieve new energy requirements in 2015. According to a report, highly energy efficient buildings could be achieved based on a long-term objective, which is an effective tool and guideline for the construction sector. [76][77]
Table 20: Low energy target by country. [76][77]
Country Low energy target Austria Planned: social housing subsidies only for passive buildings as of 2015 Denmark By 2020 all new buildings use 75 % less energy than currently enshrined in code for new buildings. Interim steps: 50 % less by 2015 , 25 % les by 2010 (base year=2006) Finland 30 – 40 % less by 2010; passive house standards by 2015 France By 2012 all new buildings are low energy buildings (Efficiency standard), by 2020 new buildings are energy-positive Germany By 2020 buildings should be operating without fossil fuel Hungary New buildings to be zero emission buildings by 2020, for large investments already in 2012 Ireland 60 % less by 2010, Net zero energy buildings by 2013 Netherlands 50 % reduction by 2015, 25 % reduction by 2010 both compared to current code plans to build energy-neutral by 2020 UK (England 44 % better in 2013 (equivalent to Passivhauslevel) and zero carbon as of 2016 and Wales) Sweden Total energy use / heated square metre in dwellings and non-residential buildings should decrease. The decrease should amount to 20 per cent until 2020 and 50 per cent until 2050, compared to the corresponding use of energy in 1995.
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The previous paragraphs referred to the problem of a common definition across the EU countries. Obviously the definition varies among the EU members but according to a 2008 research carried out across Europe, the low energy definition is known by different names. [77] According to the Concerted Actions supporting the EPBD, the research shows that most of the members use different descriptions for existing low energy buildings for example low energy house, high-performance house, passive house/Passivhaus, zero carbon house, zero energy house, energy savings house, energy positive house, 3-litre house, eco-building or green building and ultra-low energy house. [77]
However, another problem concerning the definition is what energy use is actually included in the definition. The definitions are divided. Some of them consider that all energy use must be considered during the estimation and calculations - for example energy use for heating, cooling, water heating, air conditioning and appliances - and some others support that during the calculations and estimations only the space heating and cooling must be take into account - ignoring electricity demand. [77]
Undoubtedly, all these attempts and definitions of low energy buildings have the same target, namely the improvement of the existing and future energy performance of buildings and the reduction of energy consumption. The focus is on the development of the standard alternative energy efficiency requirements in the building codes. Generally speaking, the ideal low energy building uses high levels of insulation, energy efficient windows, low levels of air infiltration and heat recovery ventilation to lower heating and cooling energy. In some cases low energy buildings use different energy efficient techniques-passive solar or active solar buildings- to improve their performance. [77]
5.4. Zero energy buildings definitions
The zero energy buildings definition presents a wide diversity through the publications and reports that have come out over the past few years and each time a different definition is given relating to the project goals and values of the design team. For example, the owners care about the energy costs, the organizations are interested in the primary and sources energy, the architectures care about a sites energy use for energy code requirements, and the
environmentalists care about the CO2 emissions and the environmental impacts of the buildings.
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However, it is important to focus on the actual word ‘zero’ and how this is defined within the
ZEB definition. This word may include CO2 emissions, primary energy, available energy or energy cost. The Torcellini report, which was published in 2006, makes use of the U.S. Department of Energy (DOE) definition which says that
“A net zero energy building (ZEB) is a residential or commercial building with greatly reduced energy needs through efficiency gains such that the balance of energy needs can be supplied with renewable technologies.” [78]
In the same report the authors refer to “zero” by saying
“Despite the excitement over the phrase “zero energy,” we lack a common definition, or even a common understanding, of what it means”. [78]
In addition, the Torcellini report attempted to cover all the different approaches by giving the most frequently used definitions:
• “Net Zero Site Energy”:A site where ZEB produces at least as much energy as it uses in a year, when accounted for at the site. [78]
• “Net Zero Source Energy”: A source where ZEB produces at least as much energy as it uses in a year, when accounted for at the source. Source energy refers to the primary energy used to generate and deliver the energy to the site. To calculate a building’s total source energy, the imported and exported energy is multiplied by the appropriate site-to-source conversion multipliers. [78]
• “Net Zero Energy Costs”: The cost of ZEB, is the amount of money the utility pays the building owner for the energy that the building exports to the grid which is at least equal to the amount the owner pays the utility for the energy services and energy used over the year. [78]
• “Net Zero Energy Emissions”: A net-zero emissions building produces at least as much emissions-free renewable energy as it uses from emissions-producing energy sources.[78]
It was only to be expected that the Torcellini report would create new discussions around the issue of the definition of ZEB. [79]In 2007 another author, Kilkis, referred to the Torcellini report but with a new approach at that time. The new definition for ZEB given by Kilkis was that
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“Net-Zero Energy Building is a building, which has a total annual sum of zero energy transfer across the building-district boundary in a district energy system, during all electric and any other transfer that is taking place in a certain period of time”. [79]
In another report, also in 2007, the authors in their definition paid attention to the balance of energy use and energy production of the building. According to them, the energy use should be equal to the energy production. [80][81]
Nevertheless, another interesting approach is facing the problem on the site of the buildings, which is energy demand and balance. Over the past few years, the greatest energy consumption in buildings has been from the space heating and hot water. Because of this, many publications attempted to describe the problems around the heating demands. Esbensen’s definition, in 1977 [82], is one example of this approach. Esbensen was Danish and it should be noted that his work was relevant to the Danish context. He stated that
“With energy conservation arrangements, such as high insulated constructions, heat- recovery equipments and a solar heating system, the Zero Energy House is dimensioned to be self-sufficient for space heating and hot-water supply during normal climatic conditions in Denmark. Energy supply for the electric installations in the house is taken from the municipal mains.”[82]
In many cases, the ZEB definition is focused on the electricity consumption of the building and its relation with the total energy. The definitions given by Gilijamse and Iqbal, respectively, represent this approach and state
“A zero energy house is defined here as a house in which no fossil fuels are consumed, and the annual electricity consumption equals annual electricity production. Unlike the autarkic situation, the electricity grid acts as a virtual buffer with annually balanced delivers and returns” [83][84] and
“Zero energy home is the term used for a home that optimally combines commercially available renewable energy technology with the state of the art energy efficiency construction techniques. In a zero energy home no fossil fuels are consumed and its annual electricity consumption equals annual electricity production. A zero energy home may or may not be grid connected.” [83][84]
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Another definition given by Lausten [85] attempts to include the total energy demand, heating and electricity demand. The result was the new definition of ZEB’s which said that
“Zero Net Energy Buildings are buildings that over a year are neutral, meaning that they deliver as much energy to the supply grids as they use from the grids. Seen in these terms they do not need any fossil fuel for heating, cooling, lighting or other energy uses although they sometimes draw energy from the grid.”[85]
More modern definitions taken into account embodied energy of the construction and the materials. This approach has been recently developed and there is a great living example close to London city, called the Bed ZED project [86]. Morbitzer states that
“theBedZED is built from natural, recycled or reclaimed materials. All the wood used has been approved to be sourced from sustainable resources, and construction materials were selected for their low embodied energy and were sourced within 35-mile radius of the site if possible.”[86]
During widespread discussions with reference to the definition of ZEB, another issue that was raised concerned electricity grids. This issue has to do with the off grid and on grid ZEB. The on grid Zero energy building is the one that is connected with the grid but also produces its own energy. These kinds of building can purchase energy or feed some back to the grid if they produce more energy than they require. On the other hand, off grid zero energy building are not connected with the grid and produce their own. These kinds of building mostly cover their energy needs from renewable energy sources. An example of the off grid ZEB is given in Lautsen’s definition:
“Zero Energy Stand Alone Buildings are buildings that do not require connection to the grid or as they have the capacity to store energy for night-time or wintertime use.”[87]
At the same time, Lautsen gave another definition for the on grid ZEB:
“Zero Net Energy Buildings are buildings that over a year are neutral, meaning that they deliver as much energy to the supply grids as they use from the grids. Seen in these terms they do not need any fossil fuel for heating, cooling, lighting or other energy uses although they sometimes draw energy from the grid”[87]
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Last but not least is the fact that some ZEB definitions focus on the renewable energy that is used to cover the needs of the buildings. It is important to remember that the main concept of ZEB is the replacement of fossil fuels with renewable sources which include solar energy, wind energy, wave energy, biomass energy and geothermal energy. Until now, the most familiar technologies are the solar thermal and photovoltaic technologies. An example of this type of definition is given by Charron:
“Homes that utilise solar thermal and solar photovoltaic (PV) technologies to generate as much energy as their yearly load are referred to as Net-Zero Energy Solar Homes (ZESH).” [88]
To conclude, from the above definitions it seems that zero energy building are affected by factors that influence the energy performance of the buildings. For that reason it is very difficult to adopt a general definition for zero energy building which can include all the different aspects. The best approach for a Zero Energy Building is to consider during the design phase all the parameters which are going to affect the energy performance of the building.
5.5. The definition impacts in ZEB design
As previously mentioned, each definition includes different aspects and the results can vary significantly. Table 21 summarises the differences, advantages and disadvantages of a Net Zero Site Building, Net Zero Source Energy Building, Net Zero Energy Cost Building and Net Zero Energy Emissions Building. [78]
Each zero energy definition has a goal which is important for engineers and designers to achieve. This goal is influenced by the building design but it is also affected by the zero energy definition. During the design stages, key issues such as energy efficiency, supply-side strategies, purchased energy sources, utility rate structures or whether fuel-switching and conversion accounting are possible, contribute to the ZEB goal. Table 1 describes the main and important characteristics of the different definitions. [78]
According to Torcellini’s report,
“a source ZEB definition can emphasize gas end uses over the electric counterparts to take advantage of fuel switching and source accounting to reach a source ZEB goal. Conversely, a ZEB site can emphasize electric heat pumps for heating end uses over the gas counterpart.
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For a cost worthy ZEB, demand management and on-site energy storage are important design considerations, combined with selecting a favourable utility rate structure with net metering. A ZEB emission is highly dependent on the utility electric generation sources. Off-site ZEBs can be reached just by purchasing off-site renewable energy—no demand or energy savings are needed. Consistent ZEB definitions are needed for those who research, fund, design, and evaluate ZEBs.” [78]
Table 21: ZEB Definitions Summary. [78]
Definition Advantages Issues Other Issues Site ZEB 1. Easy to implement. 1. Requires more PV export to 2. Verifiable through on-site offset natural gas. measurements. 2. Does not consider all utility costs 3. Conservative approach to (Can have a low load factor). achieving ZEB. 3. Not able to equate fuel types. 4. No externalities affect 4. Does not account for nonenergy performance, can track success differences between fuel types over time. (Supply availability, pollution). 5. Easy for the building community to understand and communicate. 6.Encouragesenergy efficient building designs Source 1. Able to equate energy value of 1. Does not account for non-energy Need to develop site-to-source fuel types used at the site. differences between fuel types conversion factors, which ZEB 2. Better model for impact on (supply availability, pollution). require significant amounts of national energy system. 2. Source calculations too broad information to define. 3.Easier ZEB to reach (do not account for regional or daily variations in electricity generation heat rates). 3. Source energy use accounting and fuel switching can have a larger impact than efficiency technologies. 4. Does not consider all energy costs (can have a low load factor).
Cost ZEB 1. Easy to implement and 1. May not reflect impact to 1. Offsetting monthly service measure. national grid for demand, as extra and infrastructure charges 2. Market forces result in a good PV generation can be more require going beyond ZEB. balance between fuel types. valuable for reducing demand with 2.Net metering is not well 3. Allows for demand-responsive on-site storage than exporting to the established, often with control. grid. capacity limits and buyback 4. Verifiable from utility bills. 2. Requires net-metering rates lower than retail rates agreements such that exported electricity can offset energy and non-energy charges. 3. Highly volatile energy rates make it difficult for tracking over time. Emissions 1. Better model for green power. Need appropriate emission 2. Accounts for non-energy factors ZEB differences between fuel types (pollution, greenhouse gases). 3. Easier ZEB to reach.
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5.5.1. Net zero site building
The Net Zero Site Building is the building that produces energy on a site and the production is equal to the consumption. Usually the energy production comes from renewable energy sources such as photovoltaic systems (roof or parking mounted PV), solar water collectors, wind power, low impact hydro and geothermal energy. [78]
The ZEB site’s definition does not take into account the values of different fuels at the source set up, and in this way it is a limitation. Furthermore, comparing the buildings that use natural gases from a ZEB source will need to generate less electricity, on site than the ZEB site. For instance, TTF building (The Thermal Test Facility, National Renewable Energy Laboratory, Golden, Colorado) which has gas heating as the major foundation, could be ZEB sourced with the use of 45-kWDC PV system but at the same time 62-kWDC PV systems are demanded to be on a ZEB site. [78]
In ZEB sources, it is difficult to calculate the energy and emissions because it is necessary to determine the “site to source factors”.[78] In contrast, on a ZEB site it is easier to calculate these factors through on site measurements. Obviously on a ZEB site there are fewer difficulties present which makes goals easier to achieve. According to Torcellini’s report, an easily measurable definition is vital, to precisely define the improvement in the direction of meeting a ZEB goal. [78]
Another important factor is the external fluctuations which affect the ZEB goal, but on a ZEB site, these fluctuations are lower compared with other sites. Due to this fact, the ZEB site can set the most repeatable and consistent definition. During the building’s life, fluctuations in energy costs and rate structures influence the accomplishment of the ZEB goal which is the net zero energy costs and lower energy consumption. An example according to Torcellini’s report is the BigHorn building (The BigHorn, Home Improvement Center, Silverthorne, Colorado) where natural gas prices wide-ranging 40% throughout the three-year observing period and electricity prices varied extensively, mostly because of a partial change from coal to natural gas for the electricity production.[78] However, during the life of a building the energy rate sources can present variations due to the types of power plants or power source mixes the utility uses to provide electricity. Undoubtedly, the achievement of the ZEB’s goal is strongly affected by the impact of the energy performance of the building for all the ZEB’s. [78]
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A building could be a ZEB site and yet not identify its comparable energy cost savings. If the peak demands and utility bills are not controlled, the energy costs may or may not be reduced. This was the case at Oberlin, as they recognised a 79% energy saving, but did not reduce peak demand charges. The uncontrolled demand charges resulted in a disproportionate energy cost saving of only 35%. [78]
Another design implication of a ZEB site is that within this definition, electrical equipment is more favourable and efficient than gas counterparts. For example, on a net ZEB site, electric heat pumps would be favoured over natural gas furnaces for heating because they have a coefficient performance of 2 to 4; natural gas furnaces are about 90% efficient. This was the case at Oberlin, which had a net ZEB site goal that influenced the design decision for an all- electric ground source heat pump system. [78]
5.5.2. Net zero source energy building
According to Torcellini’s report, a ZEB source produces as much energy as it uses when measured at the source.[78] As mentioned before, calculating the building’s total energy is difficult but not impossible. This calculation demands power generation and transmission factors and these factors are multiplied by the imported and exported energy.
Torcellini’s report also mentions that this meaning may possibly embolden the use of gases in as several end uses as probable (boilers, domestic hot water, dryers, desiccant dehumidifiers) to take benefit of this fuel swapping and source accounting to reach this ZEB goal. [78]
There may be some issues with a ZEB source definition as electricity is generated on site with gas from fossil fuels. The ZEB definitions agree that the buildings must use renewable energy sources to achieve the ZEB goal; therefore, electricity generated on site from fossil fuels cannot be exported and count toward a ZEB goal. However, this is unlikely, because buildings are unlikely to need more heat than electricity and the inefficiencies of an on-site electricity generation and exportation makes this economically very unattractive. The best cost or energy pathways will determine the optimal combination of energy efficiency, on-site cogeneration, and on-site renewable energy generation.
The issue of unmanaged energy costs on a ZEB site is similar to a ZEB source. A building can be a ZEB source and yet not realize the comparable energy cost savings. If peak demands and utility bills are not managed, the energy costs may or may not be similarly reduced.
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5.5.3. Net zero energy emissions building
Emissions-based ZEB’s produce at least as much emissions-free renewable energy as used from emissions-producing energy sources. If an all-electric building obtains all its electricity from an off-site zero emissions source (such as hydro, nuclear, or large scale wind farms), it then already has zero emissions and does not have to generate any on-site renewable energy to offset emissions. However, if the same building uses natural gas for heating, then it will need to generate and export enough emissions-free renewable energy to offset the emissions from the natural gas use. Purchasing emissions offsets from other sources would then be considered an off-site zero emissions building. [78]
Success in achieving emissions ZEB performance depends up on the generation source of the electricity used. Emissions vary greatly, depending on the source of electricity which ranges from nuclear, coal, hydro, and other utility generation sources. One could argue that any building that is constructed in an area with a large hydro or nuclear contribution to the regional electricity generation mix would have fewer emissions than a similar building in a region with a predominantly coal-fired generation mix. Therefore, emissions ZEB would need a smaller PV system in areas with a large hydro or nuclear contribution compared to a similar building supplied by a utility with a large coal-fired generation contribution. [78]
The net zero emissions ZEB definition has calculation difficulties that are similar to the ones previously discussed at the ZEB source definition. Many of these difficulties are related to the uncertainties in determining the generation source of electricity. Like the source definition, one would need to understand the utility dispatch strategies and generation sources ratio in order to determine the emissions from each of these sources. [78]
5.6. The project development though the ZEB definitions
When one considers the varying climatic, social economic and regulatory conditions across Europe, it is quite challenging to make an exact definition of the concept of zero energy building for the whole of Europe. Moreover, national standards and methodologies fluctuate and so “zero energy” idea in one country may refer to “low energy” in another country.
However, review of the literature reveals the lack of a common definition or common understanding of what low or zero energy building means. The choices that engineers make to achieve the goal are affected by the definition of the goal of zero energy. Moreover, in European countries there are different definitions and approaches that target different energy reduction goals.
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According to the background theoretical research, generally a zero energy building is a commercial or residential building where the energy needs have been reduced to the least possible and the remaining energy demand can be met with renewable technologies. What is at the heart of zero energy building is a low cost, locally accessible, non-polluting, renewable source that provides the energy for the building’s needs. Current research takes into account the broad approach and concept of zero energy building which is generally acceptable overall.
OUTCOME PROOF CHECK a successful ZEB principles guidelines INTERACTIONS simulation for ZEB Technology on reference Financing CHALLENGES buildings Implications for an Policy ZEB definition + STARTING PRINCIPLES POINT Energy demand Existing Renewables definitions, CO emissions standards and 2 roadmaps
Figure 20: Project development diagram The development and achievement of this project (Figure 20) is based on the existing definitions for zero energy building which are provided by different countries and organizations. The starting point of the research is the current definitions and standards, while the next step is to define the challenges and principles for the ZEB. Hence it is essential to check possible interactions and impacts of the technology, financing and policy on the development of ZEB. The next step is the proof check where the ZEB principles will be tested with a simulation program on reference buildings. The final outcome of the theoretical research and simulation procedure is the provision of guidelines for a successful Zero energy building. The correct design and development of zero energy building it is not only matter of definition but also depends on the precise regulations and standards of European Union.
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Chapter 6 Preparation of simulation weather data sets
6.1. Introduction
As previously mentioned, the theoretical research and the preliminary simulation procedure established the necessity for the weather data analysis
Large amounts of data are essential for carrying out building simulations. Much of this information, for example concerning building form and fabric, was easy to assemble. However, obtaining weather data consisting of statistically defensible assemblies of relevant information, (the so- called “Test Reference Years” or “EPW weather files”) was more problematic[77]. A Reference Year, also known as a Test Reference Year (TRY) is a single year of hourly data (8760 hours) that has been selected to represent the range of weather patterns which would typically be found in a multi-year dataset. Its intention is to allow a more faster simulation than multi-year datasets and to form an equitable basis for comparing the predicted buildings energy consumptions with different designs.[89] EPW weather files are files generated from TRY files in a format that can be used by different programs, for example the IES simulation program.[77]
In contrast to many other countries, there are no such data sets for Cyprus or, where they do exist, they are not up to date. The geomorphological specificities of Cyprus are such that there were valid concerns about the applicability of one standard set of weather data to the whole island. [78] The research highlighted the need for updated weather data sets and from different locations of Cyprus though a preliminary simulations on an exemplar building. The comparison between different locations justifies the need to specify more than one Test Reference Year for the island. Moreover, a thorough investigation of the weather data from different towns is essential for the development of strategies for the design and construction of zero energy buildings for Cyprus. However, another study producing results for TRY for Cyprus was published in 1998 and covered the years after 1992. The Typical Meteorological Year was generated using available hourly meteorological data recorded during the period 1986-1992, using the Filkenstein-Schafer statistical method. [79]
Another significant factor taken into consideration by the project was the relocation of most of the stations. The Cyprus Meteorological Service in Nicosia provided the project with the temperature data needed to carry out a detailed analysis.
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Cyprus has five meteorological stations but only three had time series for periods longer than 50 years. One of the stations that had been relocated three times since the beginning of data collection in 1933 was the Larnaca station (the one used by the IES simulation program). These relocations clearly showed shifts in the weather data trends. Therefore, the project used data periods and stations where the effects of relocation did not affect the reliability of the data. The Limassol station was relocated twice during the period May 1977 to October 1987. However there was an uninterrupted long period of 74 years before the first station move, although little change is noted in the temperature trends after the two station relocations. The Nicosia station had a continuous record of 114 years from 1896–2010 in the same location without any problems of relocation. In addition, the period (1997 to 2008) which was analysed in this project was unaffected by relocation. [80]
The IES weather data set provides satisfactory information for the simulation, but in the case of Cyprus the data was not up to date or was not representative for all locations. Moreover, the actual IES weather data covered only Larnaca Airport which was not representative of and accurate for the whole island. The significant differences between Larnaca and the other cities of Cyprus could not be ignored. The problem with the stations and accurate weather data concerns not only Cyprus but also many other locations. Thus, before continuing with the simulation procedure it was essential to understand the data base of the weather data used by each program.
As a result of the weather research and analysis there was a considerable amount of weather data from a number of sites in Cyprus, which was processed into a form suitable for use in building simulations.
6.1.1.Weather data effect on the preliminary simulations.
The IES building simulation program has been used in order to simulate the temperature variation observed within a six-storey building model in Cyprus. The building model, illustrated in Figure 21, has six floors with a total area of 2395.5 m2 and external walls 1521 m2. The wall (double-wall) consists of 0.10 m hollow brick, 0.03 m plaster on each side with an unventilated 0.05 m air gap in between. This combination gives a U value 1.13 W/m2K. The flat insulated roof consists of fair-faced 0.15 m heavy-weight concrete, 0.05 m polystyrene insulation, 0.03 m screed and 0.01 m asphalt covered with aluminium paint of 0.55 solar absorptivity. This combination gives a U value of 0.56 W/m2K. The total glazed area of the building is 648 m2 with 54 m2 of glazing for each flat.
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Figure 21: The IES building model, six floors high, in Cyprus The first comparison of the preliminary simulations illustrated the effect of the weather data and location upon building energy consumption and total carbon emission. The local weather conditions of each town ( Nicosia, Larnaca and Limassol), affected the energy consumption and total carbon emissions of the building during the summer and winter. This was due to the variations between the weather conditions in each town which are a consequence of the geomorphological features and meteorological conditions of each location. The work of C. Price, S. Michaelides , S. Pashiardis and P.Alpert [80] confirms the findings of the preliminary simulation work and underlines the need for different weather data sets for each location.
As observed in preliminary simulations, the widest percentage difference is between Nicosia and Limassol, and Limassol and Larnaca; This was to be expected as Nicosia is inland and Limassol is a coastal town. Moreover, the towns have considerable geomorphological and meteorological differences which affect the local microclimate conditions. According to the IES simulation program, the percentage difference between Nicosia and Limassol was 21.4% for the boiler energy, 14.39% for the chillers energy and 9.58% for the total carbon.
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Also the percentage difference between Larnaca and Limassol was high, being 20.54% for the boiler energy, 11.85% for the chillers energy and 9.58% for the total carbon. The percentage difference between Nicosia and Larnaca was 1.8% for the boiler energy, 5.28% for the chillers energy and 2.52% for the total carbon. Nevertheless, there was another issue with the Larnaca IES data and the up-dated Larnaca file. It was observed that the percentage difference between Larnaca IES and Larnaca was 23.08% for the boiler energy, 17.46% for the chillers energy and 5.36% for the total carbon.
Based on the above results, updating of weather data sets was seen as essential for the project. If this was not implemented, then the effects of the weather data sets would go unnoticed resulting in the reliability of computer simulation results being compromised. This was the main reason the project developed the research around the simulation weather data and then proceeded to a further analysis of the problem. Moreover, the analysis of the weather files helped in understanding the behaviour of thermal loads and energy demands of buildings in Cyprus and directed designers to apply measures to reduce energy demands.
According to the preliminary simulation findings, special attention should be paid to the weather file of the simulation program and the update of it in order to have accurate and representative results. It is necessary to point out the difficulty of reaching general conclusions from a small number of local stations. Nevertheless, given the rarity of such long time series in this region, it was important to have these results presented in the scientific literature.
6.2. Weather data sets for building simulation
The tasks identified in order to complete the assembly of the weather data were:
1. Collection and statistical analysis of Cyprus weather data from 3 different towns in order to provide comparison with the simulation files of the IES program. 2. Creation of up-to-date simulation weather files to use during the simulation procedure in order to ensure more accurate and reliable results. 3. The climate changes which lead to ever-increasing differences between the internal and external environment are related to increasing energy demands in the building sector.
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This analysis correlates the energy demand in buildings with weather changes and highlights the importance of the weather files in the simulation procedure. However, the weather data analysis and the programs and tools used for the construction of EPW weather simulation files were not the actual purpose of this research. The weather analysis was indispensable for the accuracy of the results of this project; however, the whole procedure was based on essential knowledge for weather simulation files.
The IES building simulation program was used in order to achieve the initial objectives. However, the building simulation needed weather data files in order to perform the different energy calculations and produce results. During the preliminary simulation procedure the simulation weather file in the database of the IES program was put under the microscope and immediately important questions arose:
1. At which meteorological station of Cyprus was the weather data gathered? 2. How long ago was the simulation file created? 3. Which period was covered by the existing weather data file?
The first action was to contact IES to obtain answers to these questions. However, it was both surprising and disappointing that the employees of IES were unaware of this issue and unable to answer the project questions.
Consequently, the next action was to define a methodology to answer the questions and cover the needs of the project. The steps of this methodology are described in the next subchapter.
6.3. Methodology for weather data analysis.
As a result of extensive research around the issue of weather simulation files, the methodology of the weather analysis was based on eight important steps. These steps are discussed in detail in subchapter 6.3.1.The first step was to explore the field of the simulation weather files; during this procedure it was important to understand how simulation weather file was constructed and how it interfaces with the simulation software.
As the second step the weather file data was extracted and converted to Microsoft Excel program format with the aim of extracting the data and information from the file and compare it with real meteorological data.
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The third step was to contact the Cyprus Meteorological Services; during this step the project was in touch with the authorities of Cyprus and collected hourly meteorological data from three different towns, Larnaca, Limassol and Nicosia.
The fourth step was to convert and analyse the hourly data whereby the project converted the hourly data into the same format with “EPW” data file and analysed the results. In order to convert the hourly data into EPW file the project used the Meteonorm program.
In the fifth step the results were compared and useful information extracted. Here the project compared the results of the analysis statistically and reached valuable conclusions about the Cyprus climate.
The sixth step was to construct new simulation weather files with the help of computer programs. The seventh step was to construct future weather files, in order to be able to predict the effects of climate change.
The final step was to organise the simulation weather files into the format recognised by the IES software.
The outcome of this process was the development of new simulation weather files that could be used to form the IES simulation program. Most important was the fact that these files were based on updated data and could thus give reliable results.
Figure 22 sets out the concept and methodology followed in order to create the weather simulation files with the help of different programs and tools.
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Figure 22: Procedure for the construction of simulation files
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6.3.1. Methodology step 1:Explore the field of the simulation weather files
It should be made clear that the weather analysis was not the primary target of this project. The need arose after the preliminary test and it was necessary to act on this problem. The following piece of research aims to provide only basic information for the simulation weather files, information that was essential in order to enable the project to construct the simulation files for Cyprus.
The first step was to clarify which data formats were supported by the IES simulation program. The two main formats supported by IES were the FWT and EPW files which included data from different sources worldwide. The weather data is sourced from a number of organizations such as the American Society of Heating, Refrigerating, and Air- Conditioning Engineers (ASHRAE), National Renewable Energy Laboratory (NREL), WATSUN Simulation Laboratory, and California Energy Commission (CEC). [81]
All these weather files provide satisfactory information for the simulation, but in many cases the data is not up-to-date or is not representative of the location. In the case of Cyprus, the weather data file (LarnacaWYEC.fwt) covers only Larnaca which is not representative of the whole island. The WYEC (Weather Year for Energy Calculations) refers to the method used to construct the simulation file. This type of file is based on ASHRAE methodology and data. [81] However, there were significant differences between Larnaca and the other Cypriot towns that cannot be ignored. It was essential to understand the database of the weather data used by each program before continuing with the simulation procedure.
The next step was to define the available weather data sources that could provide the necessary data. After extensive research the project concluded with the following sources:
1. The Cyprus Meteorological Services provided the project with 10 years’ hourly data for different parameters and different towns.[82 2. US Department of Energy provided the project with a constructed weather simulation file. The file was available for download online and was based on International Weather for Energy Calculations (IWEC). [82] 3. The Meteonorm software can produce EPW files for almost any location in the world.
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During extensive research into this issue found several possible methods for constructing a simulation weather file were found. However, as the issue was not a priority for this project, a quick, reliable and effective method needed to be found. One of the best options was Meteonorm commercial software whereby it was possible on the one hand to directly generate EPW weather simulation files, and on the other to input the collected data from Cyprus and generate the files. Furthermore, the program provided the opportunity for generation of future weather files based on current climate conditions. This method was chosen not only for the rapid results that could be produced but also for its reliability (this is discussed in more detail in subchapter 6.4) once it was suggested by the IES program and the US Department of Energy. [83]
In conclusion, meteorological data are generally measured and gathered by the meteorological authorities of the countries concerned. These data are referred at specific geographical locations and recorded at certain frequencies such as hourly, daily, monthly. In order to create typical or extreme values it is necessary to analyse from 10 to 30 years of records. There are several ways to create these data files or simulation files but this is not an issue of the current research. The project focused on the available data sources, the analysis and comparison of the data and the use of a program in order to create the final simulation weather files.
6.3.2. Methodology step 2:Extract the weather file data and convert it to the Microsoft Excel program format
The extraction of data from different weather simulation files was of significant importance for the analysis and comparison of weather data. In order to be able to compare the different data and reach useful conclusions, it was necessary to find a program that could open and read the various different formats of simulation weather files. Moreover, it was important to be able to extract the weather data and then input the data into the to Microsoft Excel program.
After researching the issue, the project concluded with the following programs:
1. CLIMATE CONSULTANT: a tool that can open and read EPW files and represent the input weather data graphically. This program is recommended on many scientific sites and can be used free. The detail analysis and how the program works is not part of this project.[84]
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2. CCWorldWeatherGen: this program allowed the project to open the epw files in Microsoft Excel environment and permitted the extraction of the weather data of the files. However, the purpose of the program is the generation of climate change weather files and the construction of ‘morphed’ EPW and TMY2 files as well as present-day TMY2 files from the original EPW format files. The detail analysis and how the program works is not part of this project and more information can be found online. [85]
These two programs were used by the project in order to evaluate the weather data and construct the final weather simulation files.
6.3.3. Methodology step 3:Contact with Cyprus Meteorological Services
During this step the project contacted the Meteorological Service of the Ministry of Agriculture, Natural Resources and Environment of Cyprus. This authority, which performs the measurements for the different weather conditions and is responsible for the meteorological stations for the whole Island, was the only source providing meteorological measurements for the different locations. The project selected two towns that were representative of the Cyprus climate: Limassol situated on the coast and Nicosia situated in the centre of the island. (Figure 23 )
Figure 23: The map of Cyprus and the three different towns, Limassol, Larnaca and Nicosia [82]
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These particular towns were selected after discussion with various staff members at the Cyprus meteorological office. The IES simulation program already included the Larnaca weather file so, on one hand, Limassol was chosen in order to compare the coastline weather data, and on the other hand, Nicosia would reveal the issue of microclimate conditions.
Another fact needing to be considered was the relocation of the stations. The Limassol station had a continuous record for a period of 74 years and the Nicosia station had a continuous record of 114 years from 1896–2010 in the same location. Moreover, neither of the stations in these two towns was relocated during the period (1997 to 2008) which was analysed in this project. [86]
After extensive research and discussion in Cyprus it was decided that a minimum of 10 years’ data for the three locations should be analysed in order to achieve accurate and reliable results. The aim was to collect data representative of the climate zone of Cyprus, which means that values of the main climate parameters would be as close as possible to long term mean values. Thus, the collected data included hourly measurements of solar irradiance, temperature, wind speed and direction, and humidity ratio, for an eleven-year period, from 1997 to 2008.
These hourly data covering a period of eleven years were given in row data and it was necessary to change these data into monthly mean values which could be handled and compared more easily than row hourly data. For this reason the data was input in the Microsoft Excel program and the final outcome was based on the statistical comparison of the three towns.
6.3.4. Methodology step 4: Convert the hourly data and analyse
Once the EPW files data and the row data were obtained from the Cyprus Meteorological Service, they needed to be analysed. Thus, it was impossible to handle and compare all these hourly data without any changes. As previously mentioned, the data was input in the Microsoft Excel program, statistically analysed and presented in graphs.
6.3.5. Methodology step 5: Compare the results and extract useful information
The statistical analysis of the weather files from the three different towns of Cyprus indicated that the weather conditions for each location are unique and differ significantly from one town to another. In the case of Cyprus the two towns of Limassol and Larnaca have the same
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6.3.6. Methodology step 6: Construct new simulation weather files
Once the comparison and analysis of the data was completed, the next important step was the construction of weather simulation files (EPW files). To achieve this, the project used the METEONORM tool which is a comprehensive meteorological reference and is based on 25 years’ experience in the development of meteorological databases for energy applications. [87][88] However, the row data from Cyprus was input into Meteonorm in order to construct the up-to-date weather simulation files. Furthermore, the program provided the opportunity to construct weather simulation files from weather stations and data that the program itself provided. The final outcome from this procedure was the construction of up-to-date files that can be used for building simulation.
6.3.7. Methodology step 7: Construct future weather files
After the construction of up-to-date weather simulation files (EPW files), the project used the CCWorldWeatherGen tool [89] in order to create future weather files. The climate change world weather file generator (CCWorldWeatherGen) is a tool that generates climate change weather files for world-wide locations in EPW format. [89][90] The program calculations are based on the Intergovernmental Panel on Climate Change (IPCC) Third Assessment Report model summary data of the HadCM3 A2 experiment. [89][90] The data for the scenarios can be downloaded free from IPCC Data Distribution Centre (IPCC DDC) [90] and was input in the CCWorldWeatherGen tool. The IPCC Data was selected on the ground that it is world recognised and trusted sources. The tool works in the Microsoft® Excel environment and converted the current EPW weather files into climate change EPW weather files. The program operation is based on ‘morphing’ methodology for climate change transformation of weather data. The methodology was developed by Belcher, Hacker and Powell. [91] The final outcome from this process was the generation of future weather files (EPW) for 2020, 2050 and 2050. These weather files provided the project with the opportunity to estimate future energy demands of the current building models and study the future operation of the buildings.
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6.3.8. Methodology step 8: Input the simulation weather files in IES
The final step was to input all the new weather simulation files into the IES simulation program and test them with exemplar building. The purpose of this step was to check that the constructed files are working and at the same time examine whether there were any differences between the results from the different weather files.
The theoretical research in combination with the preliminary results confirmed the need to construct up-to-date weather simulation files for Cyprus. Two important outcomes from the research and from the weather data analysis which follows need to be highlighted. The first is the fact that there are significant differences between the data of the IES and the new weather data that need to be taken into account for purposes of the building simulation. The second is the fact that there are climatic differences between the three towns of Cyprus and these differences impacted on the buildings energy performance.
As previously stated, it was essential to use different programs during the procedure for constructing the new files. The new files are based on data from meteorological office of Cyprus and the Meteonorm program. The most important step for the construction of EPW weather simulation files was the use of the Meteonorm program: during this step the collected data was input in the program and new EPW files were created. The Meteonorm is a comprehensive climatological database and can be used as meteorological reference. In addition it is possible to use the Meteonorm data that is collected from ground stations or satellite data, while there is also the option to import data manually.
6.4. The Meteonorm software
A combination of a climate database, a spatial interpolation tool and a stochastic weather generator Meteonorm [92] is a global climatological database. It is extensively used as meteorological input for simulations of solar applications and buildings and typical years with hourly or minute time resolution can be calculated for any location. The input of Meteonorm for global radiation is Global Energy Balance Archive [93.] whilst databases of WMO[93] and NCDC [93] provide other meteorological parameters for the timeframes 1961-90 and 1996-2005. The stochastic generation of global radiation is based on a Markov chain model for daily values and an autoregressive model for hourly and minute values. [94][95]
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Temperature generation depends on global radiation and measured distribution of daily temperature values of approximately 5000 sites generates. Additional parameters such as precipitation, wind speed or radiation parameters like diffuse and direct normal irradiance are also generated by Meteonorm. [94][95]
Hence, rather than using complicated and time consuming downscaling methods based on regional climate models Meteonorm may be utilised as a comparatively simple and straightforward method for increasing the spatial and temporal resolution.
Where the user provides his/her own data there are the two options of monthly data or hourly data. Monthly import data included global and diffuse radiation, temperature, humidity and the missing values were interpolated with long term means. Hourly import data included global and diffuse radiation, temperature, humidity, precipitation, and missing values are coded as -999. During the development of this project the use of both methods, manually imported and the use of Meteonorm data, were used in order to construct the EPW files.
The Meteonorm program was used as a tool in order to create the weather simulation files (EPW). Importantly, the Meteonorm program is recommended as a reliable tool by numerous users, Universities and from U.S. Department of Energy[83]. The analysis of how the program works and the models used by the program are not an issue for this project. More information can be found in the Meteonorm manual v.6. [87]
6.4.1. Meteonorm Software description - Detailed software overview
The Meteonorm program offers two options (Figure 24) concerning the data use; the first was the use of Meteonorm data and the second was the use of imported data. In addition, the user can choose a time period from three options; the first the period from 2000 to 2009, the second the period from 1961 to 1990 and the third for a future period. This project used the time period 2000 to 2009 which was closer to the collected data from Cyprus meteorological stations (1997-2008) and permitted a comparison of the different data sets.
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Figure 24: Data form of the Meteonorm software [92]
The software consists of two steps: the first step (Figure 25. ) comprises a search of nearby weather stations and the second step involves their long-term monthly means being interposed to the specific location. Radiation parameters in areas where there is a low density of ground-based data available can be improved by data obtained from satellite imagery.
Figure 25: Meteonorm program interpolation procedure [92]
The second step (Figure 26), for the majority of the output formats a stochastic weather generator runs a typical mean year of data in hourly resolution (8'760 values per parameter) on the included monthly data with some output formats necessitating a minute-by-minute time resolution.
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Figure 26: Meteonorm program results presentation [92] In order to use the Meteonorm program more details were needed to follow the specific steps:
1. Locations: Select the locations for which it is desired to run Meteonorm: during this step the location was defined using the Meteonorm map (Figure 27). For defined location the Meteonorm data base offers seven different site types: Interpolated cities, weather stations, weather stations without global radiation measurement (that means global radiation is interpolated for them), design reference years (DRYs), user-defined sites, sites with imported monthly values (User (month)) and sites with imported hourly values (User (hour)). [92] This research used the weather stations data base of Meteonorm program and the sites with imported hourly values (User (hour)).
Figure 27: Meteonorm weather stations location map [92]
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2. Data: Adjust data settings.
Time period for temperature / radiation
The time period can be selected for the radiation parameters (radiation), the temperature and all other parameters. Both groups have a choice of two climatological time periods and a future time period for a scenario of climate change [92]:
a) Temperature and all other parameters with the exception of radiation: 1961 – 1990 and 2000 – 2009 b) Radiation: 1981 – 1990, 1991 – 2010 c) Selecting Future activates the field IPCC Scenario for future time periods. There is a choice between different scenario types each of which influences the climate in a different way.
The periods most frequently used are 2000 – 2009 for temperature and the 1991 – 2010 for radiation. These periods may differ from the standard ones at some stations. When one opens the information window of a weather station, it is possible to see in the Locations part what data is available and what period it refers to. However, the radiation period cannot be selected for Cities or User defined sites and for those sites the radiation values are pre-interpolated. A database which includes global radiation measurements of all time periods is used for this added information. [92]
In addition, another important parameter for this step was the temperature model. The Meteonorm program offers three different temperature models. The first is the Standard (hour) which calculates hourly temperature values and produces hourly extremes, which correspond to mean extreme values. The second model, the 10 year extreme (hour), is related to hourly temperature values producing hourly extremes which correspond to 10 year hourly extreme values. The climatological mean stays the same while this option spreads the distribution of values. It is most suitable for simulations where extremes of warm or cold values need to be considered (for example building simulations). [92]The Clear sky temperature is the third model; it cannot be chosen by the user but is selected automatically when the clear sky radiation model is chosen.
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This project used the second model, the 10-year extreme (hour), for two reasons; the first reason was the fact that this model is more appropriate for building simulations as it takes extreme warm and cold days into account. The second was the time period that was covered by this model, 10 years data, and it was possible to compare it with the data from meteorological stations of Cyprus (real data).
3. Format: Set the output format.
What final data will be stored to a file and the output data format (Figure 28) is defined by the Format window. There are 36 pre-defined data formats possible. In addition to various data formats identified by Meteonorm or comprehensive data formats such as the Typical Meteorological Year (TMY), there are many data formats referenced for data exchange with software packages specifically for the purpose of building simulations or solar energy applications. In Table 22 the respective formats with their parameters and units are given. The data format is named/designated according to/based on the external software; for instance, for the software Energy Plus the data format is named epw. Developers of the corresponding software have cooperated in specifying and testing the data exchange formats for the external simulation software. Moreover, with the 'User defined' data format one can define one’s own output format. [92]
Figure 28: Meteonorm data output format [92]
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Table 22: Definition of output formats for Building simulation software. [92]
Table 22 shows the definition of output formats for Building simulation software. The Integrated Environmental Solutions (IES) Virtual Environment which was used by this project accepts the EnergyPlus (epw) format as a weather data file. [92]
4. Output: Calculate and store the results.
The output weather data file is stored according to the data format selected in the format window. If the user selects the hourly data, then the hourly files may include very different parameters depending on the selected output format. The hourly files consist of 8'760 lines with each line containing the values for one hour. [92]
The monthly files contain a table with the values and information about the settings used as well as information about the three nearest stations used for the interpolation procedure and uncertainty information for radiation and temperature.
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6.4.2. Meteonorm Software-Import of own data
The Meteonorm program offers the user the ability to import their own weather data, monthly or hourly data (Figure 29).
Figure 29: Meteonorm program input weather data format tool [92] The import tool was vital for the progress of the project. In order to use the import tool of the Meteonorm program, a new type of weather data, the so called typical month was needed. Each month of a typical year is a true month from one of the years in question. As the generation of this type of weather data is a lengthy and complicate procedure, the project needed the collaboration and contribution of the Meteorological Services of Cyprus which had experience in that area. The Meteorological services responded to the request and provided the project (after agreeing on the fee payment) with excel file included the typical months (typical year). This data was essential for construction of the new weather data files (EPW files) for the three towns.
As the Meteorological Services of Cyprus had previously collaborated with Cyprus University in the generation of a typical meteorological year, they had previous experience in this area. The Meteorological office analyzed the collected data 1997-2008 with measured hourly values of the relevant variables and with the use of Filkenstein–Schafer statistical method [96] they selected the typical real months. A typical month is considered from the indexed year for which the distance Finkelstein-Schäfer between CDFc and CDFc,i is the smallest. (CDFc is a cumulative distribution function where c is the distribution for long term and CDFc,i is an empirical distribution function for a month for each year considered separately where i is the year index).[91][92][96] A previous article,'' Generation of typical meteorological year (TMY-2) for Nicosia, Cyprus'', was published presenting the generation of the Typical Meteorological year for Nicosia based on the Meteorological Services of Cyprus data from 1986 to 1992. [96] The generation of the Typical Meteorological Year for the period 1986-1992 was based on the same method (the Filkenstein–Schafer statistical
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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Limassol 1998 2005 2002 1999 2003 1997 2007 1998 2008 2001 2004 2000 Larnaca 2006 2001 1998 2000 2005 1999 2001 2004 2002 2007 1997 2003 Nicosia 1999 1997 2000 2003 2004 2001 1998 2007 2005 2008 2006 2002
The Excel file in CSV (Character Separated Values) which was prepared by the Meteorological office of Cyprus included actual measured hourly values with the difference that the individual months came from different years and more specifically from the analyzed period 1997-2008. The Meteonorm program allows users to import their own monthly and hourly values with the use of an import tool. This tool was used by the project in order to import the excel file for each town with the typical months (regarded as a typical year) and to transform it into an EPW file. More specifically, the Meteonorm tool was used to transform the prepared data (typical months that can be called as typical year) of the Meteorological office of Cyprus into a readable format (EPW file) of IES building simulation program. The outcome of the procedure was the generation of new weather data files for the three towns in EPW format that can be used by the IES building simulation program (table 25).
The parameter abbreviations followed by 12 lines (one for each month) was needed to specify by one header line. In addition, the first column was reserved automatically by the program for the month. However, the meteorological parameter columns were optional and not in any particular order. In case of missing data-missing values, the empty space was replaced with - 999 value. The Meteonorm program filled the missing value with climatological mean. [92]
Figure 30 Parameters for monthly data import. The times tamp (Month) is mandatory, all other parameters are optional. [92]
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Additionally the Meteonorm program offers the import of hourly data which was feasible for every location. For this option the program included three different types of files which can be read. The first one is Italian weather station format which includes eleven header lines and the following parameters: Year, month, day, day of year, hour, global radiation, temperature, relative humidity, precipitation, pressure, wind direction, wind speed and long wave incoming radiation. All radiation parameters must be in W/m2, temperatures in °C, pressure in Pa and wind speed in m/s. The second format is the free format where the parameters are specified in Figure 31. Data missing values are permitted and were coded as -999. The Meteonorm program filled the missing values with a climatological mean. [92]
Figure 31: Parameters for data import. The times tamp (m, dy or dm, h) is mandatory, all other parameters are optional. [92] 6.4.3.Climatological Databases-Ground stations.
Meteonorm uses several databases combined to form a single all-inclusive database that would enable worldwide simulation of solar energy systems, buildings and environmental simulations. All the essential factors necessary for further processing (global radiation, temperature, wind, humidity and precipitation) are included in the database.
For worldwide applications, several different international databases are included. Global radiation data was taken from the GEBA Global Energy Balance Archive (WMO World Climate Program - Water) [97]. The data was quality controlled using six separate procedures (checking of physical probability, time series analysis and comparison of cloud data). Temperature, humidity, wind data, sunshine duration and days with rain were taken from WMO Climatological Normals 1961–1990 [92][97]. To replace missing data and ensure a homogeneous distribution of weather stations, other databases such as the data summary of international weather stations compiled by the National Climatic Data Center, USA (NCDC, 1995/2002) were added. [92][98][99]
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6.4.4. Meteonorm Climate change data
The Meteonorm program includes the average of all the 18 models of IPCC report 2007 and there are three scenarios available for the user; the B1 (low), the A1B (mid) and the A2 (high).[92][100] The program uses the anomalies of temperature, precipitation, global radiation of the periods 2011–2030, 2046–2065, 2080–2099 to calculate the future weather time periods. [92]
However, the temperature changes are comparatively larger than the forecast changes of global radiation until 2100 with all scenarios of IPCC, with range of one tenth of a percent up to some percent. Moreover, the three scenarios present relatively small differences between them with global radiation presenting on average a slight decrease. [92]
In the region of the Mediterranean, however, the trend is positive (+ 2-4 % until 2100). Over the last 25 years changes have been going in the same direction but are already exceeding the predicted anomalies for the period until 2030. Moreover, it should be noted that climate models in the past have greatly underestimated the variations over the past 50 years (global dimming and brightening). [92] It is important to bear in mind that predictions based on climate models always tend to be uncertain/unreliable since knowledge of the climate system is limited and depends on the computing resources available.
6.4.5. Principles of methods used by the weather analysis software
The calculations of heating and cooling loads in buildings are strongly related to solar radiation and temperature parameters. This project focused on the development of zero energy buildings in hot climate countries and hence accurate weather data was vital for the heating and cooling loads.
The temperature Meteonorm model consisted of three parts; the first is the stochastic generation of daily values where the calculations are based on monthly temperature, daily radiation values and measured temperature distributions; the second is the monthly minimum and maximum temperatures calculations which are based on daily temperature values and daily and monthly radiation values; the third is the generation of hourly values which are based on daily minimum and maximum temperature values and hourly radiation values. [92]
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The stochastic generation runs with an auto-regressive process where boundary settings almost do not exist. Then the distribution is mapped to the measured or interpolated distribution (according to the input), drawing on the statistical temperature data base resource. Equation 1 shows the execution of the auto-regressive process for daily temperatures where, dT is the mean day to day difference, dTsd is the standard deviation of the day to day difference, dy is the day number in the month and r is a normally distributed random variable with expected value 0 and standard deviation 1. [92]
Equation 1: The auto-regressive process for daily temperature [92]
where:
Equation 2 : The calculation of δΤ [92]
Equation 3: The calculation of random variable r
Equation 4: The calculation of dT'
Equation 5: The calculation of dT'sd
Accessing the temperature database obtain temperature data at the selected site by using the nearest site interpolation procedures provides the statistical data which is needed in order to
estimate dT' and dT'sd which are needed to carry out the auto-regressive operation described by equation (Equation 4-5). It is the stochastically generated time series of hourly global solar radiation which is produced first since it is the temperature driving agent in the process. The two difference values vary according to the calculated daily insolation. If it is more than 50% of the clear sky value, the value used is" mostly clear sky" and with the "mostly overcast" value being used if it is less than 50%. For both values, the current and previous day’s mean is used for a realistic daily difference. [92]This process is first run without any limitations on the minimum, maximum or mean values.
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A check is carried out after the generation of each month to ascertain whether the difference between the month's last daily value and the mean of the current and following month exceeds 4°C. If the mean exceeds 4°C, a correction term is used to keep the difference below 4°C. The monthly mean of December is regarded as the first value. [92]
Once the end of month corrections have been produced and applied, the daily values are mapped to the measured mean distribution, which is interposed between the seven stored quantiles. This results in mean distributions and not extreme distributions and thus a statistically normal year is generated. Moreover, in the northern hemisphere the annual one day minimum is chosen as the January minimum or in the southern hemisphere as the July minimum; the annual one day maximum is selected as the summer (July/January) maximum in order to include not only monthly extremes but mean one year extremes. [92]
In the northern hemisphere the 4 day minimum temperature is calculated for January or in the southern hemisphere for July so as to reproduce minimum design temperatures which are generally defined/identified based on a period of several days. [92]
When the resulting 4-day minimum exceeds the measured value by more than 0.25°C, the 4 days with the lowest minimum temperature are corrected to the measured value. When there is less than 1°C difference, other days are not altered. If the difference exceeds 1°C, the following or the preceding 4 days (depending upon the day of month) are increased so that the monthly mean will remain unchanged. [92]The input data is also used to calculate daily minimum and maximum temperatures with the monthly factor dX first being calculated using measured monthly input values [92]:
Equation 6: Equation of monthly factor dX
Equation 6 shows the monthly factor dX , where Tad,max and Tad,min as the monthly mean
daily minimum and maximum hourly temperatures and Gm the monthly mean global radiation. This gives the general factor for conversion from radiation to temperature. [92]
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Then to find the daily difference between the maximum and minimum temperature, the daily radiation value is calculated using Ghd. ([92]
Equation 7: Equation of daily difference between the maximum and minimum temperature[92]
By using this daily difference and on the basis that the mean value is the mean of the extreme daily values, it is possible to calculate the daily minimum and maximum temperatures. [92]
Equation 8: Equation of daily minimum temperatures[92]
Equation 9: Equation of daily maximum temperatures[92]
Regular checks confirm that the daily extremes are within the limits set by the monthly extreme hourly values and if the monthly extremes are not equal (with a permitted difference of up to 0.5°C), the calculated maximum and minimum values are based on the monthly extremes. [92]
6.4.6. Quality of interpolated data
After interpolation, the following cross correlation method is used to measure the accuracy of the results: Interpolation of global radiation: mean biased error (mbe): 0 W/m2 (0 %); root mean square error (rmse): 12 W/m2 (7.1%) (Table 23). For temperature interpolation, the mbe was 0.0 °C and the rmse 1.2 °C. Using the nearest neighbour interpolation method as a benchmark, the rmse for global radiation would be 14% and that for temperature 3.4 °C. [92]
Quality of the ground bases interpolation, where Gh is the Global radiation, horizontal, Ta is the air temperature (ambient temperature, 2 m above ground), Td is the Dew point temperature, FF is the Wind speed (FFE, FFN longitudinal and latitudinal part of the wind speed), RR is the Precipitation, Rd is the Days with Precipitation > 0.1 mm and Sd is the Effective sunshine duration. [92]
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Table 23: Quality of the ground bases interpolation [92]
6.4.7. Uncertainty of interpolation of ground measurements versus distance
Uncertainty concerning the ground measurements extends from 1% and 10% but the majority of stations in Europe are situated between 2% and 4%. Stations with the lowest uncertainty are Malin Head (Ireland), Innsbruck (Austria) and Lichinga (Mozambique) with 1% of uncertainty while the stations with highest uncertainty are Mocamedes (Angola, 7.1%), Pleven (Bulgaria, 7.6%) and Hirado (Japan, 10.1%). The uncertainties are dependent on both quality (technique, duration) and also on climatological causes. For ground interpolation the uncertainty is at 1% at a distance of 2 km and at 100 km the uncertainty is generally at 6% (Figure 32). The uncertainty is set constant at 8% for distances more than 2000 km. [92]
Figure 32: Uncertainty of interpolation of ground measurements vs distance [92]
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For satellite data the value of the uncertainty varies between 3% and 6% for Europe and Northern Africa (Meteosat high resolution area) and between 4% and 8% for all other satellites (Figure 33). [92]
Figure 33: Uncertainty of satellite data in dependence of latitude and source of satellite, where MSG=Meteosat Second Generation, hr = high resolution area (Europe). [92]
6.4.8. Meteonorm Accuracy
According to the Meteonorm manual [87], certain inconsistencies were unavoidable due to the comprehensive framework chosen for the present edition. However, it can still be established which data base and algorithms were used. Differences between the various data bases and algorithms may be summarized as follows:
1. Quality of basis data: The radiation data was subjected to extensive tests. The root mean square error in interpolating the monthly radiation values was 7%, and for temperature 1.2°C. [87]
2. Climatic variations: The METEONORM radiation data base is based on 20- year measurement periods and the other parameters are based data bases covering the periods of 1961-1990 and 2000-2009. Comparisons with longer term measurements indicate that the discrepancy in average total radiation between the two datasets is due to the choice of time period and is less than 2% for all weather stations. [87]
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3. Computational models: The models that are used in METEONORM are designed to calculate radiation on inclined surfaces and additional parameters. Depending on data basis one or more models are used. If the results will be passed on for further processing, the data basis and models used should be specified in order to ensure correct interpretation of the results. [87]
4. In general, the hourly model tends to slightly overestimate the total radiation on inclined surfaces by 0-3% (depending on model). Compared to measured values the discrepancy is ±10% for individual months and ±6% for yearly sums. [87]
Table 24: Summary of uncertainties in interpolation for principal data. [92]
Table 24 present a short synopsis of the uncertainties in the major data used in validating a variety of models and the combined model of the Meteonorm program.
Stochastic models are used to generate hourly and monthly values at any desired location. These models create intermediate data with the same statistical properties as the measured data, for instance the average value, variance, and characteristic sequence (autocorrelation). The data which is produced is as far as possible the same as the natural characteristics. Research has recently indicated that data which has been produced in this way can also be satisfactorily used in place of long-term measured data [101]
The weather data analysis and the use of Meteonorm program were vital for the project in order to ensure that the collected data and the new weather data files are reliable. The
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comparison of the collected data with the data available from Meteonorm minimizes the probability simulation errors and comes back with values that were closer to the reality and return more accurate results.
6.4.9. The results from the Meteonorm program
The outcome of the procedure was the generation of new weather simulation files (EPW) that were constructed from Meteonorm programs and are presented in Table 25 .
Table 25: The new weather simulation files for Larnaca, Limassol and Nicosia.
Location File name Period/Year Data Source
Larnaca Larnaca_hour_hay 1997-2008.epw 1997-2008 Cyprus Meteorological stations
Larnaca Larnaca_hour_hay 2000-2009.epw 2000-2009 Meteonorm data
Limassol Limasssol-AKROhour_hay1997-2008.epw 1997-2008 Cyprus Meteorological stations
Limassol Limassol AKRO_hour_hay_2000-2009.epw 2000-2009 Meteonorm data
Nicosia Nicosia_hour_hay _1997-2008.epw 1997-2008 Cyprus Meteorological stations
Nicosia Nicosia_hour_hay_2000- 2009.epw 2000-2009 Meteonorm data
The Table 25 shows the weather data files that are constructed from the data collected from Meteorological stations of Cyprus and the weather data files constructed at the Meteonorm program data base.
6.5. CCWorldWeatherGen program
The second step was the use of CCWorldWeatherGen. The creation of future weather files of the three towns (Limassol, Larnaca and Nicosia) for 2020, 2050 and 2080 was important. In fact the files were the future estimations of Cyprus weather data based on a use of IPCC TAR(Third Assessment Report of the IPCC) model summary data of the HadCM3 A2(Hadley Centre Coupled Model, version 3) experiment ensemble which is available from the IPCC DDC (Data Distribution Centre of the IPCC).[89][102][103].
The CCWorldWeatherGen is a powerful tool that generates climate change weather files which can be used directly for building simulation. The tool is Microsoft® Excel based and morphs the ‘current day’ weather simulation files (EPW) into future weather files taking different climate change scenarios into account.
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The methodology used by the tool to carry out the calculations is based on work published by CIBSE as well as on previous work by the authors of this tool. The morphing methodology for generating climate change weather data is based on the methods developed by Belcher, Hacker and Powell. [103][104][105]
6.5.1. CCWorldWeatherGen program principle of the methods
The CCWorldWeatherGen tool utilises coarse General Circulation Model (GCM) data (the General Circulation Model is analysed in detail below)[106]. The most sophisticated tools currently available for simulating the response of the global climate system to increasing greenhouse gas concentrations are numerical models (General Circulation Models or GCMs), signifying physical processes in the atmosphere, ocean, cryosphere and land surface. (Criterion 1: Consistency with global projections. They should be consistent with a broad range of global warming projections based on increased concentrations of greenhouse gases. This range is variously cited as 1.4°C to 5.8°C by 2100, or 1.5°C to 4.5°C for a doubling of atmospheric CO2 concentration (otherwise known as the "equilibrium climate sensitivity"))[106]. Although there are simpler models that have provided globally- or regionally-averaged estimates of the climate response, it is only GCMs, perhaps used in cooperation with nested regional models, which are capable of providing geographically and physically consistent estimates of regional climate change essential in impact analysis, thus fulfilling criterion 2 (Criterion 2: Physical plausibility. They need to be physically possible; for example, they should not violate the basic laws of physics. Thus, changes occurring in one region need to be physically consistent with changes in another region and globally. Furthermore, the combination of changes in different variables (which are often correlated with each other) should be physically consistent.) [106].
GCMs portray the climate by means of a three dimensional grid over the globe (Figure 34), characteristically with a horizontal resolution of from 250 to 600 km, 10 to 20 vertical layers in the atmosphere and occasionally as many as 30 layers in the oceans. Relative to the scale of exposure units in impact assessments, GCMs have quite coarse resolution, thus not fully satisfying criterion 3 (Criterion 3: Applicability in impact assessments. They should depict changes in a sufficient number of variables on a spatial and temporal scale that allows for impact assessment. For instance, impact models may require input data on variables such as precipitation, solar radiation, temperature, humidity and wind speed at spatial scales ranging from global to site and at temporal scales ranging from annual means to daily or hourly
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values). Furthermore, it is impossible to properly model numerous physical processes, for instance, those related to clouds, which arise on smaller scales.
As an alternative, their known properties must be averaged over the larger scale in a technique known as parameterization. This represents one source of uncertainty in GCM- based simulations of future climate while others concern the simulation of various feedback mechanisms in models concerning, for example, water vapour and warming, clouds and radiation, ocean circulation and ice and snow. Hence, GCMs may simulate quite different responses to the same forcing, just because of how some processes and feedbacks are modelled. [106].
Figure 34: GCMs depict the climate using a three dimensional grid over the globe. [106].
However, whereas these differences in response are unlikely to satisfy criterion 4 (Criterion 4: Representative, they usually correspond with the climate sensitivity range as described in criterion 1).They need to be representative of the potential range of future regional climate change.
Only in that way is it possible for a realistic range of possible impacts to be estimated concerning the uncertainty range of regional projections. Not even selecting all the available GCM experiments could guarantee a representative range, since there are other uncertainties such as the range in estimates of future atmospheric composition which are not completely addressed by GCMs. [106].
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6.5.2. CCWorldWeatherGen Calculation methods of the future weather files
1. Ground Temperature
Information on the monthly mean ground temperature at one or more levels of depth is usually given in the EPW file header. Based on the method developed by Kusuda and Achenbach [107], the mean ground temperature for a given day of the year is obtained from the predicted annual mean dry bulb temperature and the amplitude of the warmest and coldest average monthly dry bulb temperatures. The calculations given here are based on routines developed by Lawrie [108] for the EnergyPlus Weather Converter. Prior calculation of the future hourly dry bulb temperatures is necessary using the following equations. It is possible to calculate the future mean ground temperature for any given day of the year by:
Equation 10: Equation of future mean ground temperature for any given day of the year. [108]
where:
and
where:
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In order to produce the future weather files, depths of 0.5, 2 and 4 m below surface were chosen. As there was no site specific information for the thermal diffusivity of the ground, Lawrie [108] gave the default value of 0.055741824 m²/day (this the actual value stated by Lawrie) which was chosen for the calculations. The calculations of the monthly mean ground temperatures are carried out by executing the above equations for each day of the year.
2. Dew point temperature (°C)
Information on the wet bulb temperature is in the CIBSE TRY / DSY files whereas data on comparative humidity and dew point temperature are kept in EPW files. It is possible to obtain the required future partial pressure of water vapour straight from the calculated future relative humidity and the saturation pressure of water vapour at the future dry bulb temperature using a transposed version of equation below [89]:
Equation 11: Present day relative humidity (%)
where:
thus:
Equation 12: Future partial pressure of water vapour(kPa)
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Once the future partial pressure of water vapour has been calculated using the above equation, the equations below can be used to determine the future dew point temperature [89]:
Equation 13: Future dew point temperature
where:
For dew points below 0 °C the following equation is used [89]:
Equation 14: Future dew point temperature for dew points below 0 °C
3. Relative humidity (%) As EPW files contain relative humidity information, the equation below can be used directly with the HadCM3 predicted absolute change of the mean relative humidity for the given month [89]:
Equation 15: Future relative humidity(%)
where:
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4. Global horizontal radiation (Wh/m²) Future radiation is calculated by using the monthly totals of the underlying EPW file for the data ‘morphing’[89].
5. Precipitable water (mm)
Whereas there is no information on rainfall in CIBSE TRY / DSY files, this information is given in some EPW files, depending upon the data source. As a change to the baseline climate, precipitation is given in the HadCM3 data. Hence, a stretch function is utilised in order to produce future precipitation data as suggested by Belcher et al [89][109]. The scaling factor for this function is calculated as follows[89][109]:
Equation 16: Scaling factor for monthly precipitation change
where:
The future precipitation for a given hour is then calculated in a stretch function[89][109]:
Equation 17: Future precipitable water(mm)
where:
Details on the underlying methodology used in CCWorldWeatherGen can be found in the publication of Jentsch M.F et al. [110] and Technical Reference Manual CCWeatherGen & CCWorldWeatherGen. [89]
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It should be mentioned that any use of a tool or program was preceded by painstaking research and study in order to understand the methodology and the way in which the programs use the data. The analysis of the methods are not part of the current project but further analysis of the equations and methodology used by the CCWorldWeatherGen can be found in technical reference manual of the tool.[111] The final outcome from the CCWorldWeatherGen tool was the new future weather files for 2020, 2050 and 2080 for the three towns (Table 26).
Table 25: The future weather simulation files for Larnaca, Limassol and Nicosia
Location File name Period/Year Data Source Larnaca Larnaca__HadCM3-A2-2020.epw 2020 CCWorldWeatherGen Larnaca Larnaca__HadCM3-A2-2050.epw 2050 CCWorldWeatherGen Larnaca Larnaca__HadCM3-A2-2080.epw 2080 CCWorldWeatherGen Limassol Limassol_HadCM3-A2-2020.epw 2020 CCWorldWeatherGen Limassol Limassol_HadCM3-A2-2050.epw 2050 CCWorldWeatherGen Limassol Limassol_HadCM3-A2-2080.epw 2080 CCWorldWeatherGen Nicosia Nicosia_HadCM3-A2-2020.epw 2020 CCWorldWeatherGen Nicosia Nicosia_HadCM3-A2- 2050.epw 2050 CCWorldWeatherGen Nicosia Nicosia_HadCM3-A2- 2080.epw 2080 CCWorldWeatherGen
6.5.3. Reliability of the models used to make projections of future Climate Change
The use of different tools and models raised a question on the reliability of the models used to make predictions of future climate change. The answer is that there will always be uncertainties concerning the prediction of climate change, mostly due to the fact that nature is inherently complicated and unpredictable. However, the technology and research minimized the uncertainties and succeeded in effectively predicting future weather changes based on past observations and data.
The climate change models could be characterised as mathematical representations of the climate system. These mathematical representations are expressed as computer codes and through the use of computer systems they are able to produce future weather data. The fact that the models’ core is based on established physical laws, such as conservation of mass, energy and momentum, together with a wealth of observations, creates confidence in the model.
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Models generally have the ability to represent important climate features such as the temperature, precipitation, radiation and wind. However, the uncertainties are higher for some climate variables than for others such as the temperature and the wind. [112]
Nonetheless, even with latest technological improvements and knowledge updates, the climate change models still present significant errors. These errors are generally larger in smaller scale analysis due to the fact that many significant small-scale processes cannot be represented precisely in models and so must be included in approximation as they interact with larger-scale features. One of the main reasons for this problem is the limitation in computer power, limitations in scientific understanding and limitations in the availability of detailed observations of some physical processes. It needs to be mentioned that regardless of the uncertainties most of the climate models are unanimous in their predictions of significant climate warming. [112]
Generally, the climate change models proved to be vital tools for simulating and understanding climate and there is every reason to believe that they are able to provide credible quantitative estimates of future climate change, particularly on larger scales. In addition, their results are extremely helpful for building simulation and prediction of the energy demand and performance of the building. However, the models still have significant limitations, such as in their predictions about wind speed and direction, which lead to uncertainties in the magnitude and timing, as well as regional details, of predicted climate change. Nonetheless, over several decades of model development, they have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases.
This project constructed up-to-date weather simulation files which are based on real measurement data from meteorological stations of Cyprus. However, the future predictions of the Cyprus climate are based on climate change models, but this future weather data did not affect the project’s primary target which was the development of zero energy building for hot climate countries. In depth analysis of the climate and climate change models were not part of this research. In order to present reliable data sets for the project development, the research studied and analyzed carefully all the relevant parameters wherever needed.
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6.6. Climate Consultant program
After the construction of the future weather simulation files (EPW) the project used the Climate Consultant (version 5) in order to present the new files graphically. The use of the Climate Consultant program enabled the direct presentation of the new data by graphic representations. In addition it was possible to actually see the unique patterns and subtle details that would otherwise be lost in tables of figures.
The future weather files were input in the Climate Consultant tool in EPW format. Then the tool organized and represented the input data in such a way as to make it easy for the reader to understand. Thus, the tool was very helpful in enabling all this row data to be presented in a comprehensible way.
Climate Consultant is based on theoretical work by B. Givoni and M. Milne, and is intended to support the book Climatic Building Design by D. Watson and K. Labs. [113][114]
It should be noted that the Climate Consultant tool includes four different comfort models. Thermal comfort is used in building simulation and can be primarily defined by dry bulb temperature and humidity levels, but alternative definitions can also be found in other sources. The choice of comfort level does not affect the data presentation through the program, but it modifies only the way comfort is shown on some graphs.
It is important to stress that the Climate Consultant tool was used as a data presentation tool and did not affect or change any of the weather simulation files. As previously mentioned, the fundamental understanding of each tool was essential for this project but it was not part of this research to further explore the different models used by the tools.
Finally, the new weather simulation files enabled the project to make accurate energy estimations based on up-to-date data. Moreover, the construction of future weather simulation files provided the opportunity to estimate the energy performance of the building under the climate change scenarios. This was very helpful as it provides the opportunity to make possible changes in order to prepare the building for potential future weather changes.
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6.6.1. Results presentation with Climate Consultant
The graphs in Appendix C present the weather simulation files with the future predictions for 2020, 2050 and 2080. The graphs present the temperature range, the monthly diurnal averages for temperature and radiation, the radiation range (hourly averages), the dry bulb temperature in combination with Humidity levels, the wind speed and the psychometric chart. The results of future weather predictions for 2020, 2050 and 2080 are presented for three Cyprus towns: Limassol, Larnaca and Nicosia.
6.7. Weather data and results
As previously stated, the weather data analysis, the programs and tools for the construction of EPW weather simulation files were not the primary target of this project. However, the analysis was essential for the development and results of the project.
Due to the huge amount of data collected from different sources, the following subchapters will present only the most relevant data and comparisons that affected the project development.
6.7.1. Weather data and results -IES program weather data (included)
The IES program simulation included the LarnacaWYEC.fwt file (Weather Year for Energy Calculations) which covers only Larnaca. The data of the file is based on ASHRAE sources and methods and is similar to CYP_Larnaca.176090_IWEC file (International Weather for Energy Calculations). More about the International Weather for Energy Calculations can be found on the US Department of Energy webpage. [115]
The following information was taken from the CYP_Larnaca.176090_IWEC [115] and showed clearly the simulation data based on 30 years data for the period 1969 to 1999.
The graphic presentation of the results is given in Appendix D.
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1. Average (arithmetic mean) hourly statistics for dry bulb temperatures °C
Table 26: The Larnaca IES weather data average (arithmetic mean) hourly statistics for dry bulb temperatures °C, during the period 1969-1999.
Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0:01- 1:00 9.8 8.8 10.7 13.9 18.2 21.6 24.2 25 22.6 18.4 14.8 10.9 1:01- 2:00 9.6 8.4 10.4 13.3 17.7 21 24 24.5 21.9 18.1 14.4 10.8 2:01- 3:00 9.5 8.1 10.2 13 17.6 20.6 23.6 24.1 21.3 17.8 14.3 10.7 3:01- 4:00 9.3 8.1 10 12.5 17.4 20.2 23.3 23.7 21 17.6 14.1 10.5 4:01- 5:00 9.2 8.1 9.8 12.3 17.2 19.8 22.9 23.3 20.6 17.3 13.9 10.3 5:01- 6:00 9.3 8.1 10.5 13 18.7 21.5 24.5 24.5 21.8 18.6 13.7 10.6 6:01- 7:00 9.5 8.2 11.2 14.9 20.3 23.4 26.4 26.2 23.2 20 14 10.8 7:01- 8:00 9.6 9.5 12 18 21.9 25.3 28.3 28.1 25.5 21.3 15.4 11 8:01- 9:00 11.4 12.2 13.4 19.6 22.6 26 29.1 29 26.9 22.7 18.2 13.1 9:01-10:00 13.1 14 14.7 20.6 23.3 26.8 29.8 30 27.9 24.2 19.8 15.1 10:01-11:00 15.1 15.2 16.1 21.5 24 27.5 30.5 30.8 28.8 25.7 20.9 17.1 11:01-12:00 15.1 15.7 16.2 21.6 24.1 27.7 30.8 31 29.1 25.7 21 17.3 12:01-13:00 15.2 15.8 16.3 21.5 24.4 27.9 31.1 31.7 29.3 25.7 21.2 17.5 13:01-14:00 15.5 15.8 16.4 21.5 24.6 28.1 31.2 32.1 29.6 25.8 21.4 18 14:01-15:00 15 15.7 16 20.9 24.1 27.9 30.7 31.6 29.2 25.2 20.8 17.2 15:01-16:00 14.4 15.4 15.6 20.8 23.7 27.7 30.3 31 28.7 24.6 20.2 16.5 16:01-17:00 13.9 14.7 15.3 20.2 23.2 27.5 29.9 30.4 28.2 23.9 19.3 15.8 17:01-18:00 13 13.7 14.4 19.4 22.5 26.6 28.8 29.5 27.1 22.9 18.6 14.8 18:01-19:00 12.1 13 13.5 18.2 21.8 25.7 27.7 28.5 26.2 21.8 17.7 13.7 19:01-20:00 11.2 11.6 12.6 17.2 21 24.7 26.6 27.6 25.4 20.7 17 12.7 20:01-21:00 10.9 11 12 16.4 20.4 24.1 26.1 27 24.8 20.2 16.1 12.2 21:01-22:00 10.5 10.3 11.6 15.6 19.8 23.5 25.4 26.4 24.1 19.6 15.7 11.7 22:01-23:00 10.2 9.7 11.3 14.9 19.2 23 24.9 25.9 23.5 19 15.4 11.2 23:01-24:00 10 9.1 11 14.4 18.7 22.4 24.5 25.5 23 18.6 14.9 11.1 Monthly Mean Dry Bulb temperature 11.8 11.7 13.0 17.3 21.1 24.6 27.3 27.8 25.4 21.5 17.2 13.4
The monthly statistics for dry bulb temperatures °C (Table 28) shows that the maximum dry bulb temperature of 36.5°C occurred in August at one o'clock and the minimum dry bulb temperature of 1.0°C occurred in February at four o'clock.
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Table 27: Monthly statistics for dry bulb temperatures °C
Monthly Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Maximum 19.2 19.7 19.2 30.5 29.4 34.8 34.7 36.5 32.2 29.2 26.3 22.4 Day:Hour 31:14:00 20:14 29:14:00 25:11:00 8:14 27:17:00 28:14:00 13:11 12:14 16:14 5:14 8:14
Minimum 3.7 1 3.3 6.2 11.2 15.8 20.4 19.4 17.6 13.8 9 3.1 Day:Hour 18:08 4:06 5:05 3:02 2:02 5:05 13:05 31:05:00 25:05:00 19:05 19:06 20:05
2. Monthly Statistics for relative humidity %
Table 28: Monthly statistics for relative humidity %
Monthly Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Maximum 96 94 100 94 100 98 100 94 91 89 94 96 Day:Hour 9:05 2:23 25:21:00 8:06 19:04 2:02 6:01 6:02 4:23 24:05:00 8:07 22:01
Minimum 39 19 41 17 19 21 21 23 19 28 35 24 Day:Hour 17:14 8:14 4:14 25:10:00 10:20 27:17:00 29:04:00 15:14 20:14 17:11 3:14 1:14
Daily Average 77 70 75 60 71 67 66 66 64 64 70 72
Table 29 shows Larnaca IES weather data monthly statistics for relative humidity % during the period 1969-1999. The daily average (arithmetic mean) generally shows that relative humidity % in Cyprus is high and this affects the climate and comfort levels.
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3. Monthly statistics for wind speed m/s
Table 29: Larnaca monthly statistics for wind speed m/s during the period 1969-1999.
Monthly Statistics Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Maximum 9.3 12.9 11.3 12.4 14.9 10.3 11.8 10.3 13.4 11.3 10.3 13.4 Day:Hour 11:20 22:15 3:20 1:15 1:14 18:14 1:14 4:14 29:17:00 1:17 14:15 21:14
Minimum 0 0 0 0 0 0 0 0 0 0 0 0 Day:Hour 8:17 1:10 1:05 1:02 1:02 1:02 1:05 1:02 1:05 3:20 1:19 1:20
Daily Average 3.2 3.8 3.9 3.6 4.4 3.6 4 3.6 3.2 3.2 3.2 3.8
Larnaca monthly Statistics for wind speed m/s during the period 1969-1999 shows that the highest value of wind speed (14.9 m/s) occurred in May. Generally the daily average (arithmetic mean) wind profile (Table 30) is presented on the analysed weather data without wide fluctuations during the period.
4. Monthly heating/cooling degree days/hours
Table 30: Larnaca IES weather data monthly heating/cooling degree days/hours during the period 1969-1999.
Monthly Heating/Cooling Degree Days/Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec HDD base 10°C ( Heating Degree Days) 8 11 1 0 0 0 0 0 0 0 0 2 HDD base 18°C ( Heating Degree Days) 193 177 156 47 1 0 0 0 0 0 41 144
CDD base 10°C ( Cooling Degree Days) 63 58 93 219 344 438 536 552 462 356 216 106 CDD base 18°C ( Cooling Degree Days) 0 0 0 26 97 198 288 304 222 108 17 0
CDH base 20°C (Cooling Degree Hours) 0 0 0 553 1449 3417 5415 5798 3914 1703 387 27 CDH base 23°C (Cooling Degree Hours) 0 0 0 181 380 1682 3250 3601 2066 619 79 0 CDH base 27°C (Cooling Degree Hours) 0 0 0 21 15 333 1159 1318 478 31 0 0
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Table 31 shows the Larnaca IES weather data monthly heating/cooling degree days/hours during the period 1969-1999.The 10°C baseline shows that there were 106 annual cooling degree-days and 2 annual heating degree-days. The 18°C baseline shows that there were 0 annual cooling degree-days and 144 annual heating degree-days.
5. Average (arithmetic mean) hourly statistics for direct normal solar radiation Wh/m²
Table 31: Larnaca IES weather data for average hourly statistics for direct normal solar radiation Wh/m²
Hours Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0:01- 1:00 0 0 0 0 0 0 0 0 0 0 0 0 1:01- 2:00 0 0 0 0 0 0 0 0 0 0 0 0 2:01- 3:00 0 0 0 0 0 0 0 0 0 0 0 0 3:01- 4:00 0 0 0 0 0 0 0 0 0 0 0 0 4:01- 5:00 0 0 0 0 0 0 0 0 0 0 0 0 5:01- 6:00 0 0 0 0 24 52 21 0 0 0 0 0 6:01- 7:00 0 0 37 144 219 275 256 203 155 58 4 0 7:01- 8:00 74 149 213 328 410 515 514 460 428 315 214 103 8:01- 9:00 265 319 371 461 536 661 674 653 640 525 436 288 9:01-10:00 373 412 468 539 604 747 765 765 766 635 520 410 10:01-11:00 400 439 508 564 641 803 809 827 831 662 521 445 11:01-12:00 437 448 484 570 650 792 812 847 844 665 530 480 12:01-13:00 444 432 427 544 611 775 806 841 832 633 511 475 13:01-14:00 412 396 357 508 563 711 774 809 781 577 458 418 14:01-15:00 375 380 347 473 519 709 734 752 715 503 385 353 15:01-16:00 277 320 291 379 437 643 645 658 561 334 222 201 16:01-17:00 49 140 179 214 279 473 455 432 283 59 1 0 17:01-18:00 0 0 6 44 91 195 193 124 8 0 0 0 18:01-19:00 0 0 0 0 0 0 0 0 0 0 0 0 19:01-20:00 0 0 0 0 0 0 0 0 0 0 0 0 20:01-21:00 0 0 0 0 0 0 0 0 0 0 0 0 21:01-22:00 0 0 0 0 0 0 0 0 0 0 0 0 22:01-23:00 0 0 0 0 0 0 0 0 0 0 0 0 23:01-24:00 0 0 0 0 0 0 0 0 0 0 0 0 Mean Hourly Statistics for Direct Normal Solar Radiation Wh/m² 129.4 143.1 153.7 198.7 232.7 306.3 310.8 307.1 285.2 206.9 158.4 132.2
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6.7.2. Weather data and results-IES weather data (LarnacaWYEC.fwt)
Weather data extracted from the weather year for energy calculations (LarnacaWYEC.fwt), which is a weather simulation file based on data from 1985 to 1995, included useful information for the project. The data format included repetitive months in order to construct the 10-year weather simulation file. The file included data for dry bulb temperature, relative humidity, wind direction and wind speed.
The extracted data was compared with the Cyprus weather data collected by the Cyprus Meteorological Services for the period 1997-2008. The graphic presentation of the results is presented in Appendix E.
6.7.3. IES weather data: results and comments
The statistical analysis and comparison of weather data from the 3 sources, Weather Year for Energy Calculations (LarnacaWYEC.fwt), International Weather for Energy Calculations (CYP_Larnaca.176090_IWEC) and Cyprus Meteorological Services, indicated that there were significant differences between the weather simulation files.
The comparison Appendix E of average (arithmetic mean) hourly statistics for dry bulb temperatures (°C) between the International Weather for Energy Calculations and Cyprus Meteorological Services data showed that there were significant differences, especially for the early morning data and late night data. Generally there was not such a great difference between the summer data files but it was significant that there was a tendency towards warmer winters. The new data showed that winter time in Cyprus is becoming warmer in comparison with the old data files (17 to 26 years ago). However, Figure 40 indicates that there are significant percentage differences between the two files which cannot be ignored. The smallest percentage difference was 0.29% and the largest was 19.36% according to the graph (Figure 35).
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20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 Percentage Percentage difference % 4 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Temperature Average Percentage difference %
Figure 35: Comparison of percentage difference % for the average hourly statistics for dry bulb temperatures °C.
The comparison of Average (arithmetic mean) hourly statistics for relative humidity (%) (Appendix E) between the CYP_Larnaca.176090_IWEC and Cyprus Meteorological Services data showed that in the past there were greater fluctuations in the Humidity levels during the day. The new data showed that there were relative humidity fluctuations during the day but they were not as great as those presented in the old data. In addition, there is a tendency towards rising relative humidity levels as humidity levels were higher in most cases after 1986. The humidity profile from new data can be characterized as more stable during the day and the differences between the hourly values were smaller than shown in the old data. Figure 36 shows the comparison between the percentage differences of the hourly relative humidity values, where the smallest percentage difference was 6.91% and the largest was 14.53%. Another important result (Figure 36) is the fact that there are high values of percentage difference of relative humidity for the whole day. These differences between the two files are compelling evidence of climate change in Cyprus.
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15 14 13 12 11 10 9 8 7 6 5 4
Percentage difference % 3 2 1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour RH Average Percentage difference %
Figure 36: Comparison of percentage difference % for the average hourly statistics for relative humidity
The comparison of the average hourly statistics for relative humidity (%) (Appendix E) showed that there were vital differences between the CYP_Larnaca.176090_IWEC and Cyprus Meteorological Services data. Except for some cases, the general picture from the graphs indicated that the wind speed from the new weather data had lower values than the older file. In general the records showed a trend of reducing wind speed between 1985 and 1991. After 1991 the wind speed seemed to increase again. However, there are important changes to the general profile of the wind speed, even during the day. The highest percentage difference for the wind speed is 45.3% and the lowest is 21.5%. However, the largest percentage difference values are presented between 1 o’clock and 11 o’clock in the morning. The wind speed is of vital importance as it has a strong impact on microclimate conditions and for that reason the simulation data has to be as close to real values as possible.
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50
45
40
35
30
25
20
15
10 Percentage difference % 5
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour Wind speed Average Percentage difference %
Figure 37: Comparison of percentage difference % for the average hourly statistics for wind speed m/s.
Generally the statistical analysis and comparison of the files (Appendix E) was a fundamental step for this research as it revealed the serious issue of the weather simulation data. The fact that comparison of the data sets offered proof of crucial changes in the Cyprus weather conditions cannot be overlooked in this project. In addition, the analysis showed that it was necessary to update the weather simulation files in order to attain accurate and reliable building simulation results.
6.7.4. Cyprus Meteorological Office weather data analysis
The hourly weather data used in this analysis were obtained from the Cyprus Meteorological Service and covered an 11-year period (1997-2008). The Limassol, Nicosia and Larnaca weather stations are the three with time periods more than 50 years. However, it should be mentioned that the Larnaca station has been relocated three times since 1933 when the data collection first started. This was a further compelling reason justifying the need for weather analysis and construction of new weather simulation files, since the IES weather data comes solely from the Larnaca station. Accordingly, the project focused on the two main stations of Limassol and Nicosia in order to carry out this analysis and extract useful results.
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1. Limassol station (34o40’ N, 33o 03’ E, elevation 5m): this station is a coastal station on the southern coast of Cyprus. The station has records from 1903 until today and it was relocated twice during the period from 1977 to 1987; prior to that the station was about 500m far from the coast. However, the data analysis that follows focuses on recent data for the period 1997 to 2008 during which period there were no relocations at all. Moreover, the new station where the data was collected is nearer to the coast.
2. Nicosia station (35o10’N, 33o 21’E, elevation 160m): this station is located inland in the centre of the town and situated on a small hill with an elevation of about 160m. The station records cover the period from 1896 until today and are continuous records without relocation.
The analysis and graphic presentation of the results are presented in Appendix F.
6.7.5. Cyprus Meteorological Office weather data: Results and comments
The results from the research and comparison of the two weather stations showed that there are differences due to the locations and the microclimate effects. The microclimate of Limassol is affected by the sea breeze which results in cooler summers and warmer winters for the coastal areas (e-Appendix 4 Figure 230). According to the results, the seasonal difference between mid-summer and mid-winter temperatures is approximately 19oC for Nicosia and 13oC for Limassol. During the winter the mean daily temperature reaches 10oC inland and 12oC on the coast while during summer the mean daily temperatures are 29oC inland and 27oC on the coast. The most significant factor to come to light during the analysis was the relatively large seasonal differences between daytime and night-time, particularly in inland areas during the summer. More specifically, during the summer the differences are 10oC on the coast and 16oC inland, while in winter the differences fall to 8oC on the coast and 10oC inland.
In general, during the summer Cyprus is under the effect of a shallow trough of low pressure spreading from the great continental depression centred over Southwest Asia. The summer can be characterised as a season with very high temperatures and cloudless skies. During the winter Cyprus is near the track of fairly frequent small depressions which cross the Mediterranean Sea from west to east between the continental anticyclone of Eurasia and the
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generally low pressure belt of North Africa. Due to the depressions there are usually daily weather changes which cause the annual precipitation. However, during the winter Cyprus also has a lot of sunshine and as a result there are wide seasonal and daily temperature fluctuations. These fluctuations affect the local microclimate and the local effects especially near the coast.
It should also be mentioned that the microclimate inland is affected by the two mountain ranges, the Troodos massif rising to 1951 m and the long narrow Pentadaktylos mountain rising to 1000m.
The rainfall in Cyprus (e-Appendix 4 Figure 232) and in both cities is very low in comparison with other European countries. The average annual total precipitation increases up the south- western windward slopes from 450 millimetres to nearly 1,100 millimetres at the top of the central massif. On the leeward slopes precipitation decreases steadily northwards and eastwards to between 300 and 350 millimetres in the central plain and the flat south-eastern parts of the island. Statistical analysis of rainfall in Cyprus reveals a decreasing trend of rainfall amounts over the last 30 years. In e-Appendix 4 Figure 232 indicates that compared with Nicosia Limassol has higher rainfall during November, December, January and February.
The mean humidity at 0800hrs for the two towns is shown in e-Appendix 4 Figure 233 and at 13:00hrs in e-Appendix 4 Figure 234. It can be observed that at 08:00hrs Nicosia has higher values for the period October to March, but during spring and summer Limassol has higher relative humidity. In contrast, at 13:00hrs (e-Appendix 4 Figure 234) Limassol has much higher relative humidity, especially during the summer. The humidity ratio is greatest during the months of June to September. Generally, the humidity ratio increases during the morning and early evening hours of a day. However, the research around this issue revealed that during the summer, mostly in the afternoons, westerly winds affect inland-Nicosia resulting in lower temperatures. Furthermore, at night there are lower humidity levels due to the katabatic dry winds from the Troodos Mountains that influence the central plain.
The mean daily sunshine (e-Appendix 4 Figures 235 and 236) has the same profile and is at almost the same levels in both towns. In general all the towns of Cyprus enjoy a very sunny climate and the average number of hours of bright sunshine for the whole year is 75% of the time the sun is above the horizon.
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For more than six months per annum there is an average of 11.5 hours of bright sunshine per day, decreasing in winter to 5.5 hours in the cloudiest months, December and January. Even the cloudiest winter months have an average of almost 4 hours of bright sunshine per day.
In e-Appendix 4 Figure 237 shows that south facing surfaces receive the highest solar irradiation during October to February and much less during April to August. In contrast, the solar irradiation on horizontal and east facing surfaces is very high during the period March till September. In addition West and North facing surfaces obviously receive the lowest radiation throughout the year. The solar radiation can be explained by the sun’s trajectory which, for the latitude of Cyprus (35°), brings the sun at a maximum altitude angle of about 78° at noon in June and a minimum of 32° in December.
As shown in e-Appendix 4 Figure 238, Limassol presents higher values of wind speed compared with Nicosia, especially during the period August to May. At the end of spring and beginning of summer the two towns present similar values of wind speed. It is important to remember that Limassol is situated on the coast and Nicosia lies inland. Due to the lack of data for the wind direction for the two towns, the statistical analysis is based on a 4 year data period, from 2006 to 2009.As shown in e-Appendix 4 Figure 239, Nicosia and Limassol have a stable profile of wind direction with some small differences throughout the years. The main directions for Nicosia are West and South West winds and for Limassol they are South West, West and North West winds.
6.8. Comparison of heating and cooling degree days
Another important factor to be analyzed was the heating and cooling degree days. It is common knowledge that the calculation of heating and cooling energy consumption in a building is not easy. The cooler the outside air temperature, the more energy it takes to heat a building and vice versa for the cooling process. However, as the above weather analyses showed, there are monthly and daily temperature fluctuations that are strongly related with the building energy performance.
The heating degree days (HDD) is way to calculate how much in degrees and for how long in days the outside temperature was below a certain level. On the other hand, the cooling degree days (CDD) is the calculation of how much in degrees and for how long in days the outside temperature was above a certain level.
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In other words, the heating degree days are the days when the building needs heating and cooling degree days are the days when the building needs cooling. The methodology for producing the heating and cooling degree days is not part of the work of this research.
325 300 275 250 225 200 175 150 125
Heating degree days 100 75 50 25 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Larnaca Airport, CY (33.62E,34.87N) Akrotiri, CY (32.99E,34.59N)
Athalassa, CY (33.40E,35.14N) Larnaca-IES (176090_IWEC -1969-1999)
Figure 38: 5-year-average (2007 to 2011and 1969 to 1999) heating degree days for base temperatures of 20oC. Figure 38 shows the 5 years average heating degree days for Limassol (Akrotiri station), Nicosia (Athalassa) and Larnaca (Airport station) compared with Larnaca IES data for the years 1996 to 1999. The demand for heating is higher inland and lower on the coast. However, the data demonstrates clearly that there are essential differences between the weather data that was collected in the past and the recent data. Even comparing the same location, Larnaca, it is apparent that there are crucial differences.
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325 300 275 250 225 200 175 150 125
Cooling degree days 100 75 50 25 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month Larnaca Airport, CY (33.62E,34.87N) Akrotiri, CY (32.99E,34.59N)
Athalassa, CY (33.40E,35.14N) Larnaca-IES (176090_IWEC -1969-1999)
Figure 39: 5-year-average (2007 to 2011 and 1969 to 1999) cooling degree days for a base temperature of 20oC Figure 39 shows the cooling degree days for the three locations. According to the results, the cooling demand for the period 2007 to 2011 is higher inland. However, the two coastal stations also have differences in cooling demand, where Larnaca has a higher demand than Limassol. Moreover, there are also differences between the Larnaca IES data and the latest data of Larnaca station and the old data is not even representative of the same place.
In general, the data for heating and cooling degree days is essential for building energy calculations. Furthermore, the data and the graphs were vital for the current weather analysis in order to understand the impact of the weather change on the building’s energy consumption.
6.9. Weather data analysis-Conclusions.
The previous subchapters presented the weather data taken from different sources. The analysis revealed valuable information about the Cyprus climate and climate changes over the years. According to data from Cyprus Meteorological Office, climate changes have affected Cyprus and are evident in precipitation and temperature observations. Comparing the precipitation for the periods 1961-1990 and 1991-2008 (17 hydrometeorogical years) there is a reduction of 9% where the precipitation was 503mm for 1960- 1990 and 457mm for 1991- 2008. Based on this rate of change it is expected that by 2030 precipitation in Cyprus will decrease by 10-15% which means that the climate will experience more drought. [82]
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Table 32: Annual precipitation in the past twenty years (1991-2011) [82]
Hydrometeorological Year Annual Precipitation % Normal (mm) (1961 – 1990) (%) 1991-1992 637 127 1992-1993 509 101 1993-1994 417 83 1994-1995 493 98 1995-1996 383 76 1996-1997 399 79 1997-1998 388 77 1998-1999 473 94 1999-2000 363 72 2000-2001 468 93 2001-2002 604 120 2002-2003 561 112 2003-2004 545 108 2004-2005 412 82 2005-2006 360 72 2006-2007 479 95 2007-2008 272 54 2008-2009 527 105 2009-2010 546 109 2010-2011 465 92 Average for the last twenty 465 92 years
Comparing the average annual temperatures for the periods 1961-1990 and 1991-2008 shows an increase of 0.5oC where the average annual temperature was 17.20oC in 1961-1990 and 17.70oC in 1991-2008. Based on this rate of change it is expected that by 2030 the temperature will increase by 1.0-1.5oC compared to the normal values of the period 1961- 1990. [82]
It is essential to mention that according to the analysis and the references to previous data, the warmest years in Cyprus occurred in the 20th century over the last two decades. Based on the recorded data 1998 was the warmest in Cyprus with the island experiencing a very severe heat-wave. Moreover, in August of 2010, the highest maximum temperature of 45.6oC was recorded in Nicosia. In general there is a tendency in Cyprus and in the Eastern Mediterranean for increasing temperatures. The climate is tending to be hotter in winter and even hotter in summer and this affects people’s behaviour.
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Figure 40: Annual temperature for 1901-2011. [82]
The weather analysis revealed significant information about the weather conditions in Cyprus that is impossible to ignore. The first is the fact that there have been significant changes in climatic conditions throughout the years and so it is important to record weather file data for better and more precise energy estimations in building performance.
The second is the fact that there are significant weather differences not only between the periods of data but also between the Cyprus towns. The micro-climates of the towns are affected by geomorphological conditions of Cyprus. However, the difference between the towns cannot be ignored and so it was necessary to create weather simulation files in order to record the difference during the simulation procedure.
The third is that the IES weather simulation file needed to be updated as according to the current data it underestimates the cooling and overestimates the heating. Using old data weather simulation files it is possible to have erroneous predictions for the building operation energy demand. Incorrect calculations, estimations and predictions for future energy building performance could possibly lead to incorrect energy saving measures.
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The fourth is related to data sources. When using the old weather files for construction of future weather simulation files, climate changes will be underestimated and the files will not accurately describe the real conditions.
The simulation files must be updated as they are of vital importance for the building simulation programs. The comfort zone, the HVAC profiles and the general operation of the building is based on the weather data that is given during the simulation procedure. Any results that are based on old weather simulation files will probably be wrong and will underestimate the real energy needs of the building for maintaining internal human comfort.
The weather analysis and construction of new simulation weather files were not part of the initial targets of this project. However, research and analysis revealed the importance of the weather simulation files for the building simulation. The analysis helped not only in the construction of the new weather simulation files but also in understanding how the microclimate could affect building performance and operation. Any calculations of the building simulation program are based on the weather data that is given by the user, so it was very important for this project to achieve accurate results as close as possible to reality.
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Chapter 7: Building simulation theory
7. Modelling and Simulation tool.
Building simulation is powerful tool that makes it possible to predict the future performance of a building in the process of design or construction or renovation.
According to Oxford Dictionaries (2010), the word “model” can be defined as “a simplified description, especially a mathematical one, of a system or process, to assist calculations and predictions” or “a three-dimensional representation of a person or thing or of a proposed structure, typically on a smaller scale than the original”.[132]
On the other hand, the Business Dictionary defines the “simulation” as “Acting out or mimicking an actual or probable real life condition, event, or situation to find a cause of a past occurrence (such as an accident), or to forecast future effects (outcomes) of assumed circumstances or factors”.[133] These two words are strongly related because the simulation procedure presupposes the existence of a model.
However, the simulation procedure can be achieved through the solving of set equations (a mathematical model), construction of a physical model (scale) and a computer graphics model. All these available tools are able to provide a prediction of the model performance by taking into account simplifications of the reality and possible user’s assumptions and through experimentation and without exposure to risk.
Generally the modelling and simulation procedure is the endeavour, with the aid of a computer, to predict behaviours or changes in a system, without a high risk exposure. This project is based on the building modelling and simulation with the aim of achieving the zero energy building.
7.1. The aim of modelling or simulation development
During this research it was important to identify the system that was to be examined, present it with a model and finally simulate the model with the help of a computer program. A system exists and operates in time and space while a model is a simplified representation of a system at a specific time. The simulation tool is the handling of a model, with assumptions and simplifications, whereby it presents or predicts the performance of the system.
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Through this process it is possible to evaluate different designs, technologies or operations without a high cost or risk. In addition, the main aim of the modelling and simulation of a system is to predict possible failures or problems during the system operation. This early design stage is critical as it can reveal new options or new prospects for the development system. However, with the simulation it is possible to observe the future performance of the system under hypothetical conditions, which means that the performance of current decisions can be tested at a future time. In the building sector the actions or decisions taken in present time can potentially affect the future performance of the building, as the building life is more than 70 years. Prediction of future performance is vital if the building is to operate at optimum capacity throughout its life-cycle. Capacity refers to reliable predictions of energy consumption in order to have something against which to benchmark actual energy consumption data.
In general, with the modelling and simulation, it is more cost-effective to create a model of a system which has already been defined and to test alternative solutions rather than building a real prototype with problems. The trial and error method would be more costly and time- consuming.
7.2. Energy Analysis Programs
Buildings consist of many complicated components and a deep analysis needs to be made in order to achieve accurate results. The buildings’ energy performance in particular is influenced by many factors and for this reason there is a need for simulation programs during the energy calculations. These simulation programs consist of factors such as designing tools and detailed simulation programs, both of which contribute to the energy analysis of a building.
In general, building simulation provides the key to assessing /evaluating/weighing up crucial building issues such as energy efficiency, carbon reduction, human comfort, the building systems interaction and the implementation of the European energy requirements.
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7.2.1. Building Energy Simulation Tools Computer Simulation Programs are programs designed to help engineers during energy analysis and simulation. Most of these programs are based on multiple zone buildings and simulation of their heating, ventilation, and air conditioning systems (HVAC). Nowadays, the progress and development of computer systems and their software offer amazing power tools for computer simulation which helps engineers in their work. Generally, the theory of building energy simulation consists of traditional methods of load and energy calculations in heating, ventilating and air conditioning design. [134]
During the process of energy calculation, the target is to estimate the energy demands of the buildings so that they will be able to cover the required loads throughout the year. On the other hand, the load calculations aim to determine the peak design thermal loads of the heating, ventilation, and air conditioning systems (HVAC) in order to size and design the equipment and plant. However, the connections between the design parameters and energy usage characteristics of a building and the analysis of its energy performance can be achieved only through the building energy simulation. The benefit of a building simulation is that it offers the opportunity to simulate and observe the impacts of all the possible changes of the building plants - in a few words, to observe the building on a real life basis. Looking at design evaluations and system selections on a building simulation can therefore also afford detailed information about energy consumption, equipment and plant performance and indoor environmental conditions. [135]
Figure 41: Major elements of building energy simulation. [135]
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Figure 41 shows the most important components of a building energy simulation procedure. The simulation system includes a variety of models, but the main ones that influence the building energy flows are: the building model, the heating, ventilation, and air conditioning systems (HVAC) model, the heating, ventilation, and air conditioning systems (HVAC) plant model and the Control system model.
The inputs of the simulation depend on the user’s program or model but generally the most common inputs are the building’s description and design parameters - the boundary condition is the climatic context of the location. On the other hand, the expected results are data about the building’s energy consumption, peak demands and indoor environmental conditions. With the use of simulation programs, the engineers aim to provide/ensure comfortable conditions in the building whilst also considering low energy consumption, optimizing the systems performance and comparing different design options based on the life cycle costs of the building. [136]
The calculations of detailed simulation programs offer dynamic interactions between thermal base components such as structural components, HVAC systems and lightings based on hourly data and this is always different for each building zone. [137]
These programs are under continuous development and there are always more and more large and complex energy simulation programs available in the market. Generally, all these programs can be divided into two categories: the open source code and the proprietary programs. The BLAST and DOE-2 are the most commonly used open source programs.
At the moment, there are many available simulation programs for building energy analysis. These programs can be simple or detailed and sophisticated, but in general it is difficult to separate them into categories because most of them have multiple features. The BESA, BLAST, BUNYIP, DOE-2, ESP-II, ESP-r, HVACSIM+ and TRNSYS are considered modern programs and offer the user the opportunity to model a building in detail. The problem is the number of requirements and numerous inputs the user needs to provide. Some other programs such as the HAP and TRACE 600 have fewer requirements and are easier to use so these are more popular in designer offices. [135]
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The building simulation programs are continuously being developed but until now they have had some major weaknesses, such as the programs input has large volumes and is scientifically detailed – whereas some dates are usually unavailable during the early design stages and many hypotheses are demanding - and the program outputs consist of large computer printouts that confuse the user. [135]The market and the users play an important role in the improvement of the programs and this can in turn help to overcome their weaknesses. In the building design process, effective work with simulation tools means that practitioners should learn to work within the limitations and appreciate the role of simulation. [135]
Generally, the design of a building can be separated into the architectural design and the engineering design. During the architectural design, the focus is on the graphical images which are determined by the form, shape, and facade whilst the engineering designs focus on the system design plants which concern the performance of thermal and HVAC calculations.
Finally, the costs involved in the simulation procedure also need to be considered. The computer system and the cost of its software are all part of the operation of a building energy analysis program and learning about the program and how to use it can be a costly procedure. However, a user’s experience with previous programs may help to reduce the cost of learning from the beginning. Moreover, some of the factors which influence the cost during the learning stage are the complexity of the data input procedure, the quality of the user’s manual and proper support for the users. Even an experienced user can face difficulties with a new simulation program which demands numerous and complex input data.
7.3. The choice of the Integrated Environmental Solutions (IES)
The issue during the development of the project was the choice of the simulation program that would carry out the simulation procedure and give accurate results. The first step was to explore the choices according to specific criteria such as the meeting of the validation standards, the use of calculation methodologies and the licence cost.
After detailed research of the numerous available simulation programs, the project chose the Integrated Environmental Solutions (IES) building simulation program which is a powerful, in-depth suite of building performance analysis tools.
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An essential point that influenced the project decision was the validation and testing of the IES VE. Extensive research showed that the IES Virtual Environment meets the standards of ASHRAE 140(2001, 2004, 2007), ASHRAE/BESTEST evaluation protocol, CIBSE TM33, European Union ( EN13791: July 2000) and EPACT Qualified (Qualified Computer Software for Calculating Commercial building energy and Tax deductions)[138][139]. In addition the IES VE can undertake the methodologies of UK National Calculation methodology (NCM), ASHRAE 55 calculation procedure, ASHRAE 90.1 Appendix G PRM calculation procedure, ASHRAE 62.1 calculation procedure and ISO 7730 calculation procedure. [140]
In the conference paper Attia, S. et al [141] there is a comprehensive analysis and comparison of ten different building simulation tools. The two main criteria of the research was the Usability and Information Management (UIM) of interface and the Integration of Intelligent design Knowledge-Base (IIKB). The IES VE ranked first (85%) among the other nine tools (HEED (82%), eQuest (77%), ECOTECT (61%), Design Builder (58%), Green Building Studio (58%) , Energy 10, (57%), Energy Plus-SketchUp Plugin (40%), Energy Plus(36%) and DOE-2 (29%)). According to research, the IES VE tool provides default values and templates facilitating quick entry; it also supports a progression in thermal performance analysis as it gets quick answers in early design progressing to detailed analysis in the later design phases.[142]
A technical report, " State of the Art of Existing Early Design Simulation Tools for net zero energy buildings: A Comparison of Ten Tools" [143] provides a comparison between the HEED, e-Quest, ENERGY-10, Vasari, Solar Shoebox, Open Studio Plug-in, IES-VE- Ware, Design Builder, ECOTECT and BEopt programs based on five criteria including usability, optimization, interoperability, accuracy and design process integration of the tools. Generally the IES VE program presents high usability, medium intelligence, medium interoperability, medium process adaptability and high accuracy. [144]Concerning NZEB objective, IES VE- Ware allow feasibility assessment of user selected renewable and low carbon technologies including wind power generators and photovoltaic arrays. [145]
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In addition to the technical reasons that determine the decision of which program could be used, the licence cost had strong influence on the project options. Due to the scholarship and limited funding, the project searched for the best combination of economical solutions which would also have high standards and accuracy. At that time the School of Mechanical, Aerospace and Civil Engineering had already bought a licence of use of IES VE and was able to provide one to the project without any extra cost.
However, the IES is one of the most commonly used programs and is relatively easy to use. It offers a range of design-oriented building analysis through a single and friendly user environment. The program includes a tool for 3D geometric representation modelling of the building to which it is possible to apply specific data. The program environment offers a detailed evaluation of the building and its system designs. Further optimizations of the systems are possible considering the comfort criteria and energy use [146].
The IES enables the user to work with the ApacheSim tool, a powerful and useful tool for engineers. According to AHSRAE, it is a “dynamic thermal simulation tool which is based on the first principles of mathematical modelling of the building heat transfer processes. It has been tested using ASHRAE Standard 140 and qualifies as a Dynamic Model in the CIBSE system of model classification.” [147][148]
Last but not least, the IES simulation program uses real weather data. During simulation, the accuracy of its results is influenced by weather data imports. The current weather conditions of each area are an important factor for the simulation procedure, and as climate changes, old weather data is not trustworthy. The available weather data on an IES simulation may cover any period of time from a day to a year. The time progress of the building’s thermal conditions is traced at intervals as small as one minute. [147][148]
According to the IES manual, the simulation results may include: Over 40 measures of room
performance including air and radiant temperatures, humidity, CO2, sensible and latent loads, gains and ventilation rates; Comfort statistics; Natural ventilation rates through individual windows, doors and louvers; Surface temperatures for comfort analysis and CFD boundary conditions; Plant performance variables; Loads and energy consumption and Carbon emissions. [147][148]
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7.4. The Project through the IES
The Virtual Environment (VE) v 6.4.8 was selected to perform this case study and carry out the final results. The reasons for this were that firstly, it was the program that the University offered and used in the department, and secondly, it allowed a single model to be used for all the required aspects of the study. However, the program offers the user the ability to make detailed evaluation of the building and system design. The most important issues that can be addressed with IES
In addition, Virtual Environment (VE) v 6.4.8 makes possible the analysis of different parameters of the project such as the Climate, Natural Resources, Energy, Solar, Light, Carbon Footprint, Building Metrics, Renewable Systems, Thermal Comfort/Loads, Sustainability Compliance (LEED/BREEAM/Green Star/Local Regulations/Energy Certification), Airflow CFD and Value/Cost. [149]
This project focuses on the energy consumption of the building, the shading issues, the
HVAC system, CO2 emissions, the occupants’ comfort and the renewable energy systems. The IES program offers building energy, thermal and carbon emission analysis tools. It enables the interrelated dynamics of a building and its surroundings to be assessed so that users can understand the effectiveness of a building and its energy systems right from the very earliest stages of design – quickly and easily. This enabled the project to reach the correct decisions at an early design stage (Figure 42) for the energy performance of the building.
Figure 42: Early stage design-a detailed design.[149]
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In order to achieve the goal of this project, a variety of different tools from the IES package are used such as ApacheSim, which is fast, accurate dynamic thermal simulation for energy/carbon modelling and enables the assessing of every aspect of thermal performance, from annual energy consumption and carbon emissions to individual surface temperatures.
The ApacheCalc performs heat loss and heat gain design calculations, using procedures laid down by the Chartered Institute of Building Services Engineers (CIBSE), to determine building heating and cooling loads. The ApacheLoads calculates design heating and cooling loads using procedures laid down by the American Society of Heating Refrigeration and Air- Conditioning Engineers (ASHRAE) [150] and these calculations, based on the ASHRAE Heat Balance Method.
The ApacheHVAC enables the simulation of heating, ventilation and air-conditioning systems quickly and easily. It uses a flexible component-based approach which enables one to assemble systems on-screen as designed. With ApacheHVAC it possible to cover all common system types including VAV, CAV, fan-coil, VVT, displacement ventilation, hollow-core slab systems and under-floor heating. It should be mentioned that ApacheHVAC is dynamically integrated with the IES building simulation software (ApacheSim). This is vital for ensuring reliable estimations of plant sizes, optimization of the plant/controls operation and accurate assessment of carbon emissions.
The MacroFlo simulates air flow driven by wind pressure and buoyancy forces (and mechanical air movement if used in conjunction with ApacheHvac)[149]. Using this option it is possible to carry out studies of natural ventilation, infiltration, and façade analysis and mixed-mode design. The application areas include: single-sided ventilation, cross-ventilation, whole building ventilation strategies, chimneys and opening controls.
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Figure 43: IES capabilities diagram. [149] In addition, an important parameter is the light/ daylight control. The quality of light, either natural or artificial, dramatically influences a building's ambience and energy efficiency as well as occupant comfort and wellbeing. The IES offers a package which permits the placing and editing of luminaires within a room for subsequent analysis.( Figure 43) Moreover, it is possible to use SunCast which is a powerful solar analysis tool that enables the performance of solar geometry studies on a building and its site. It can be used at the earliest stages of the design process to maximize site orientation, for right to light studies and when seeking planning approval. The numerical information generated by SunCast can be used to enhance thermal analyses performed by the IES APACHE software. [149]
Finally, another vital issue in building analysis is the value/cost which cannot be ignored. The closely linked Deft, Cost Plan and Lifecycle modules within VE-Pro allow the detailed, effective and structured study of value engineering across the entire design process. A range of building performance indicators can be used to compare different design options at any stage of the process. Taking an in-depth look at whole building life cycle costs is imperative and can help justify sustainable design decisions based on payback periods and Return on Investment (ROI) calculations that look beyond initial capital costs of systems and measures to include annual energy bill savings and maintenance costs. [149]
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7.5. IES Simulation: thermal applications
The thermal analysis of buildings can be achieved through the use of the thermal applications category of the Virtual Environment (IES), which consists of thermal analysis software facilities. There are three main applications in the thermal application category. The first is the Virtual Environment compliance which checks: the analysis to test compliance with Part L of the UK Building Regulations (2010) – England & Wales; the analysis to test compliance with Part L of the UK Building Regulations (2010) – England & Wales; and the analysis to test compliance with Section 6 of the Building Regulations (2010) – Scotland. The second is the Industry-standard thermal calculations which check: the CIBSE heat loss calculations (ApacheCalc, Vista); the CIBSE heat gain calculations (ApacheCalc, Vista); the ASHRAE heating loads calculations (ASHRAELoads, Vista) and the ASHRAE cooling loads calculations (ASHRAELoads, Vista). The third category is the Dynamic simulation (ApacheSim and related programs) which checks: the Building dynamic thermal simulation (ApacheSim): the Natural ventilation simulation (MacroFlo); the HVAC system simulation (ApacheHVAC); and the Results viewing and analysis (Vista, OutView, PlotView). [151]
The Apache Application View prepares the input data for Apache calculations for ASHREA loads and ApacheSim. In addition,it carries out the calculations and simulations using the ApacheCalc, ApacheSim, ApacheHVAC and MacroFlo.[151] The ApacheHVAC Application View prepares the input data for the ApacheHVAC simulation. The MacroFlo Application View prepares the input data for MacroFlo simulation. The Vista Application View presents and analyses the results from the ApacheSim, ApacheHVAC and MacroFlo simulation. [151]
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7.6. IES Simulation: Thermal application data requirements.
An important factor for all the simulation packages is the geometrical data from the ModelBuilder. The ModelBuilder is important because it is the interface by which the data for the simulation is input. The geometrical data includes the geometry of the building which is to be simulated and hence the building design and geometry are very important during the simulation.
Figure 44: IES process flow chart [152]
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The simulation data is managed by the different simulation packages-programs (Figure 44) that are in the Application Views. However, the input data is available, where possible, for common use by all the programs so that it will not be necessary for the data used in the simulation and the analysis to be re-entered multiple times. Templates are objects that are available in a simulation program and can further improve the efficiency of the data input. The input data-thermal input variables- can be grouped together under the Templates and can be assigned to sets of rooms, building elements or other objects. There are different types of template such as the construction templates which store descriptions of constructions for the various categories of building element (walls, floors, windows and so on) and the room thermal templates which store sets of casual gains, air exchanges, plant operation parameters and zoning information associated with rooms of a given type. The Templates of each project can be transferred to another project and so they are invaluable in maintaining data quality and saving the user’s time.
7.6.1. Site location and Weather data.
The APlocate program in IES defines the location of the building and the climate conditions of the simulated location. The latitude and longitude of the site, the information about the local time zone and any summertime clock adjustment are included in the location data that the user sets. [151]
The weather data files which are available in the IES database have significant implications for the results of the whole project. The weather data is related directly with the calculations of heat loss and heat gains and the thermal simulation program. However, it is important to stress that the weather data takes the form of a single outside winter design temperature for the heat loss calculation.[151] On the other hand, the heat gains calculations are based on hourly dry-bulb temperatures, wet-bulb temperatures and solar data for one design day per month.
The weather data for thermal simulation need to be more extensive and can be found in IES weather files or other compatible weather files. The weather data files include specific variables (hourly measures) such as the dry-bulb temperature, wet-bulb temperature, direct beam solar radiation, diffuse solar radiation, wind speed, wind direction and cloud cover.[151]
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7.6.2. Constructions
The program Apache constructions database manager (APcdb) is responsible for the material composition such as the walls, the windows and other building elements. The APcdb has a wide variety of materials and constructions that can be used and edited during the development of the building project. The constructions data of the IES program includes thermo-physical properties and widths that give the detailed analysis to the building project. For example, the glazing construction the layers provide the solar transmittance, absorptance and reflectance characteristics of each glaze type. [151]
Another important issue for the construction is the fact that it calculates the U-values and admittance parameters, the glazing angular solar transmission properties and provides condensation analysis.[151]
7.6.3. Profiles
The IES profiles are controlled by the program APpro. They are utilised by the user in order to describe the time variation of input variables and to make more clear how quantities (such as casual gains, ventilation rates and set points) fluctuate over the hours of the day, the days of the week and the months of the year. [151]
However, an important issue is the formula profiles which, according to the IES program, allow inputs to vary in response to room or external conditions arising during simulations. [151]
7.6.4. Internal Gain
During the thermal simulation and heat gain calculation of the heat gains from occupants, lights and equipment are needed as input data in order to have accurate estimations. It is possible that the heat gains will be sensible or latent where the sensible gains are considered by radiant fraction.
It is possible to specify separately for every single room the level and types of these casual gains in combination with profiles that indicate their time variation. (Room Thermal Template).[151]
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7.6.5. Infiltration and Ventilation
The definition (specification) of infiltration and ventilation rates can be achieved through the setting of maximum value and a profile. However, there is an option to represent the ventilation as natural or mechanical and the source of the ventilation can be outside air, air from another room or air at a definite (possibly time-varying) temperature. It is possible to control and combine the air exchanges with the Room Thermal Template. The MacroFlo and ApacheHVAC programs can calculate dynamically the pre-specified air exchanges which are supplemented by natural and mechanical ventilation air flows.[151]
7.6.6. Plant and Controls
The IES simulation program needs input data (characteristics of the systems) in order to simulate the rooms conditioning system such as the heating, the cooling, and the humidification or dehumidification systems. The set-points, the heating and cooling capacities and the radiant fractions, together with profiles defining periods of plant operation, are defined by the room control specifications. These parameters are very important for the internal environment conditions and form part of the Room thermal Template. [151]
7.6.7. Heating and Cooling Zones
The IES program offers the user the ability through the Thermal View to group the rooms of the building into Heating and Cooling zones, in order to sum up the results from calculation or simulation. [151]
7.7. IES Simulation:Industry-standard Thermal Calculations (ApacheCalc)
The ApacheCalcprogram, which includes the CIBSE Heat Loss & Heat Gain, is responsible for the heat loss and heat gain calculations. The calculations are based on the procedures laid down in CIBSE Guide A (1995, 1999, 2001). [151][153][154]
7.7.1. Heat Loss
The heat loss calculations are very important for the room heating requirements and the sizing of the heating plant. During the Steady-state room heat losses calculations the casual and solar heat gains are not included, but there is an option to calculate the conduction heat gains from adjacent rooms and the effects of mechanical and natural ventilation air exchanges. The final results from the simulation and the calculations are accessible through the Vista program and can be seen in table format or histograms of room or zone heat loss.
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In addition, the losses can be expressed on a floor area or room volume basis in combination with room temperature.
7.7.2. Heat Gain.
The room cooling requirements and summertime temperatures are included and calculated in heat gain. The calculations for Room cooling loads and free-floating temperatures are based on the CIBSE admittance procedure[154] The APlocate program provides the weather data that is needed for the calculations and in addition the timing and nature of each gain during the calculations is taken into account by applying the appropriate radiant fraction to all sources of heat and cooling.
The solar transmission properties of room or building windows (glazing) analysis are based on Fresnel equations. The Fresnel equations (or Fresnel conditions), describe the behaviour of light when moving between media of differing refractive indices [155]. It is important to stress the fact that the calculations of SunCast for the effects of ventilation air exchanges and external solar shading may be combined with solar transmission properties.
The final results from the simulation and the calculations are available through the Vista program and can be seen in table format or histograms of room or zone heat loss.
7.8. IES Simulation:Industry-standard Thermal Calculations (ASHRAE Loads)
The IES ASHRAELoads program (ASHRAE Heating and Cooling Loads) is based on ASHRAE Heat Balance Method[156][157] in order to calculate the heating and the cooling loads.[151]
7.8.1. Heating loads.
The heat loads calculations are significant for the room heating requirements and the sizing of heating plant. During the Steady-state room heat losses calculations the casual and solar heat gains are not included, but there is an option to calculate the conduction heat gains from adjacent rooms and the effects of mechanical and natural ventilation air exchanges. The final results from the simulation and the calculations are accessible through the Vista program and can be seen in table format or histograms of room or zone heat loss. In addition, the losses can be expressed on a floor area or room volume basis in combination with room temperature.[151]
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7.8.2. Cooling Loads.
The room cooling requirements and summertime temperatures are included and calculated in Cooling Loads. The calculations for Room cooling loads and free-floating temperatures are based on ASHRAE Heat Balance Method. [156][157]The APlocate program provides the weather data that is needed for the calculations and in addition the timing and nature of each gain during the calculations is taken into account by applying the appropriate radiant fraction to all sources of heat and cooling.
The solar transmission properties of room or building windows (glazing) analysis are based on Fresnel equations. The Fresnel equations (or Fresnel conditions), describe the behaviour of light when moving between media of differing refractive indices [155]. The calculations of SunCast for the effects of ventilation air exchanges and external solar shading might be combined.
The final results from the simulation and the calculations are accessible through the Vista program and can be seen in table format or histograms of room or zone heat loss.
7.9. IES simulation: Thermal Simulation (ApacheSim)
The IES includes the ApacheSim program which is very important for the dynamic thermal simulation. The calculations of the ApacheSim program are based on first-principles mathematical modelling of the heat transfer processes occurring in and around a building.[151]
The CIBSE system of model classification qualifies the ApacheSim ad a Dynamic Model which goes beyond the requirements of such a model in several areas. The ApacheSim program is responsible for the detailed evaluation of building and system design while at the same time it allows their optimisation based on comfort criteria and energy use. In addition, the ApacheSim can individually simulate and integrate conduction, convection and radiation heat transfer processes for each element of the building fabric in combination with models of room heat gains, air exchanges and plant. [121]
The calculations of the program are based on real weather data and may refer to any period from a day to a year. The data exists in the IES database but can be inserted from external sources if it is in an appropriate format. The time-evolution of the building’s thermal conditions is traced at intervals as small as one minute. [151]
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According to the IES manual, the simulation engine has many features such as the finite difference dynamic heat conduction modelling; the dynamically calculated surface convection characteristics; the air temperature, surface temperature and room humidity modelling; the advanced solar and long-wave radiation exchange models; the external solar shading using data from SunCast; the solar tracking through an arbitrary number of transparent internal partitions using data from SunCast; the Angle-dependent glazing transmission, reflection and absorption characteristics; the Accurate accounting for the radiant/convective characteristics of casual gains and plant heat inputs; the Room plant and control models allowing for limited heating or cooling capacity; the Simultaneous solution of sensible and latent heat balance equations for the whole building; the optional integration with natural ventilation air flow simulation (MacroFlo) or HVAC system simulation (ApacheHVAC); and the Simultaneous integration with both MacroFlo and ApacheHVAC for the simulation of mixed-mode systems.[151]
The results of the simulation procedure include the comfort statistics, energy consumption data, CO2 emission data, room load statistics, plant sizes, surface temperatures for comfort studies or CFD boundary conditions and comprehensive performance measures with hourly room temperatures (air, mean radiant and dry resultant), humidities, plant loads, casual gains and air exchanges.[151]
7.10. IES simulation: HVAC System Simulation (ApacheHVAC)
The heating, ventilation and air conditioning systems performance and operation are simulated by the ApacheHVAC program. The ApacheHVAC is connected with the building simulation program ApacheSim and there is an option for the user to link the MacroFlo program too. The ApacheHVAC provides more functions to the ApacheSim program through the comprehensive demonstration of room heating and cooling units, air handling systems, central plant components and controls. Through this powerful tool the user has the capability to accurately estimate the energy use, the fresh air loads, the free cooling, the heat recovery, the component sizing, the sizing of mechanical air flows, the system psychrometrics, the distribution efficiency, the boiler and chiller performance, the fan and pump energy and the mixed-mode operation. [151]
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Through the graphical interface of the program the IES user has the ability to create a system plan representation and to set the operational parameters for its components. The building blocks include components such as rooms, radiators, direct-acting heaters and coolers, chilled ceilings, heating and cooling coils, ducts, fans, humidifiers, heat recovery devices, controllers, boilers and chillers.[151]
There is the option to configure and simulate on-off, proportional control and complex control functions through controllers that are available in the program. However, the profiles control the time variation of operational parameters and the formula profiles offer supplementary flexibility in control conditions. [151]
The program offers an almost unlimited range of system types (such as the Variable air volume (VAV), Constant air volume (CAV), Fan-coil, Displacement ventilation, Chilled beams, Radiators, Underfloor heating) that can be used in order to simulate the system of the building. [151]
During the simulation it is possible to have natural ventilation analysis with the use of the MacroFlo program. If the user ticks the box of the MacroFlo, then the program will calculate all flow imbalances ascending in the system simulation, showing a path for the simulation of mixed-mode systems. [151]
The ApacheHVAC is a powerful tool that produces a broad range of results (outputs) and it is possible to track separate psychrometric and control processes occurring inside a system. In addition, the program can present more results-outputs such as monthly energy loads and consumption totals, optionally broken down by fuel or component type. [151]
7.11. IES simulation:Natural Ventilation Simulation (MacroFlo)
The IES program includes the MacroFlo simulation program, which is actually responsible for the design and evaluation of naturally ventilated and mixed-mode buildings. This program works in combination (optional) with ApacheSim and during the simulation procedure the two programs exchange data in order to achieve a fully integrated simulation of air and thermal exchanges. [151] During the building simulation there are various issues, such as the infiltration, single-sided ventilation, cross-ventilation, natural ventilation, temperature- controlled window opening and mixed-mode solutions (used in conjunction with ApacheHVAC) that can be addressed with MacroFlo.
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The design of the building geometry and the development of the building model includes windows, doors and ‘holes’ that allow the air flow. The flow of air is created from the pressures arising from wind and buoyancy forces (stack effect) and can be simulated with the MacroFlo program. The MacroFlo calculations take into account the mechanical air flows that were set up in the ApacheHVAC program.[151]
The weather data files provide the necessary data to the MicroFlo program in order to calculate the wind pressures on the exterior surfaces of the building at each simulation time step. In addition, the combination of wind speed and direction data with opening orientations and wind exposure give the wind pressure on each external opening. The calculations contain wind pressure coefficients that were result of wind tunnel experiments. The buoyancy pressures are not constant and change with height in accordance with temperature-dependent air densities.[151]
The calculation of the flow though each opening is given as a function of the imposed pressure change and the features of the opening. The relation between the height and the buoyancy pressures shows that two-way flow can happen through a single opening either side of a neutral pressure plane. The communication between the MacroFlo, ApacheSim and ApacheHVAC allow the exchange of data in order to successfully reach the concurrent solution of the inter-dependent thermal and air flow balances. [151]
7.12. IES simulation: Viewing and Exporting Simulation Results (Vista, OutView, PlotView)
The results of the IES simulation program are presented through the Vista program. The Vista program is part of the Virtual Environment and thus it has access to the ModelBuilder view (geometry model). A natural framework for browsing simulation output datasets is provided by the geometry model.[151]
The graphic environment in combination with the model image permits/enables the user to have a direct access to graphs or tables of room temperatures, plant loads, casual gains and other simulation variables, just by pointing the mouse. The program can present the results for different rooms in graphs and allow comparisons between the resulting datasets. [151]
The MacroFlo simulation results can be presented at the room level or the opening level. The IES provides detailed analysis of the natural ventilation flows such as graphs of in-flows, out- flows and the degree of opening.
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The ApacheHVAC results for the energy and load totals can be presented as an hourly time series or monthly totals. Additional facilities for viewing the simulation results are provided through the OutView and PlotView programs. [151]
7.13. Evaluation of the IES simulation
According to Shady A. et al, there are the following five selection criteria for building performance simulation tools (BPS) [158]: The Usability and Information Management (UIM) of interface, the Integration of Intelligent design Knowledge-Base (IIKB), the Accuracy of tools and Ability to simulate Detailed and Complex building Components (AADCC), the Interoperability of Building Modelling (IBM) and the Integration with Building Design Process (IBDP).
During the survey of the study (with 249 valid responses), ten tools were compared by architects, designers, architectures educators and students based on the usability and information management (UIM) of interface and the integration of intelligent design knowledge-base (IIKB). Figure 50 shows the comparison results between the ten tools where the IES VE came in the first category.
Figure 45: Ranking the ten tools [159] The results (Figure 45) showed that the responders characterized the IES VE as a user- friendly program but most important was the friendly graphical user interface (GUI). The results underline the importance of the default values and templates offered by the program.
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The facility of this program enables quick entry and supports a progression in thermal performance analysis from obtaining quick answers in early design to detailed analysis in later design phases.[160][161]
However, the research team of this project chose to use the IES VE due to the status of the program as market leader (related to the commercial design environment in UK). In addition, another important factor was the technical support of the program for the research team which developed the models and simulation method. [162]
The Crawley et al study [163] analysed the most important building simulation programs available in the market. The study recommended the IES VE as a simulation program that offers detailed modelling and analysis of fabric, glazing, system and gains performance.
Another research of the University of Edinburgh (Edinburgh School of Architecture and Landscape Architecture)[164] that used the IES simulation mentioned some restrictions/limitations related to the precision of the IES results. One of the problems reported by this study was the duration of the simulation analysis which was quite long and as a result the space needed to be reviewed. Subsequently, the accuracy of the achieved results was 90 percent. The availability of sustainable building materials such as green roofs, green walls and the materials made from reusable materials was another issue that arose, according to the study [164]. It would be difficult for a potential user to simulate these types of material since they are unavailable and therefore the result of the calculations may possibly be less accurate. The problem with the database of the materials was also an issue for this research which responded with simplifications of the construction without affecting the simulation results.
One more issue that was mentioned in Shady A. et al [165] was mostly due to lack of visual presentation and too much textual and tabular information in output results. Consequently, these types of results were not so suitable for supporting the decision-making process. [165]
Generally, the IES simulation program allows the input for HVAC, solar gains, shading, natural ventilation and dimming strategies. Moreover, it offers the option to simulate thermal comfort, make comparisons of results and check the compliance with LEED and SBEM. [165]The process adaptability of the program can be characterized as very good, as it is adapted to different design phases and design users, permitting flexibility in developing the model from early design to comprehensive design stages. [165]
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The accuracy of the IES can be characterized high as the APACHEsim, which is the core of thermal design and energy simulation, has been tested with ASHRAE Standard 140 (ANSI/ASHRAE Standard 140-200,ANSI/ASHRAE Standard 140-2004, ANSI/ASHRAE Standard 140-2007)[166]. The ASHRAE Standard 140 is referred to as the standard testing method for the evaluation of building energy analysis computer programs.
7.14. Conclusion
The IES simulation program structure provides the ability to analyse the building at different stages during its life. It is possible to mix and match the different IES tools in order to extract the best solution for the building design. This project takes into account the abilities of the program and focuses on solar radiation, climate, energy demand, renewable energy and carbon footprint, targeting the Zero energy building concept.
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Chapter 8: The case of singe family house
8.1. Introduction
The first building category was a single family house in Cyprus. In Chapter three -building types and characteristics (Table 11) the analysis shows that single family houses represent the main growing category of residential building; according to the most recent report of the Cyprus Statistical Service [47], the single family house represents 68% of the Cyprus existing building stock. [145] In that case the fact that the project is based on the transformation of the Cyprus building sector and the analysis of the single family house would have significant impact. The project concept was that the larger and more representative the category analysed by the project, is the greater the contribution and the impact of the results will be for the building sector. Thus the selection of the specific type of building was not random but was based on the project’s theoretical research and study. More specifically, this particular type of house, was chosen for two reasons; firstly, because this house type, the two storey family house, is the most common type in the Cyprus market [57][167] and secondly, because it was an actual existing house and the plans were provided by the same company that provided other information and building plans for the project. It is important to stress the fact that real case studies offered a more realistic approach to the problem as it was possible to discuss the development and the challenges of the project with the engineering team. The realistic approach to the problem and the use during the simulation of real values and plans provided more accurate results for the research.
During the simulation three different scenarios (the Base case study, the Refurbishment case study and the Best Practise case study) were developed in order to analyse the options related to construction materials, insulation, glazing, shading internal and external factors, HVAC systems, solar heating, photovoltaic systems, climate and microclimate effect, future weather predictions and building orientation.
The ground floor consisted of a living room, kitchen, storage room and one toilet, and the first floor had three bedrooms with a bathroom and toilet. The total floor area of the house was 246.71 m 2 and the total volume 859.08m3.(Figure 46-51)
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Figure 46: The case of single family house model in SketchUp
Figure 47: The case of single family house model in SketchUp-plan view
Figure 48: The case of single family house model in IES simulation software
Figure 49: The case of single family house model in IES simulation software-site view
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Figure 50: The case of single family house model in IES simulation software-ground floor plan view
Figure 51: The case of single family house model in IES simulation software-first floor plan view
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Table 34: Comparison of the three different case studies
Case study The Base case The The Best study Refurbishment Practise Examine Factors Improvement 1.Construction Materials and Insulation
2.External Insulation Impact
3.Windows and Glazing improvement
4.Window Insulation
5.External Shading
6.Internal Shading
7.HVAC system
8.Boiler –hot water
9.Solar hot water
10.Renewable Energy
11. Weather effect & Microclimate
12.Building Orientation
In order to achieve the target, the simulation analysis included 14 tests whereby the different parameters were simulated and analysed in detail.(Table 34) Each of these tests includes different scenarios for the parameter being examined concluding with the choice of the best scenario. The final target of each test was to minimize the energy consumption (total annual energy consumption and total annual energy consumption per floor) and the total carbon dioxide emissions of the building.
8.2. Single family house –Base case study (scenario 1)
The base case study included the construction materials as stated in the initial house plan. The construction did not include any insulation or energy measures that might possibly reduce the energy demand.
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Table 35 shows the simulation values for the family house in the base case scenario. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities. These values are representative of 75% of the house building stock of Cyprus and were applied before the accession of Cyprus into the European Union. [146][147]
Table 35:Family house(Base case study scenario) construction simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Single family house –Base case study
1 External Wall 0.34 0.48 0.06 0.12 1.53 2 Internal Partitions 0.09 0.70 0.12 0.12 1.52 3 Ground 0.72 0.62 0.04 0.12 1.07 contact/exposed floors 4 Internal 0.89 1.0 0.11 0.11 0.82 Ceilings/Floors 5 Roofs 0.84 0.75 0.03 0.11 1.29
a/a Description - Construction U-value Net U-value Outside surface inside surface windows thickness (m) (Glass (including frame) air-film resistance air-film construction only) (W/ m2K) (m2K/W) resistance (W/ m2K) (m2K/W)
6 External Windows 0.024 2.80 2.90 0.03 0.12
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
7 Heating Fan coil systems electricity 1.0 1.0 0.0
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
8 Cooling Cooling/ventilation electricity 2.0 2.0 2.2 mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
9 Hot water (DHW) was served electricity 0.5 10 60 by apacheHVAC
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The weather file data referred to Larnaca and was based on the meteorological station of Larnaca airport (Figure 52).
36
34
32
30
28
26
24
Temperature(°C) 22
20
18
16
14 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date: Jan to Dec
Max Dry-Bulb Temperature Max Wet-Bulb Temperature
Figure 52: The Annual max dry bulb and max wet bulb temperature The following assumptions were made during the simulation procedure:
1. The windows remained closed during the simulation. 2. The HVAC system was controlled by sensor in each room and thus the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling.
The input simulation data and the detailed simulation results of the single family house - base case study - can be found in Appendix G.
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8.2.1. Single family house-Results analysis
The results of the simulation of the single family house showed that the annual total energy consumption was 45.4 MWh and the annual total energy consumption per floor area was 184.1kWh/m2.
The simulation of the Base case study typically represents the “old building stock” in Cyprus which can be characterised as non-energy efficient compared to the other case studies. The calculation of the average U-value took into account the U-value of each element of the building construction. The construction U-value was 1.53 W/ m2K for the external wall, 1.5220 W/ m2K for internal partitions, 1.07 W/ m2K for Ground contact/exposed floors, 0.8242 W/ m2K for Internal Ceilings/Floors, 1,292 W/ m2K for roof and 2.9026 W/ m2K for glazing.
Table 36: U-values for the reference building in Cyprus[168]
Table 36 presents the U-values of reference building in Cyprus as they were presented in Implementation of the EPBD in Cyprus Status in November 2010. [146][147]
8.2.2. Single family house-Base case study results analysis
The comparison of the Base case study values with Reference building values (residential) showed that the percentage difference between the U-values for the roof was 102.5%, for the walls 112.5%, for floors 28%, for ground floors 49.5% and for windows 54.5%.
The total annual energy consumption was 41.1 MWh and the total annual energy consumption per floor area was 166.7kWh/m2. The peak load for heating was in January (3.9 MWh) and the peak load for Cooling was in August (3.2 MWh). The total heating energy demand was 15.6MWh per year and the total cooling demand was 12.9MWh per year.
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The total carbon dioxide emissions (yearly) were 36,734.4kgCO2 with the total system
emissions being 29,483.3kgCO2, the total light emissions being 2,910.6 kgCO2 and the total
equipment emissions being 4,340.6 kgCO2.
The simulation weather file is based on Larnaca where the mean dry-bulb temperature was in August (31.15oC) and the mean dry-bulb temperature was in January (15.45 oC). According to the weather data, the heating demand is high from November to March and the cooling demand is high from May to October. The heating demand from April to October that is presented in the graphs was due to the hot water demand (boilers energy). The lack of solar hot water systems increased the heating energy and at the same time influenced the heating demand in spring and summer. On the other hand, the cooling demand that was observed from November to March can be explained by the Cyprus weather. Even during the winter in Cyprus there is a lot of sunshine and in the Base case study the lack of shading in combination with windows being kept closed increased the indoor temperature. This is possible in cases where the glazing area is large and the solar radiation penetrates and affects the internal space. This small increase of internal temperature was detected by the cooling sensor which was set at 24 oC and the cooling system was set in operation.
The cooling and heating systems used electricity to cover the building’s needs. The peak system electricity load was high during the winter and summer and low during the spring and autumn. The wide fluctuations of the system power (electricity) were directly caused by the outdoor rise and fall of temperatures due to the lack of insulation in the building and operation profile for the HVAC system.
In general the results of the Base case study building confirmed the theoretical research concerns regarding the need for building improvement in Cyprus. The “old method” of construction was very far from the European energy targets for buildings. In addition, the Base case study revealed a further significant need for the building sector, the need for the refurbishment of “old” buildings.
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8.3. Single family house –Refurbishment case study (scenario 2)
The Refurbishment case study improved the energy performance of the house by applying energy efficient measures to the construction. However, in addition to the improvement of construction, better and more energy efficient systems (for heating and cooling) were used in order to improve the energy performance of the house. (Table 37)
Table 37:Family house(Refurbishment case scenario) construction simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Single family house –Refurbishment case study
1 External Wall 0.47 3.85 0.04 0.13 0.25 2 Internal Partitions 0.14 3.57 0.13 0.13 0.26 3 Ground 0.82 2.15 0.04 0.17 0.40 contact/exposed floors 4 Internal 0.99 3.50 0.10 0.10 0.27 Ceilings/Floors 5 Roofs 0.94 3.24 0.4 0.10 0.29
a/a Description - Construction U-value Net U-value Outside surface inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W)
6 External Windows 0.024 2.65 2.74 0.04 0.13
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
7 Heating fan coil system Electricity 2.50 2.00 0.5
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
8 Cooling Cooling/ventilatio electricity 2.5 2.5 2.6 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
9 Hot water (DHW) was electricity 0.5 10 60 served by apacheHVAC
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Table 37 shows the technical characteristics of the construction materials (construction layers outside to inside) and simulation values for the case study of the family house under refurbishment. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities; they are representative of 20% of the house building stock of Cyprus and have been applied since the accession of Cyprus to the European Union. [146][147]
The following assumptions were made during the simulation procedure:
1. The windows remain closed during the simulation. 2. The HVAC system was controlled by sensor in each room and thus the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling.
The input simulation data and the detailed simulation results of the single family house - Refurbishment case study can be found in Appendix G.
8.3.1. Single family house-Refurbishment case study results analysis
The Refurbishment case study was based on the need for issues such as insulation materials and energy efficient measures to be carefully studied. The target of this case study was the energy improvement of the house (old construction) with essential and minimal changes.
The calculation of the average U-value took into account the U-value of each element of the building construction. The construction U-value for the external wall was 0.25 W/ m2K, it was 0.26 W/ m2K for internal partitions, 0.40 W/ m2K for ground contact/exposed floors, 0.27 W/ m2K for internal ceilings/Floors, 0.29 W/ m2K for roof and 2.74 W/ m2K for glazing. The insulation improvement resulted in better energy performance of the building. The comparison between the U-values of the reference building and the Refurbish case study showed that U values of the Refurbishment case study were lower than the requirements of Implementation of the EPBD in Cyprus Status in November 2010. The improvement of U- values compared to the Base case study was 83.7% for the external walls, 82.4 for internal partitions, 64.5% for ground/exposed floors, 67.5% for internal ceiling/floor, 74.3 % for roof and 4.33% for glazing (windows).
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In addition, the Refurbishment case study also included systems improvements. The “old” HVAC systems were replaced with newer energy efficient systems and energy demand for heating and cooling decreased as a result of this. Compared with the Base case study the improvement was 66.7% for the cooling system and 150% for the heating system.
The total annual energy consumption was 27.5 MWh and the total annual energy consumption per floor area was 111.6kWh/m2. The peak load for heating was in January (1.5 MWh) and the peak load for cooling was in August (1.0 MWh). The total heating energy demand was 10.7 MWh per year and the total cooling demand was 4.6 MWh per year. The total carbon dioxide emissions (annually) were 25,432.6kgCO2 where the total system
emissions were 18,137.5kgCO2, the light total emissions 2,927.6kgCO2 and the equipment
total emissions 4,367.5kgCO2. The comparison between the Base case study and the Refurbishment case study showed that the improvements create an annual energy reduction of 33.1% and a reduction of 33.0% on a total annual Energy Consumption per Floor Area.
In the simulation weather file based on Larnaca, the mean dry-bulb temperature was in August (31.15oC) and the mean dry-bulb temperature was in February (15.45 oC). According to the weather data, the heating demand is high from mid-November to mid-March and the cooling demand is high between May and November. The decreased (almost to zero) heating demand from May until mid-November is due to the use of solar panels for hot water and the use of operation profiles for the HVAC systems. The slight increase in cooling for October and November was due to the increase of internal temperature because of sun radiation. The insulation of the building contributed negatively to this as the insulation measures aimed to maintain the indoor temperature and as a result there was a rise in the demand for cooling. However, the general profile of cooling demand presented a 62.02% decrease which was highly significant. Maintaining constant temperatures during the winter and summer was an issue for the project but the main target was the reduction of energy and not the optimization of cooling or heating demand. Compared to the main target of the research, the project can be regarded as successful at this stage.
The systems, cooling and heating, used electricity to cover the building’s needs. The peak system electricity load was high during the winter and summer and low during the spring and autumn. Compared with the Base case study, the fluctuations of the system power (electricity) were not so extreme due to the improved operation of the systems and the better response to the outdoor changes.
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8.4. Single family house –Best Practice case study (New buildings)
The Best Practice case study (New buildings) is in compliance with the new construction and energy efficiency regulations. In addition, all HVAC systems were based on new technological systems that afforded lower energy consumption for the building’s needs. This case study is based mainly on new building construction where the new energy regulations are obligatory.
Table 38 shows the technical characteristics of the construction materials (construction layers outside to inside) and simulation values for the scenario of the family house under refurbishment. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities. These values are representative of the under construction houses and future house building stock of Cyprus and are currently applied in some building cases. [146][147]
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Table 38:Family house(Best Practice case scenario) construction simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Single family house – Best Practise case study
1 External Wall 0.46 6.44 0.04 0.13 0.15 2 Internal Partitions 0.19 6.76 0.13 0.13 0.14 3 Ground 0.87 6.03 0.04 0.17 0.15 contact/exposed floors 4 Internal 0.86 6.18 0.10 0.10 0.16 Ceilings/Floors 5 Roofs 0.76 7.68 0.04 0.10 0.12
a/a Description - Construction U-value Net U-value Outside surface inside windows thickness (m) (Glass (including frame) air-film surface air- construction only) (W/ m2K) resistance film (W/ m2K) (m2K/W) resistance (m2K/W)
6 External Windows 0.038 1.48 1.80 0.04 0.13
a/a Description - Type of system Fuel Seasonal efficiency Sensible Heat heating /cooling Coefficient of recovery systems Performance (SCoP kW/kW)
7 Heating fan coil Electricity 3.50 4.00 1.00 system
a/a Description - Type of system Fuel Nominal effective Seasonal Energy System heating /cooling exchange rate Efficiency Ratio Seasonal systems (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
8 Cooling Cooling/ventilat electricity 3.50 3.50 4.00 ion mechanism Air conditioning
a/a Description - Type of system Fuel Boiler delivery Mean Cold Hot water water boiler efficiency water inlet supply temperature temperature (oC) set (oC)
9 Hot water (DHW) was electricity 1.0 10 60 served by apacheHVAC
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The following assumptions have been made during the simulation procedure:
1. The windows remain closed during the simulation. 2. The HVAC system was controlled by sensor in each room and thus the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling.
The input simulation data and the detail simulation results of the single family house - Best Practice case study can be found in Appendix G.
8.4.1. Renewable energy-Photovoltaic systems
As the aim of the Best Practice case study is to create a Zero Energy building, the installation of renewable energy systems on the building’s roof was the best option for minimizing or eliminating electricity demand. As this case study used the available insulation materials, construction methods and energy efficient systems to minimize the energy demand of the house, the next step was the introduction of photovoltaic systems in order to cover the house energy needs.
Cyprus has high solar potential since there is high solar radiation and sunshine throughout the year. According to the Cyprus National Energy Efficiency Action Plan for Renewable Energy [147][148] the use of photovoltaic systems for the generation of electricity is one of the most effective ways of utilising solar energy in Cyprus. Moreover, the Ministry of Agriculture, National Resources and Environment and the Ministry of Commerce, Industry and Tourism reports [149][150] refer to the high solar potential with mean daily sunshine from 9.8 to 14.5 hours in contrast with the low wind potential (some areas with mean wind velocity 5-6m/s, and few areas with 7m/s)(Figure 53). Hence the theoretical research of the project showed that the adoption of photovoltaic systems is the fastest way to transform the building market, reach the Cyprus 2020 energy targets and achieve the goal of zero energy buildings. That was the main reason the project chose the development of photovoltaic systems as a renewable option.
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Figure 53: Solar collector and annual mean wind velocity [150] The optimization procedure of a photovoltaics area results in an energy self-sufficient house where the energy demand is covered by the photovoltaic installation on the roof. Moreover, the minimum PV area created surplus energy that can be returned into the grid. To be precise, the installation of 78m2 of monocrystalline silicon photovoltaic panels returned 0.6 MWh per year surplus of energy (Figure 54).
Figure 54: The photovoltaics system installation settings
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13 12.5 12 11.5 11 10.5 10 9.5 9 8.5 8 7.5 7 6.5 6 5.5 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 -0.5
Systems Energy (MWh) Energy Systems -1 -1.5 -2 -2.5 -3 -3.5 -4 -4.5 -5 Test 1 Test 2 Test 3 Test 4 Test 5 Test 6 Test 7 Total Yearly Energy 12.7 -2.9 0.9 -0.1 -2.1 -4 -0.6 Consumption MWh
Figure 55: Area Optimization of the PV systems on the house roof.
Table 39: Photovoltaic systems input data
Tests PV type PV module Reference PV area Total yearly energy nominal irradiance for m2 consumption of the efficiency NOCT (W/m2) house (MWh) Test 1 Monocrystalline - - - 12.7 silicon Test 2 Monocrystalline 0.13 800 108 -2.9 silicon Test 3 Monocrystalline 0.13 800 81 0.9 silicon Test 4 Monocrystalline 0.13 800 88 -0.1 silicon Test 5 Monocrystalline 0.15 1000 88 -2.1 silicon Test 6 Monocrystalline 0.17 1000 88 -4 silicon Test 7 Monocrystalline 0.17 1000 78 -0.6 silicon
It should be mentioned that all the values used by the project for the simulation procedure were not taken randomly but were a result of research and collaboration with the Energy Service of the Ministry of Commerce, Industry and Tourism, which has the overall responsibility for Energy in Cyprus. [151]
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8.4.2. Orientation of the Best Practice case study
The impact of building orientation was studied during this project. The orientation of a building has a significant impact on building performance, as the most advantageous orientation allows the capture of free heat in winter and repels the heat in summer. Moreover, the optimal orientation for maximum energy efficiency of the house is achieved when the long axis of the building runs east to west (Figure 56).
Figure 56: House orientation and sun path during the summer and winter.
All the simulation parameters remained the same (construction, system parameters and weather file) except for the change of orientation of the house. The house was turned 90o and the main entrance of the house changed from south facing to west facing (Figure 57).
Figure 57: Initial and final orientation of the house
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The house was rotated 180o and the main entrance of the house changed from south facing to north facing (Figure 57).
Figure 58: Initial and final orientation of the house
The house was turned 270o from the initial orientation and the main entrance of the house changed from south facing to east facing (Figure 58).
3 2.8 2.6 2.4 2.2 2 1.8 1.6 South face 1.4 West face 1.2 North face 1 Systems Energy Systems Energy (MWh) 0.8 East face 0.6 0.4 0.2 0
Heating
Figure 59: Heating demand and orientation impact
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2.8 2.6 2.4 2.2 2 1.8
1.6 South face 1.4 West face 1.2 North face
Systems Energy Systems Energy (MWh) 1 0.8 East face 0.6 0.4 0.2 0
Cooling
Figure 60: Cooling demand and orientation impact
20.0% 18.0% 16.0% 14.0% 12.0% 10.0% 8.0%
Percentage Difference Percentage (%) 6.0% 4.0% 2.0% 0.0% South vs West South vs North South vs East Heating demand 4.2% 20.7% 17.9% Cooling demand 4.3% 0.0% 12.0%
Figure 61: Percentage Difference (%) of energy consumption between the different orientations
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Another factor affecting building energy performance was the orientation of the building. During the research development the building was simulated in different orientations in order to study how that particular factor impacts on energy consumption. The initial position of the building was south where the long axis of the building runs east to west. In first case the building was turned 90o clockwise, in second case 180o and in third case 270o.
The results of the different simulations showed that the best orientation, i.e. where the house was more energy efficient, was south facing (with the long axis of the building running east to west). The comparison between the south facing and west facing orientation showed that the heating demand for south was 4.2% lower than west and the cooling was 4.3%. The comparison between the south facing and the north facing orientation showed that the heating demand was 20.7% lower in south facing compared to north facing and the cooling was the same. The comparison between the south facing and east facing showed that the heating demand was 17.9% lower and the cooling was 12% lower than east facing. The general conclusion of this analysis is the fact that the correct orientation of the building contributes positively to the energy reduction of the building.
8.4.3. Single family house-Best Practice case study results analysis
The Best Practice case study represents the new construction of buildings according to the new European energy regulations, such as the Implementation of the EPBD in Cyprus. The Implementation of the EPBD in Cyprus was the first step of making thermal insulation a requirement in Cyprus buildings envelope. In addition, the EPBD set minimum energy performance requirements for new buildings, residential and commercial. The Best Practise case study was based on these standards for the purpose of developing the project but further additional measures were developed in order to achieve the primary target of zero energy building.
Table 40: U-value comparison between the Reference Building and the Best Practice case study
Exposed elements Reference building Best Practice case Reduction of U-value study U-value (W/ m2K) U-value (%) (W/ m2K) Roofs 0.64 0.12 81.2 Walls 0.72 0.15 79.2 Internal Partitions / 0.14 / Floors/ceilings 0.64 0.16 74.9 Ground floor 1.60 0.15 90.6 Windows 3.23 1.80 44.7
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The construction improvements of building elements in the Best Practice case study significantly reduced the U-values of the building while at the same time improving the building energy performance.
Furthermore, compared to Refurbishment and Base case studies, the Best Practice case study included further system improvements. This new more energy efficient system replaced the previous HVAC systems resulting in a decrease in the energy demand for heating and cooling. Compared to the Base case study the improvement was 133.3 % for the cooling system and 250% for the heating system. Compared to the Refurbishment case study the improvement was 40.0 % for both the cooling and the heating system. The systems efficiency had a significant impact on the reduction of energy needed to maintain comfortable indoor temperatures.
The total annual energy consumption was 12.7 MWh, the total annual energy consumption per floor area being 51.3 kWh/m2. The peak load for heating was in January (0.3 MWh) and the peak load for cooling was in August (0.5 MWh). The total heating energy demand was 2.5 MWh per year and the total cooling demand was 2.3 MWh per year. The Total carbon dioxide emissions (yearly) were 11,696.6kgCO2 while the total system emissions were
6,000.0kgCO2, the total light emissions 2,133.3kgCO2 and the total equipment emissions
3,563.3kgCO2. The comparison between the Base case study and the Best Practice case study showed that the improvements led to an annual energy reduction of 69.1% and a reduction on Total Yearly Energy Consumption per Floor Area of 66.2%. The comparison between the Refurbishment case study and the Best Practice case study showed that as a result of the improvements there was an annual energy reduction of 53.8% and a reduction of 54.0% in Total annual Energy Consumption per Floor Area.
In the simulation weather file based on Larnaca the mean dry-bulb temperature was in August (31.15 oC) and the mean dry-bulb temperature was in February (15.45 oC). According to the weather data, the heating demand is high from late November until the end of March and the cooling demand is high from May until November. The decrease (almost to zero) in heating demand from May to mid-November is due to the use of solar panels for hot water, improved boiler efficiency and the use of operation profiles for the HVAC systems.
The use of shading systems and operation profiles for the HVAC systems make a positive contribution to reduced energy use for cooling and heating. Sun penetration into indoor space
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at times when it was unnecessary was minimized by the use of shading systems (external shading system controlled by operation profiles).
The systems, both cooling and heating, used electricity in order to satisfy the building needs. The peak system electricity load was high in summer and low during the winter, spring and autumn. Due to the further improvements of the systems operation and better response to outdoor changes, the fluctuations of the system power (electricity) were less extreme in comparison with the Base and Refurbishment case studies. In general, the use of the system electricity fell significantly and therefore the house energy needs were easily satisfied through the use of renewable energy systems.
In addition, the Best Practice case study investigated the installation of photovoltaics systems on house roofs. The main goal was the transformation of buildings into zero energy buildings where building needs would be satisfied by means of locally renewable systems. The optimization procedure of PV area, PV module nominal efficiency and Reference irradiance for NOCT (W/m2) returned a Zero Energy Building where the 78m2 of photovoltaic system cover the house energy needs. Furthermore, the minimum PV area offers 0.6 MWh per year surplus of energy. The PV type was Monocrystalline silicon with PV module nominal efficiency 0.17 and the Reference irradiance for NOCT was 1000 W/m2.
The Best Practice case study in combination with renewable systems (photovoltaics system) showed that the goal of Zero Energy Building is achievable. The only aspect not included in this project was the cost of this solution since cost plays a vital role in any final decisions. However, the matter of the cost of this solution, zero energy buildings, needs detailed study in order to compare the investment with depreciation time. This subject was not relevant to this research as the goal was the achievement of zero energy building in a hot climate country.
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8.5. Comparison of the three case studies.
Table 41: Comparison of the three case studies
Parameters Base case Refurbishment Best practise case Comparison Comparison Comparison study (1) case study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%) Construction: External wall U-value (W/m2K) 1.53 0.25 0.15 83.7 90.2 40.0 Internal Partitions U-value (W/m2K) 1.48 0.26 0.14 82.4 90.5 46.1 Ground/Exposed Floors U-value 1.07 0.38 0.16 64.5 85.0 57.9 (W/m2K) Internal Ceiling/Floor U-value 0.83 0.27 0.16 67.5 80.7 40.7 (W/m2K) Roofs U-value (W/m2K) 1.13 0.29 0.13 74.3 88.5 55.1 Glazing U-value (W/m2K) 2.77 2.65 1.8 4.33 33.1 29.0 Heating system: Fuel Electricity Electricity Electricity - - - Seasonal Efficiency 1.0 2.5 3.5 150 250 40 SCoP kW/kW 1.0 2.0 4.0 100 300 100 Vent. heat recovery effectiveness 0.0 0.5 1.0 - - 100 Vent. Heat recovery return air temp. 0.0 21.0 oC 21.0 oC - - -
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Parameters Base case Refurbishment Best practise case Comparison Comparison Comparison study (1) case study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%)
Cooling systems: Mechanism Air Air conditioning Air conditioning - - - conditioning Fuel Electricity Electricity Electricity - - - Seasonal EER kW/kW 1.5 2.5 3.5 66.7 133.3 40 SSEER kW/kW 1.2 2.6 4.0 33.3 233.3 53.8 Heat rejection (% of rejected heat) 10 10 15 - 50 50 Hot Water: Served by ApacheHVAC boiler Yes Yes YES - - - DHW delivery efficiency 0.51 0.51 1.0 - 96.0 96.1 Mean cold water inlet temperature 10oC 10oC 10oC - - - Hot water supply temperature 60oC 60oC 60oC - - - Solar water system: Area m2 0.0 8 8 - - - Heat exchanger effectiveness 0.0 0.4 0.4 - - - Total Yearly Energy Consumption 41.1 MWh 27.5 MWh 12.7 MWh 33.1 69.1 53.8 Total Yearly Energy Consumption per 166.7 111.6 51.3 33.0 69.2 54.0 Floor Area kWh/m2 kWh/m 2 kWh/m 2 *Comparison between the Case studies and Percentage Change between the parameters
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4.4 4.2 4 3.8 3.6 3.4 3.2 3 2.8 2.6 2.4 2.2 2 1.8
Systems Energy (MWh) Energy Systems 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Base case study Refurbish case study Best practise case study
Figure 62: Monthly system energy comparison for the three case studies-Heating systems
100.0% 95.0% 90.0% 85.0% 80.0% 75.0% 70.0% 65.0% 60.0% 55.0% 50.0% 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% Percentage Reduction (%) ofMonthly Heating Energy Consumption 0.0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case study 61.5% 60.0% 55.2% 33.3% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 14.3% 57.1% Compare Base with Best Practise case study 92.3% 91.4% 89.7% 77.8% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 71.4% 89.3% Compare Refurbish with Best Practise case 80.0% 78.6% 76.9% 66.7% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 66.7% 75.0% study
Figure 63: Percentage Reduction (%) of Monthly Heating Energy Consumption
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3.6 3.4 3.2 3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4
Systems Energy Systems Energy (MWh) 1.2 1 0.8 0.6 0.4 0.2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Base case study Refurbish case study Best practise case study
Figure 64: Monthly system energy comparison for the three case studies-Cooling systems
100.0% 95.0% 90.0% 85.0% 80.0% 75.0% 70.0% 65.0% 60.0% 55.0% 50.0% 45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% Percentage Reduction (%) ofMonthly Cooling Energy Consumption 10.0% 5.0% 0.0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case study 50.0% 0.0% 50.0% 50.0% 50.0% 66.7% 68.8% 71.4% 65.0% 33.3% 66.7% 50.0% Compare Base with Best Practise case study 100.0%100.0%100.0% 50.0% 66.7% 83.3% 84.4% 85.7% 85.0% 66.7% 66.7% 50.0% Compare Refurbish with Best Practise case 100.0%100.0%100.0% 0.0% 33.3% 50.0% 50.0% 50.0% 57.1% 50.0% 0.0% 0.0% study
Figure 65: Percentage Reduction (%) of Monthly Cooling Energy Consumption
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Generally, comparison between these case studies showed that the Best Practice case study achieved the greater reductions of energy compared with the Refurbishment case study. Comparing the Best Practice study with the Refurbishment case study, the higher reduction in heating energy use occurred in January (80%) and the lower in November (66.7%). The higher reduction in energy for cooling was 50% and related to the summer period (from June to August) when there is the actual need for cooling. However, the scenario of refurbishment cannot be ignored as many buildings were already constructed before the new energy regulations. There is a need for a methodology development for buildings refurbishment in order to be more energy efficient and closer to Low energy building. The refurbishment of a building is a key issue as there are sometimes many limitations compared with the available solutions, techniques and materials.
8.6. Weather- Microclimate Effect
During the project development the weather and microclimate effect were analysed in order to study their impact on the energy consumption of the house. The Best Practice case study house was simulated with different Locations-towns of Cyprus and with a different weather file each time. The simulation weather files were a result of the weather research conducted by the project and analysed in the previous chapter (chapter 6). The results of Chapter 6 indicate that the climatological zone where the house is built plays a vital role in terms of weather conditions and architectural style and hence plays a crucial role in energy use.
By keeping all other factors constant and changing only the simulation weather file, any increase or decrease of system energy (heating and cooling) was due to the microclimate differences between the towns. Figures 66 and 67 show the results of the simulation tests. There are significant differences between the Cyprus towns that cannot be ignored if the possible estimation of the building energy demand is to be as accurate as possible. The graphs show that a simulation based in only one town may possibly underestimate the cooling or the heating demand of the house.
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0.9 0.85 0.8 0.75 0.7 0.65 0.6 0.55 0.5 0.45 0.4 0.35 System Energy Energy System (MWh) 0.3 0.25 0.2 0.15 0.1 0.05 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca weather file-IES data 0.3 0.3 0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.3 Limassol weather file 1997-2008 0.4 0.4 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Limassol weather file 2000-2009 0.5 0.4 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.4 0.4 Nicosia weather file 1997-2008 0.6 0.5 0.3 0.3 0.1 0.1 0.1 0.1 0.1 0.2 0.5 0.6 Nicosia weather file 2000-2009 0.7 0.7 0.6 0.4 0.1 0.1 0.1 0.1 0.1 0.3 0.6 0.8
Figure 66: Heating demand and microclimate effect
0.7 0.65 0.6 0.55 0.5 0.45 0.4 0.35 0.3 System Energy Energy System (MWh) 0.25 0.2 0.15 0.1 0.05 5E-16 -0.05 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca weather file-IES data 0 0 0 0.1 0.2 0.3 0.5 0.5 0.3 0.2 0.1 0.1 Limassol weather file 1997-2008 0 0 0.1 0.1 0.3 0.4 0.6 0.6 0.4 0.3 0.1 0.1 Limassol weather file 2000-2009 0 0 0.1 0.1 0.4 0.5 0.7 0.7 0.5 0.2 0.1 0.1 Nicosia weather file 1997-2008 0 0 0.1 0.1 0.2 0.3 0.5 0.5 0.3 0.2 0.1 0.1 Nicosia weather file 2000-2009 0 0 0.1 0.1 0.1 0.4 0.4 0.4 0.2 0.1 0.1 0
Figure 67: Cooling demand and microclimate effect
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8.6.1. Future Weather files
Based on the simulation weather files created during the development of the project, future weather files were constructed in order to predict the performance of the Best Practice case study- zero energy building at a future time.
The future simulation files concerned the years 2020, 2050 and 2080. The following graphs are useful tools that may enable engineers to predict and, where possible, change parameters that can be vital for future building performance.
The future weather analysis is based on the Best Practice case study building and used three future weather files (2020, 2050 and 2080) for each town. In this way the project studies the possible impacts on heating and cooling demands of the proposed zero energy building (Best Practice case study building) in three different locations (towns) of Cyprus.
8.6.2. Future Weather files- Limassol town
0.36 0.34 0.32 0.3 0.28 0.26 0.24 0.22 0.2 0.18 0.16 0.14 0.12
Systems Energy Systems Energy (MWh) 0.1 0.08 0.06 0.04 0.02 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Limassol 2009 0.3 0.3 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Limassol 2020 0.3 0.3 0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Limassol 2050 0.3 0.3 0.3 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Limassol 2080 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2
Figure 68: Heating demand and Future weather files
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0.8 0.76 0.72 0.68 0.64 0.6 0.56 0.52 0.48 0.44 0.4 0.36 0.32 0.28 0.24 Systems Energy Systems Energy (MWh) 0.2 0.16 0.12 0.08 0.04 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Limassol 2009 0 0 0 0.1 0.2 0.3 0.5 0.5 0.3 0.2 0.1 0.1 Limassol 2020 0 0 0 0.1 0.2 0.5 0.6 0.6 0.4 0.3 0.3 0.1 Limassol 2050 0 0 0 0.1 0.2 0.5 0.7 0.7 0.4 0.3 0.3 0.1 Limassol 2080 0 0 0.1 0.1 0.3 0.6 0.8 0.8 0.6 0.4 0.4 0.1
Figure 69: Cooling demand and microclimate effect 8.6.3. Future Weather files- Nicosia town
0.72 0.68 0.64 0.6 0.56 0.52 0.48 0.44 0.4 0.36 0.32 0.28 0.24 Systems Energy (MWh) 0.2 0.16 0.12 0.08 0.04 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Nicosia 2009 0.5 0.5 0.5 0.4 0.1 0.1 0.1 0.1 0.2 0.3 0.2 0.5 Nicosia 2020 0.6 0.6 0.7 0.5 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.7 Nicosia 2050 0.6 0.6 0.7 0.4 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.6 Nicosia 2080 0.5 0.5 0.6 0.4 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.5
Figure 70: Nicosia Heating demand and Future weather files
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0.52 0.5 0.48 0.46 0.44 0.42 0.4 0.38 0.36 0.34 0.32 0.3 0.28 0.26 0.24 0.22 0.2 0.18 0.16
Systems Energy (MWh) 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Nicosia 2009 0 0 0 0 0.1 0.2 0.3 0.3 0.2 0.1 0.1 0 Nicosia 2020 0 0 0 0 0.1 0.2 0.4 0.4 0.2 0.1 0.1 0 Nicosia 2050 0 0 0 0 0.1 0.3 0.4 0.4 0.2 0.1 0.1 0 Nicosia 2080 0 0 0 0.1 0.2 0.4 0.5 0.5 0.3 0.1 0.1 0
Figure 71: Nicosia cooling demand and microclimate effect 8.6.4. Future Weather files- Larnaca town
0.31 0.3 0.29 0.28 0.27 0.26 0.25 0.24 0.23 0.22 0.21 0.2 0.19 0.18 0.17 0.16 0.15 0.14 0.13 0.12 0.11 0.1 0.09 Systems Energy Systems Energy (MWh) 0.08 0.07 0.06 0.05 0.04 0.03 0.02 0.01 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca 2009 0.2 0.2 0.15 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Larnaca 2020 0.3 0.3 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Larnaca 2050 0.3 0.3 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 Larnaca 2080 0.25 0.25 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2
Figure 72: Larnaca Heating demand and Future weather files
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0.84 0.8 0.76 0.72 0.68 0.64 0.6 0.56 0.52 0.48 0.44 0.4 0.36 0.32 0.28 0.24
Systems Energy Systems Energy (MWh) 0.2 0.16 0.12 0.08 0.04 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca 2009 0 0 0 0.1 0.2 0.3 0.5 0.5 0.3 0.2 0.1 0.1 Larnaca 2020 0 0 0 0.1 0.2 0.3 0.5 0.6 0.4 0.2 0.1 0.1 Larnaca 2050 0 0 0.1 0.1 0.2 0.5 0.6 0.6 0.5 0.2 0.1 0.1 Larnaca 2080 0 0 0.1 0.1 0.3 0.5 0.7 0.8 0.6 0.3 0.2 0.1
Figure 73: Larnaca cooling demand and microclimate effect 8.6.5. Weather data results
The weather and microclimate impact on buildings’ energy consumption was a central issue for this project and there is an extensive analysis of the weather effect in Chapter 6 with the importance of the different weather files being stressed. As previously mentioned, weather conditions (exemplar building) play a crucial role in the energy behaviour of the building. The project weather results and conclusions are confirmed in another study: " The energy behaviour of the building stock in Cyprus in view of the Energy Performance of Buildings Directive implementation" [152] and by the Cyprus Energy Services, which recognise four major climatological zones (Figure 74): namely, coastal, low land, semi-mountainous and mountainous areas. Hence the building simulation with the new weather data files covering the three main zones is closer to reality and is more accurate than a simulation using only the initial IES weather data file (only zone 1 would be covered in the IES weather data file).
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Figure 74: Map of Cyprus showing the four major climatological zones [152] The development of weather data files for three different towns of Cyprus and the simulation of the Best case study under the different weather simulation files reveal valuable information. Comparison of the results indicated that heating demand is higher inland compared to the seaside towns of Larnaca and Limassol. An important issue of this comparison was the fact that weather data for the same town returned different results. This is due to the geomorphological differences between the two towns Larnaca and Limassol; Limassol combines two zones: coastal and semi-mountainous, whereas Larnaca is clearly a coastal area. As for cooling demand, higher values were presented in Limassol and lower values in Nicosia so it appears that coastal towns need more cooling during the summer than is the case with inland Nicosia. The results are strongly related with Chapter 6 where analysis indicates that the coastal town had a combination of higher temperatures and humidity. This creates more problems and unpleasant conditions for people living there with the use of air- conditioning in some cases being mandatory. Nicosia, in contrast, belongs to the semi- mountainous zone where the temperature and the humidity levels, according to Chapter 6 weather data analysis, are lower than in Limassol.
The most striking aspect of the weather analysis was the fact that there were significant differences that could not be ignored between the towns and in general between the inland and the coastal towns. The IES simulation program offered only one simulation file for Cyprus, the Larnaca weather simulation file, with which it was not possible to cover the microclimate conditions of the whole island. Simulations based only on this weather file would possibly underestimate or overestimate the cooling and heating demand.
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Thus, the project reveals the need for updated weather simulation files with individual weather simulation files for each town. The influence of the weather is a very important factor as it affects indoor conditions of the house and the operation of its systems.
Another aspect of the weather analysis was the attempt at future estimations of building performance for 2020, 2050 and 2080. The future weather for Limassol predicts that the winters will be colder for 2020 and 2050 which means an increase in heating demand and the summers will be hotter compared to 2009 data. The heating demand of 2080 is predicted to decrease which means that possibly the winter will be warmer by that time. In addition in 2080 the cooling demand was higher than the previous year which means that 2080 will present higher temperatures in general. For Nicosia a trend of increasing heating demand between 2020 and 2050 is predicted from December to January, and for 2080 the heating demand decreased compared with previous years. On the other hand, the cooling demand increased during the summer period (from June to August) and the hottest period seems to be 2080 where the cooling will be higher compared to the previous years. Larnaca’s future weather files showed that the winters of 2020 and 2050 will be colder compared to 2009 and 2080. The latter will have a warmer winter and a warmer summer compared with the previous years. The cooling demand for 2020 will be the same as 2009 from April to July after which there will be a tendency of increase. Generally there will be an increasing tendency for cooling especially for 2080.
The general picture of the analysis showed that the weather will change in the future. However, the estimates cannot be precise due to the many uncertainties of the weather models and the unpredictable factors that influence changes in weather. However, it was essential as well as interesting to explore the future impact of weather on energy consumption of the house. The estimations could possibly enable engineers to predict potential improvements in the building envelope in order to perform better in future weather conditions.
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8.7. Conclusion
The extensive analysis of the single family house and the target to transform this kind of building stock into zero energy buildings show that the target is achievable and Cyprus can make the difference.
The fact that more than 80% of the houses - single family houses - in Cyprus do not have insulation in their external walls creates an essential need for refurbishment of the old building stock so that a significant reduction of energy may be achieved. [152] The refurbishment case study shows that reductions of 33% on total yearly energy consumption could be achieved compared to the base case study scenario which represents the current situation of the majority of houses.
However, the most important step for Cyprus is the complete transformation of the single family house by adapting the Best Practice case study-representative of the new and future buildings and target the adoption of the zero energy concept. In that case, a reduction of 69.1% in total yearly energy consumption could be achieved compared to the base case study scenario and 53.8% in total yearly energy consumption could be achieved compared to the refurbishment case study scenario. In both cases there is a significant decrease in total annual energy consumption that will help Cyprus to achieve its national energy targets.
The results indicate that there are high priority technologies which the Cyprus Building Authorities need to recognize and promote in order to achieve the zero energy office building. From the construction phase onwards, it is essential for new ways of building and the use of new materials to be introduced in order to improve the energy performance of the building. These materials in combination with appropriate design will reduce the walls, roofs and windows u-value and will increase the energy savings of the building. Moreover, the use of new technology will have a vital impact on the buildings’ energy as it will be possible to take full advantage of the Cyprus sunny weather. The use of the photovoltaic systems, which contributes directly to the reduction of electricity consumption, in combination with solar energy for cooling and heating is the key to the transformation of office buildings into zero energy buildings.
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The research results highlight that the building orientation, solar collectors, day-lighting, triple-glazed operable windows with individual sunshades, external insulation and the use of building energy management systems are some of the key features for making zero energy building possible.
The project results highlight the need for a more powerful and methodical legislative framework that will transform the building sector and reach the National European targets of 2020. However, such a framework will need the backing of suitable economic motivation and appropriate support structures as well as the implementation of a training/information program for those who are involved in building construction.
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Chapter 9: Commercial Building-Office building case study.
9.1. Introduction
The office building (case study building) is intended to be representative of commercial buildings built to current standards and this section focuses on the new type of commercial building (new design and materials). The simulation analysis is based on three different case studies: the Base case study, the Refurbishment case study and the Best Practice case study with each case study representing three chronologically different periods of Cyprus building stock. The Base case study represents the period when there were no energy regulations for buildings in Cyprus whereas the Refurbishment case study represents the transitional period from the “old construction” to the new types of building. The building stock that was constructed before the introduction of energy regulations in Cyprus will need refurbishment in order to comply with the energy standards of the EPBD.[168] This refurbishment was investigated in the Refurbishment case study in order to propose specific energy measures for reducing the building’s energy demand. The Best Practise case study represents the new type of building and the installation of renewable energy systems aims to transform this type of building into the zero energy building. .
Due to Cyprus’ strategic position, the island has developed into a centre for trade and international business and the fact that Cyprus is now an international business centre has created new previously non-existent demands for the building market. [175] The need for contemporary design and high technology office buildings leads the transformation of the market, but the problem of the high energy demands was never seriously considered. Now, however, an issue for the building market is the development of tall high technology buildings based on the concept of zero energy building. As office buildings play an important role in the Cyprus economy and its future development, the second building category to be analysed and simulated was the Commercial building – an office building, as shown in Figure 75. The target was not only to develop a zero energy building as a new building project, but also to explore the transformation of existing office building stock into zero energy buildings. The development of this idea by the Cyprus authorities and building market will contribute immediately to the target for lower energy consumption in buildings. The goal of the project/research results was to contribute knowledge and influence the building market and authorities.
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Figure 75: The original office buildings plans in AutoCAD software-3D and plan view
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The office building chosen for the simulation represents the current trend of the Cyprus building market and is an 8-storey building with, two reception rooms, a main entrance, and two offices on each floor. The total floor area of the building is 3645.09m2 and the total volume is 13243.99m3. The ground floor of the building has 14 shops, each of which comprises two separate areas, the main store and the toilet.(Figure 75)
The objective of the simulation work was to minimize energy consumption (total yearly energy consumption and total yearly energy consumption per floor) of the building as well as the total carbon dioxide emissions. To achieve this, the simulation analysis involved 14 tests where the different parameters were simulated and analysed in detail. Each of these tests involved different scenarios for the parameter under scrutiny with the best scenario being chosen.
9.2. Cyprus Reference Building
The Implementation of the EPBD in Cyprus Status in November 2010 [168] set the minimum energy performance requirements for new buildings and for all buildings above 1000m2 that are undergoing refurbishment.
Table 42: The minimum energy performance requirements-2007 regulations [168]
The energy performance requirements changed in 2009 after the issue of a new Ministerial Order where the maximum U-values for the building envelope remained the same but the requirements became stricter since the building was regarded as one entity (Table 43).
Table 43: New minimum energy requirements -2009 regulations [168]
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Table 44: Predetermined U values for the reference building [168]
The development of the Office building project was based on the U-values as shown in Table 44 in order to compare the simulation results. Moreover, the project took further steps and improved the recommended U-values with the aim of achieving the Zero Energy Building.
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9.3. Office Building –Base case study
The technical characteristics of the construction materials (construction layers outside to inside) are given in Table 45.
Table 45: Office building (Base case study scenario) construction input simulation values
a/ Description - Construction R-value Outside surface Inside surface U-value a construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Office building –Base case study
1 External Wall 0.29 0.52 0.04 0.13 1.44 2 Internal Partitions 0.09 0.41 0.13 0.13 1.48 3 Ground contact/exposed 0.75 0.14 0.04 0.17 1.11 floors 4 Ground contact/exposed 0.37 0.52 0.04 0.17 1.37 floors to air 5 Internal Ceilings/Floors 0.64 0.93 0.10 0.10 0.88 6 Roofs 0.59 0.75 0.04 0.10 1.12
a/ Description - windows Construction U-value Net U-value Outside surface inside surface a construction thickness (m) (Glass only) (including frame) air-film resistance air-film (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows Store 0.01 5.57 5.28 0.04 0.13 Windows External Windows 0.02 2.82 2.81 0.04 0.13 Office Windows
a/ Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery a /cooling systems Coefficient of Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 1.0 1.0 0.0
a/ Description - heating Type of system Fuel Nominal effective Seasonal Energy System a /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 2.0 2.0 2.2 n mechanism Air conditioning
a/ Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water a boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 0.5 10 60 served by apacheHVAC
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Table 45 shows the simulation values for the office building under the Base case scenario. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities. [168][169]
The weather file data referred to Larnaca and was based on the meteorological station of Larnaca airport (Figure 76 and Table 46).
32
30
28
26
24
22
20 Temperature(°C)
18
16
14
12 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Date: Jan to Dec
Max Dry-Bulb Temperature Max Wet-Bulb Temperature
Figure 76: The annual max dry bulb and max wet bulb temperature
Table 46: Max dry-bulb temperature and max wet-bulb temperature
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During the simulation procedure the following assumptions were made:
1. The windows remained closed during the simulation. 2. The HVAC system was controlled by a sensor in each room and so the internal temperature remained constant at 21o C for heating and 24o C for cooling.
The input simulation data and the detailed simulation results of the single family house - base case study can be found in Appendix H.
9.3.1. Office Building -Base case study results analysis
As shown in Table 45, the base case study U-values were greater than the U-values of the reference residential building indicating that the building did not adopt the new energy regulations. The percentage difference for external wall the U-value was 66.57%, for internal partitions the U-value was 68.54%, for ground contact/exposed floors the U-value was 36.42 %, for ground contact/exposed floors expose to air the U-value was 72.72%, for internal ceilings/floors the U-value was 31.96%, for roof the U-value was 54.85% , for external store windows the Net U-value (including frame) was 48,18% and for external office windows the net U-value (including frame) was 14.13%. Only in two elements, ground contact/exposed floors and external office window, was the U-value of the base case construction better than the reference building. The percentage difference between the U-values of the base case study and the reference building showed the gap between the “old” and the new methods of construction that set new standards in building construction. The gap between the old and new requirements can be reduced with refurbishment of old building stock.
The total annual energy consumption was 680.2 MWh and the total annual energy consumption per floor area was 186.6 kWh/m2. The peak load for heating was in January (13.3 MWh) and the peak load for Cooling was in August (34.7 MWh).
The total heating energy demand was 45.8 MWh per year and the total cooling demand was
199.9 MWh per year. The Total carbon dioxide emissions (yearly) were 618.371.3kgCO2
where the total system emissions were 369,351.8kgCO2, the light total emissions were
170,109.7kgCO2 and the equipment total emissions were 78,909.7kgCO2. The simulation weather file was based on Larnaca where the mean dry-bulb temperature was in August (31.15o C) and the mean dry-bulb temperature was in January (15.45 o C).
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According to the weather data, the heating demand is high from November to March and the cooling demand is high from May to the end of October. The heating demand shown in graphs from April to October was due to the hot water demand (boilers energy). The lack of solar hot water systems increased the heating energy demand and at the same time it affected the heating demand in spring and summer. On the other hand, the cooling demand observed from November to March can be explained by the Cyprus weather. Even in winter in Cyprus there is a lot of sunshine and in the Base case study the lack of shading in combination with windows kept closed increased the indoor temperature. This may occur in cases where the glazing area is large and the solar radiation penetrates and affects the internal space. This small increase in internal temperature was detected by the cooling sensor which was set at 24 o C and the cooling system was set in operation.
The cooling and heating systems used electricity to cover the building’s needs. The peak system electricity load was high during winter and summer and low during spring and autumn. The wide fluctuations of the system power (electricity) were directly affected by outdoor rising and falling temperatures due to the lack of insulation measures.
In general, the results of the base case study building confirmed the theoretical research concerns about the need for building improvement in Cyprus. Not only did the “old method” of construction fail to meet the European energy targets for buildings but the Base case study also revealed another imperative building sector necessity, i.e. the urgent need to refurbish “old” buildings.
9.4. Office Building –Refurbishment case study
The Refurbishment case study improved the energy performance of the Office Building by applying energy efficient measures to the construction and in addition better and energy efficient systems (for heating and cooling) were also used.
The technical characteristics of the construction materials (construction layers outside to inside) are given in Table 47
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Table 47: Office building (Refurbishment case study scenario) construction input simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Office building –Refurbishment case study
1 External Wall 0.33 1.34 0.04 0.13 0.46 2 Internal Partitions 0.09 1.92 0.13 0.13 0.46 3 Ground 0.88 0.22 0.04 0.17 0.33 contact/exposed floors 4 Ground 0.36 2.19 0.04 0.17 0.42 contact/exposed floors to air 5 Internal 0.64 1.61 0.10 0.10 0.55 Ceilings/Floors 6 Roofs 0.62 2.34 0.04 0.10 0.40
a/a Description - Construction U-value Net U-value Outside surface Inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows 0.04 2.54 2.57 0.04 0.13 Store Windows External Windows 0.028 2.62 2.63 0.04 0.13 Office Windows
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 2.5 2.0 0.5
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 2.5 2.5 2.6 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 0.5 10 60 served by apacheHVAC Solar panels Panels 12m2 sun exchanger 10 60 effectiveness 0.40
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Table 47 shows the technical characteristics of the construction materials (construction layers outside to inside) and simulation values for the office building in the Refurbishment case scenario. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities.
The following assumptions were made during the simulation procedure:
1. The windows remained closed during the simulation. 2. The HVAC system was controlled by sensor in each room and thus the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling.
The input simulation data and the detailed simulation results of the Office building - Refurbishment case study can be found in Appendix H.
9.4.1. Office Building -Refurbishment case study results analysis
As previously mentioned, the refurbishment case study was created in order to investigate the gap between the new and old building stock (buildings constructed without any energy regulations) and to propose a solution for these buildings. The main aim of this case study was the energy reduction of the building and operational improvement with minimal changes to the building.
The calculation of the average U-value took into account the U-value of each element of the building construction. The construction U-value for the external wall was 0.46 W/ m2K, for internal partitions it was 0.46 W/ m2K, for ground contact/exposed floors it was 0.33 W/ m2K, for ground contact/exposed floors exposed to air the U-value was 0.42 W/ m2K, for internal ceilings/floors it was 0.52 W/ m2K, for roof it was 0.40 W/ m2K, for external store windows the net U-value (including frame) was 2.57 W/ m2K and for external office windows the net U-value (including frame) was 2.63 W/ m2K. The main improvement in this case study was the insulation and system (HVAC) resulting in a better energy performance of the building with lower energy consumption. In general the U-values of the base case study were lower than the reference building and the building responded to the new energy standards required by the Implementation of the EPBD in Cyprus.
In addition, the Refurbishment case study included system improvement. The older type using the original HVAC systems were replaced with newer energy efficient systems and consequently the energy demand for heating and cooling was reduced.
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Compared to the Base case study, the improvement was 66.7% for the cooling system and 150% for the heating system.
The total annual energy consumption was 565.5 MWh and the total annual energy consumption per floor area was 155.1kWh/m2. The peak load for heating was in January (4.9 MWh) and the peak load for cooling was in August (20.4 MWh). The total heating energy demand was 25.9 MWh per year and the total cooling demand was 122.2 MWh per year. The
Total carbon dioxide emissions (yearly) were 518,093.8kgCO2 where the total system
emissions were 269,074.3kgCO2, the light total emissions were 170,109.7 kgCO2 and the
equipment total emissions were78,909.7kgCO2. Comparison of the Base case study and the Refurbishment case study showed that the improvements resulted in an annual energy reduction of 17.01% and a reduction of 16.88% in total yearly energy consumption per floor area.
The simulation weather file was based on Larnaca where the mean dry-bulb temperature was in August (31.15o C) and the mean dry-bulb temperature was in February (15.45 o C). According to the weather data, heating demand is high from mid-November to mid-April and cooling demand is high from May to November. The considerably reduced heating demand (almost to zero) from May to mid-November is due to the use of solar panels for hot water and of operation profiles for the HVAC systems. The small increase of cooling for October and November was due to the increase in internal temperature from sun radiation. The insulation of the building contributed negatively to this as the insulation measures aimed to maintain the indoor temperature and consequently the cooling demand was maintained during the winter period. However, the general profile of the cooling demand presented a 53.52% decrease which was highly significant. Maintaining constant temperatures during the winter and summer was an issue for the project but the main target was the reduction of energy and not the optimization of cooling or heating demand. Compared to the main target of the research, the project can at this stage be characterized as successful.
The cooling and heating systems used electricity to cover the building’s needs. The peak system electricity load was high in winter and summer and low in spring and autumn. The fluctuations of the system power (electricity) were not so extreme compared with the Base case study due to the improved operation of the systems and the improved response to outdoor changes.
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9.5. Office Building–Best Practise case study (New buildings)
The Best Practice case study (New buildings) is in compliance with the new construction and energy efficiency regulations. Furthermore, all HVAC systems were based on new technological systems that afforded lower energy consumption for the building’s needs. This case study is based mainly on new building construction where the new energy regulations are compulsory.
Table 48 shows the technical characteristics of the construction materials (construction layers outside to inside) and simulation values for the office building under the refurbishment case scenario. These values were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities. [168][169]
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Table 48: Office Building (Best Practice case scenario) construction input simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Office building – Best Practise case study
1 External Wall 0.39 4.05 0.04 0.13 0.24 2 Internal Partitions 0.14 3.57 0.13 0.13 0.26 3 Ground 0.92 0.84 0.04 0.17 0.19 contact/exposed floors 4 Ground 0.47 6.26 0.04 0.17 0.15 contact/exposed floors to air 5 Internal 0.72 4.89 0.10 0.10 0.20 Ceilings/Floors 6 Roofs 0.69 4.42 0.04 0.10 0.22
a/a Description - Construction U-value Net U-value Outside surface inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows 0.044 1.70 1.85 0.04 0.13 Store Windows External Windows 0.054 1.69 1.84 0.04 0.13 Office Windows
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 3.5 4.0 1.0
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 3.5 3.5 4.0 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 1.0 10 60 served by apacheHVAC Solar panels solar panels 20 m2 sun heat exchanger 10 60 effectiveness was 0.40
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The following assumptions have been made during the simulation procedure:
1. The windows remained closed during the simulation. 2. The HVAC system was controlled by sensor in each room so the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling. 3. Both store and office windows covered by external shading - louvres and internal shading-blinds - were operated with profiles. Consequently, summer and winter operation profiles needed to be created to offer the best performance for the building’s needs. For the summer profile the louvres and blinds were on from 9 a.m. to 5 p.m. and from 10 a.m. to 4 p.m. for the winter profile. The profiles were set to operate throughout the week and for seasonal operation in summer they operated between June and October and in winter from November to March.
The input simulation data and the detailed simulation results of the Office building - Best Practice case study can be found in Appendix H.
9.5.1. Renewable energy-Photovoltaic systems
Since the aim of the Best Practice case study is to develop a design for a Zero Energy building, the best option for minimizing or eliminating the electricity demand was the installation of renewable energy systems on the building roof. As this case study used the available insulation materials, construction methods and energy efficient systems to minimize the building’s energy demand, the next step was the introduction of photovoltaic systems to cover the building’s energy requirements. The choice of photovoltaics is explained in detail in Chapter 8 - single family house case study in subsection 8.5.1. renewable energy- photovoltaic systems.
The optimization procedure for a photovoltaics area returned an energy self-sufficient Office Building with the energy demand fully covered by the installation of photovoltaics. However, a major issue during the optimization of the PV area was the available space on the building for the systems’ installation. Due to the building’s predicted high energy demand, the PV area needed to cover the demand was extremely large in relation to the available roof area. As the installation of the PV systems on the building was not part of the work of this research, it was assumed that there was available space to install the PV systems. This area could be the shading systems- louvres or the glazing of the building in combination with the available roof space.
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Another option recently introduced with the new regulations was the installation of PV systems in an available area beside or near the building and the transfer of the produced energy to the building.
During the optimization exercise, monocrystalline silicon photovoltaics were used with PV module nominal efficiency 0.17, Reference irradiance for NOCT 1000W/m2 and PV area 2900m2. This combination produced a surplus of energy 12.9 MWh per year which can be used from the grid for other purposes or to cover other energy needs (Figure 77).
Figure 77: The photovoltaics system installation settings
It should be mentioned that all the values used by the project for the simulation procedure were not taken by at random, but were a result of research and collaboration with the Energy Service of the Ministry of Commerce, Industry and Tourism, which has the overall responsibility for Energy in Cyprus. [168][169][173]
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495 0.18 480 465 450 435 0.16 420 405 390 375 0.14 360 345 330 0.12 315 300 285 270 0.1 255 240 225 210 0.08 195 Total Total energy MWh consumption 180 165 efficiency nominal PV module 150 0.06 135 120 105 90 0.04 75 60 45 30 0.02 15 0 -15 -30 0 400 1200 2000 3200 3800 2900 0 PV area in square meters
Total energy consumption MWh PV module nominal efficiency
Figure 78: Area optimization of the PV systems
Table 49: Photovoltaic system input data
Tests PV type PV module Reference PV area Total yearly nominal irradiance for m2 energy efficiency NOCT (W/m2) consumption of the office (MWh) Test 1 Monocrystalline - - 0 479 silicon Test 2 Monocrystalline 0.13 800 400 409.2 silicon Test 3 Monocrystalline 0.13 800 1200 323.3 silicon Test 4 Monocrystalline 0.13 800 2000 220 silicon Test 5 Monocrystalline 0.13 800 3200 65 silicon Test 6 Monocrystalline 013 1000 3800 -12.5 silicon Test 7 Monocrystalline 0.17 1000 2900 -12.1 silicon
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9.5.2. Orientation of the Best Practice case study
The impact of the building orientation of the building was studied during this project. The building’s orientation has a significant impact on building performance since the optimum orientation allows the capture of free heat in winter and repels the heat in summer and the optimum Office orientation for maximum energy efficiency is achieved when the long axis of the building runs east to west (Figure 79).
Figure 79: Office building orientation and sun path during the summer and winter time. All the simulation parameters remained the same (construction, system parameters and weather file) while only the orientation of the office building was changed. The office building was turned 90o and the main entrance of the office building changed from south facing to west facing (Figure 80).
Figure 80: Initial and final orientation of the Office building.
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The Office building was turned 180o and the main entrance of the office changed from south facing to north facing (Figure 81).
Figure 81: Initial and final orientation of the Office building The Office building was turned 270o from the initial orientation and the main entrance of the office changed from south facing to east facing (Figure 82).
16
15
14
13
12
11
10
9 South face 8 West face 7 Systems Energy Systems Energy (MWh) 6 North face 5 East face 4 3 2 1 0
Heating
Figure 82: Heating demand and orientation impact
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70 65 60 55 50 45 40 South face 35 30 West face 25 North face Systems Energy Systems Energy (MWh) 20 East face 15 10 5 0
Cooling
Figure 83: Cooling demand and orientation impact
4.0%
3.0%
Percentage Difference Percentage (%) 2.0%
1.0%
0.0% South vs West South vs North South vs East Heating demand 3.9% 3.2% 2.6% Cooling demand 1.0% 0.8% 2.5%
Figure 84: Percentage Difference (%) in energy consumption between the different orientations.
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9.5.3. Height effect of the Best Practice case study
In this case study, the office building was eight storeys high. The energy consumption for cooling and heating was related not only to the building orientation but also to the height of the different floors. Consequently, a peak room load analysis was made so as to investigate the relation between energy consumption (heating and cooling energy) and the height of the floors. Figure 178 shows the peak room conditioning loads (kW) for heating and cooling and the orientation of the offices on the floors. The secondary axes of the graph (figure 178) from zero to three represent the direction of the offices; the north facing offices are number one, the south facing offices number two, and the south and north facing offices number three. It should be mentioned that office group five had generally higher energy consumption for heating and cooling as it covered a larger area than the other office groups.
10 3 9.5 9 8.5 8 7.5 7 6.5 2 6 5.5 5 4.5 4 3.5 1 of the building Direction 3 2.5 Peak Room Conditioning Loads (kW) Loads Conditioning Room Peak 2 1.5 1 0.5 0 0 Office 1 floor 2 Office 1 floor 3 Office 1 floor 4 Office 1 floor 5 Office 1 floor 6 Office 1 floor 7 Office 1 floor 8 Office 2 floor 1 Office 2 floor 2 Office 2 floor 3 Office 2 floor 4 Office 2 floor 5 Office 2 floor 6 Office 2 floor 7 Office 2 floor 8 Office 3 floor 1 Office 3 floor 2 Office 3 floor 3 Office 3 floor 4 Office 3 floor 5 Office 3 floor 6 Office 3 floor 7 Office 3 floor 8 Office 4 floor 1 Office 4 floor 2 Office 4 floor 3 Office 4 floor 4 Office 4 floor 5 Office 4 floor 6 Office 4 floor 7 Office 4 floor 8 Office 5 floor 1 Office 5 floor 2 Office 5 floor 3 Office 5 floor 4 Office 5 floor 5 Office 5 floor 6 Office 5 floor 7 Office 5 floor 8 Office 1 1 Office floor Best Practise/Heating Best Practise/Cooling Direction
Figure 85: Peak Room Conditioning Loads (kW) and Building orientation: secondary axis- direction, Number 1=North face, Number 2= South face, Number 3= South and North
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The initial position of the building was south where the long axis of the building runs east to west. In the first case the building was turned 90o clockwise, in the second case 180o and in the third case 270o. The results of the different simulations showed that the best orientation, i.e. where the office was more energy efficient, was south facing (the long axis of the building running east to west). Comparing the south facing and the west facing orientation showed that for the south the heating demand was 3.9% lower and the cooling was 1.0% lower than the west. Comparison the south and north orientation showed that the heating demand was 3.2% lower and the cooling was 0.8% lower in the south than in the north. Comparison between the south and east showed that in the south the heating demand was 2.6% lower and the cooling was 2.5% lower than in the east. The general conclusion drawn from this analysis is that the optimal orientation of the building could contribute positively to the energy reduction of the building. However, the materials and construction methods of the building were related to orientation. The case Office building had large glazing surfaces and hence the building orientation did not have the same impact as in the case of a single family house.
9.5.4. Office Building -Best Practice case study results analysis
The Best Practice case study represents the new construction of buildings and the new European energy regulations such as the Implementation of the EPBD in Cyprus. The implementation of the EPBD in Cyprus was the first to require thermal insulation in Cyprus buildings envelope. In addition, minimum energy performance requirements were set for new buildings, both residential and commercial. The Best Practice case study is based on these standards in order to develop the project but further measures were also developed in order to achieve the initial target of Zero Energy Building.
Table 50: U-value comparison between the Reference building and the Office Best Practise case study
Exposed elements Reference building Best Practice case study Reduction of U-value U-value U-value (W/ m2K) (W/ m2K) (%)
Roofs 0.64 0.22 65.60
Walls 0.72 0.24 67.20
Internal Partitions / 0.26 -
Floors/ceilings 0.64 0.20 69.20
Ground floor 1.60 0.15 90.30 Windows 3.23 1.84 42.90
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The construction improvements of building elements in the Best Practice case study significantly reduced the U-values of the building while also improving the building energy performance. All building elements U-values were lower compared to reference building and therefore responded to not only current but also future energy regulations.
Moreover, the Best Practice case study included further system improvements compared to Refurbishment and Base case studies. As new more energy efficient systems replaced the previous HVAC systems, the energy demand for heating and cooling decreased. Compared to the Base case study the improvement was 100 % for the cooling system and 250% for the heating system. Compared to the Refurbishment case study, the improvement was 40% for both the cooling and the heating systems. The systems efficiency had a significant impact on the reduction of energy demand for maintaining indoor comfort temperatures.
The total yearly energy consumption was 479 MWh and the total yearly energy consumption per floor area was 131.4 kWh/m2. The peak load for heating was in February (2.7 MWh) and the peak load for cooling was in August (10.8 MWh). The total heating energy demand was 16.1 MWh per year and the total cooling demand was 60.9 MWh per year. The total carbon
dioxide emissions (yearly) were 439,484.5kgCO2 while the total system emissions were
190,465.1kgCO2, the light total emissions were 170,109.7 kgCO2 and the equipment total
emissions were 78,909.7kgCO2. The comparison between the base case study and the best practice case study showed that the improvements effect a yearly energy reduction of 29.58% and a reduction in total yearly energy consumption per floor area of 29.58%. The comparison between the refurbishment case study and the best practice case study showed that the improvements result in a yearly energy reduction of 15.29% and a reduction in total yearly energy consumption per floor area of 15.28%.
The simulation weather file is based on Larnaca where the mean dry-bulb temperature was in August (31.15 o C) and the mean dry-bulb temperature was in February (15.45 o C). According to the weather data, the heating demand is high from late November to late March and the cooling demand is high from May to November. The decreased (almost to zero) heating demand from May to mid- November is due to the use of solar panels for hot water, better boiler efficiency and the use of operation profiles for the HVAC systems. The use of shading systems and operation profiles for the HVAC systems contribute positively to the energy reduction for cooling and heating.
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The sun penetration into the indoor space at unnecessary times was minimized by the use of shading systems (external shading system controlled by operation profiles).
The cooling and heating systems used electricity to cover the building needs. The peak system electricity load was high in summer and low in winter, spring and autumn. The fluctuations of the system power (electricity) were not as extreme as in the Base and Refurbishment case studies due to the further improved systems operation and an improved response to the outdoor changes. In general, the use of system electricity fell significantly so the office energy needs could be easily covered by renewable energy systems.
In addition, the Best Practice case study investigated the installation of the photovoltaics system on an office building. The main goal was to transform the building into a Zero energy Building where building needs would be covered by a locally renewable system. The optimization procedure of PV area, PV module nominal efficiency and Reference irradiance for NOCT (W/m2) returned a zero energy performance where the 2900m2 of photovoltaic system cover the office energy needs. Moreover, the minimum PV area offers 12.9 MWh per year surplus of energy. The PV type was monocrystalline silicon with a PV module nominal efficiency 0.17 and the Reference irradiance for NOCT was 1000 W/m2.
The Best Practice case study in combination with renewable systems (photovoltaics system) established that the goal of Zero Energy Building performance is achievable in theory and so there is great potential for constructing it in reality. The only aspect not included in this project was the cost of this solution which plays an important role in final decisions. However, the cost of zero energy buildings is an issue that needs to be thoroughly examined comparing the investment with the depreciation time. However, this was not relevant to the research in hand as the goal was the achievement of Zero energy building in a hot climate.
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9.6. Comparison of the three case studies
Table 51: Comparison of the three case studies
Parameters Base case study Refurbishment Best practice case Comparison Comparison Comparison (1) case study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%) Construction:
External wall U-value (W/m2K) 1,44 0.46 0.24 68.21 83.60 48.40 Internal Partitions U-value (W/m2K) 1,48 0.46 0.26 68.87 82.31 43.18 Ground/Exposed Floors U-value 1,11 0.33 0.19 70.07 82.42 41.26 (W/m2K) Ground/Exposed Floors (air) U- 1.37 0.42 0.15 69.45 88.68 62.95 value (W/m2K) Internal Ceiling/Floor U-value 0.88 0.55 0.20 37.27 77.56 64.38 (W/m2K) Roofs U-value (W/m2K) 1.12 0.40 0.22 63.99 80.40 45.59 Store Glazing U-value (W/m2K) 5.28 2.57 1.85 51.32 64.92 27.93 Office Glazing U-value (W/m2K) 2.81 2.63 1.84 6.31 34.30 39.87
Heating system:
Fuel Electricity Electricity Electricity - - - Seasonal Efficiency 1.0 2.5 3.5 150 250 40 SCoP kW/kW 1.0 2.0 4.0 100 300 100 Vent. heat recovery effectiveness 0.0 0.5 1.0 - - 5025 Vent. Heat recovery return air temp. 0.0 21.0 o C 21.0 o C - - -
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Parameters Base case study Refurbishment case Best practise case Comparison Comparison Comparison (1) study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%) Cooling systems: Mechanism Air conditioning Air conditioning Air conditioning - - -
Fuel Electricity Electricity Electricity - - - Seasonal EER kW/kW 2.0 2.5 3.5 25.0 75.0 40 SSEER kW/kW 2.0 2.6 4.0 30.0 100 53.84 Heat rejection (% of rejected heat) 2.2 10 15 - - - Hot Water: Served by ApacheHVAC boiler Yes Yes YES - - - DHW delivery efficiency 0.50 0.50 1.0 - 100 100 Mean cold water inlet temperature 10oC 10oC 10oC - - - Hot water supply temperature 60oC 60oC 60oC - - - Solar water system: Area m2 12 20 - - 66.66 Heat exchanger effectiveness 0.0 0.4 0.4 - - - Total Yearly Energy Consumption 680.2MWh 565.5MWh 479MWh 17.01(-)** 29.58(-)** 15.29(-)** Total Yearly Energy Consumption per 186.6 kWh/m2 155.1kWh/m 2 131.4kWh/m 2 16.88(-)** 29.58(-)** 15.28(-)** Floor Area *Comparison between the Case studies and Percentage Change between the parameters,**(-)=reduction of energy
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14 13.5 13 12.5 12 11.5 11 10.5 10 9.5 9 8.5 8 7.5 7 6.5 6 5.5 5 4.5 4
Systems Energy Systems Energy (MWh) 3.5 3 2.5 2 1.5 1 0.5 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Office Base case study Office Refurbish case study Best Practise case study
Figure 86: Monthly system energy comparison for the three case studies-heating systems
100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% Consumption Consumption 40% 35% 30% 25% 20% 15%
Percentage Reduction (%) of Monthly Heating Energy Energy Heating (%) ofMonthly Reduction Percentage 10% 5% 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case study 63.2% 59.1% 54.3% 32.3% 30.0% 22.2% 30.0% 22.2% 30.0% 80.0% 16.7% 57.6% Compare Base with Best Practise case study 80.5% 76.5% 71.4% 48.4% 80.0% 88.9% 90.0% 88.9% 90.0% 80.0% 44.4% 75.3% Compare Refurbish with Best Practise case study 46.9% 42.6% 37.5% 23.8% 71.4% 85.7% 85.7% 85.7% 85.7% 0.0% 33.3% 41.7%
Figure 87: Percentage Reduction (%) of Monthly Heating Energy Consumption
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36 34.5 33 31.5 30 28.5 27 25.5 24 22.5 21 19.5 18 16.5 15 13.5 12 10.5 Systems Energy Systems Energy (MWh) 9 7.5 6 4.5 3 1.5 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Office Base case study Office Refurbish case study Best Practise case study
Figure 88: Monthly system energy comparison for the three case studies-cooling systems
100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% Consumption Consumption 45% 40% 35% 30% 25% 20% Percentage Reduction (%) Reduction of Percentage MonthlyEnergy Cooling 15% 10% 5% 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case study 33.3% 23.5% 23.4% 37.9% 36.9% 38.8% 40.4% 41.2% 41.4% 41.4% 38.1% 28.0% Compare Base with Best Practise case study 69.2% 64.7% 59.6% 72.8% 67.3% 67.2% 68.5% 68.9% 72.3% 74.8% 72.9% 64.0% Compare Refurbish with Best Practise case study 53.8% 53.8% 47.2% 56.3% 48.1% 46.4% 47.2% 47.1% 52.8% 56.9% 56.2% 50.0%
Figure 89: Percentage Reduction (%) of Monthly Cooling Energy Consumption
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Generally, comparison of these case studies showed that the Best Practice case study achieved larger energy reductions than the Refurbishment case study. Comparing the Best Practice and the Refurbishment case study, the greater heating energy reduction (related only to space heating) was presented in January (46.9%) and the lower in November (33.3%). A considerable reduction in cooling demand (47.1%) was achieved for the summer period (from June to August) when there is an actual need for cooling. However, the refurbishment scenario cannot be ignored as many Cypriot buildings had already been constructed before the new energy regulations. Methodology development for building refurbishment is urgently needed to make old buildings more energy efficient and closer to being low energy buildings; however, building refurbishment is problematic as there are sometimes many limitations affecting the use of available solutions, techniques and materials.
Another important issue with the office case study was the height of the building. The building had eight floors with five offices on each floor. Three offices were south facing, one office had a north facing orientation and one (a large office situated in a corner of the building) had a south and north facing outlook. Figure 90 shows peak Room conditioning loads (kW) for heating for the three case studies and Figure 91 shows peak room conditioning loads (kW) for cooling.
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14 3 13.5 13 12.5 12 11.5 11 10.5 10 9.5 2 9 8.5 8 7.5 7
6.5 of the building Direction
Peak Room Conditioning Loads (kW) Loads Conditioning Room Peak 6 5.5 5 4.5 1 4 3.5 3 2.5 2 1.5 1 0.5 0 0
Base case/Heating Refurbish/Heating Best Practise/Heating Direction
Figure 90: Heating peak room conditioning loads (kW) and building orientation: where on secondary axis- direction, number 1=north face, number 2= south face, number 3= south and north
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14 3 13.5 13 12.5 12 11.5 11 10.5 10 9.5 2 9 8.5 8 7.5 7 6.5 6 5.5 5 of the building Direction 4.5 1 4 3.5 Peak Room Conditioning Loads (kW) Loads Conditioning Room Peak 3 2.5 2 1.5 1 0.5 0 0
Base case/Cooling Refurbish/Cooling Best Practise/Cooling Direction
Figure 91: Cooling peak room conditioning loads (kW) and building orientation: where on secondary axis- direction, number 1=North face, number 2= South face, number 3= South and North
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The measures applied in the different case studies succeeded in reducing the peak heating room conditioning loads (kW) in all offices regardless of the office orientation. The Base case study without any insulation or energy efficiency measures had a higher heating consumption than the two other case studies. After the refurbishment and the application of insulation the heating demand decreased significantly. The Best Practice case study had the lower heating peak load due to the further energy measures applied to the building. The combination of new insulation materials with new techniques of construction and new energy efficient systems achieved increased heating reduction in the building. The offices on eight floors presented a higher heating demand in general regardless of orientation. This was due to the height effect where the top floor had surfaces which were more exposed to outside conditions and the interaction between indoor and outdoor conditions was greater. The considerable difference in heating loads of the group five offices was due not only to the difference in area from the other offices but also to the fact that this group of offices had larger surfaces of glazing. This office group occupied both sides of the building, the front facing south and the rear facing north. The north facing orientation in combination with the large glazing surface significantly increased the heating demand.
The comparison of cooling peak loads between the three case studies showed that the Base case study had the higher cooling peak loads and the Best Practice case study the lower cooling peak loads. The Base case study did not include any energy efficient measures for the building performance in contrast with the Refurbishment case study where the changes were based on the new energy regulations and standards. The reduction of cooling peak loads was substantial after the adoption of different methodologies and measures for the energy reduction of the building. The improvement of the HVAC systems, the development of internal shading and operation with profiles and the insulation of the building were some of the fundamental improvements that contributed positively to the reduction of cooling peak loads. The Best Practice case study adopted further methodologies in order to reduce the demand to a possible minimum. The development of external and internal shadings (louvres and blinds) operated with profiles, the improvement of the HVAC systems, the installation of super insulation on the building elements and the control of the systems with operation profiles succeeded in reducing the cooling peak loads and thus the energy demand of the building.
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The most important achievement of the energy measures was the fact that the top floor (eighth floor) which had higher cooling peak loads than in the in Base and Refurbishment case studies had almost the same cooling peak loads as in the Best Practice case study. This can be interpreted as the success of the energy measures and construction in minimizing the impact of external conditions on the indoor environment.
9.7. Weather- Microclimate Effect
During the project development the weather and microclimate effect were analysed in order to examine their impact on energy consumption of the office building. The Office Best Practice case study was simulated with different towns of Cyprus and with a different weather file each time. The simulation weather files were a result of the weather research conducted by the project and analysed in the previous chapter (Chapter 6). According to the results of Chapter 6, the climatological zone in which the building is located is crucial in terms of weather conditions, architectural style and therefore energy behaviour.
By keeping all the other factors constant and changing only the simulation weather file, any increase or decrease of system energy (heating and cooling) was due to the microclimate differences between the towns. Figure 92 and Figure 93show the results of the simulation tests. There are striking differences between the Cyprus towns that cannot be ignored if the estimation of potential building energy demand is to be as accurate as possible. The graphs show that simulation based on only one location may underestimate the cooling or the heating demand of the office building.
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0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES data 2.1 2.2 1.6 1.2 0.7 0.6 0.7 0.7 0.7 0.7 0.9 1.5 Larnaca 1997-2008 2.6 2.4 2 1.1 0.8 0.6 0.6 0.6 0.7 0.9 1 1.6 Limassol 1997-2008 2.4 2.3 1.8 0.9 0.7 0.6 0.6 0.6 0.6 0.8 1 1.6 Limassol 2000-2009 2.7 2.6 2.1 1 0.7 0.6 0.6 0.6 0.6 0.9 1.3 1.4 Nicosia 1997-2008 2.6 2.4 1.9 1 0.8 0.6 0.6 0.6 0.7 0.8 1 1.6 Nicosia 2000-2009 2.4 2.3 1.8 0.9 0.7 0.6 0.6 0.6 0.6 0.8 1 1.6
Figure 92: Heating demand and microclimate effect
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0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES vs Larnaca 1997-2008 24 9 25 8 14 0 14 14 0 29 11 7 Larnaca IES vs Limassol 1997-2008 14 5 13 25 0 0 14 14 14 14 11 7 Larnaca IES vs Limassol 2000-2009 29 18 31 17 0 0 14 14 14 29 18 7 Larnaca IES vs Nicosia 1997-2008 24 9 19 17 14 0 14 14 0 14 11 7 Larnaca IES vs Nicosia 2000-2009 14 5 13 25 0 0 14 14 14 14 11 7 Larnaca IES vs Nicosia 2000-2009 2.4 2.3 1.8 0.9 0.7 0.6 0.6 0.6 0.6 0.8 1 1.6
Figure 93: Percentage difference between the simulation weather files for heating demand
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0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES data 1.1 1.2 1.7 2.4 4.5 6.5 8.1 8.4 7 4.6 2.9 1.7 Larnaca 1997-2008 1.5 1.6 2.6 3 5.5 8.5 10.9 10.8 8.1 5.7 3.4 2.4 Limassol 1997-2008 1.6 1.7 2.8 2.9 5.3 8.3 10.7 10.8 7.9 5.7 3.4 2.5 Limassol 2000-2009 1.2 1.2 1.9 2.7 5.5 10 12.2 12 8 6.1 5.5 3 Nicosia 1997-2008 1.5 1.6 2.7 3 5.4 8.5 10.8 10.8 8 5.6 3.4 2.3 Nicosia 2000-2009 1.6 1.7 2.8 2.9 5.3 8.3 10.7 10.8 7.9 5.7 3.4 2.5
Figure 94: Cooling demand and microclimate effect
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0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES vs Larnaca 1997-2008 36 33 53 25 22 31 35 29 16 24 17 41 Larnaca IES vs Limassol 1997-2008 45 42 65 21 18 28 32 29 13 24 17 47 Larnaca IES vs Limassol 2000-2009 45 42 65 21 18 28 32 29 13 24 17 47 Larnaca IES vs Nicosia 1997-2008 36 33 59 25 20 31 33 29 14 22 17 35 Larnaca IES vs Nicosia 2000-2009 45 42 65 21 18 28 32 29 13 24 17 47
Figure 95: Percentage difference between the simulation weather files for cooling demand
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9.8. Future Weather files
Based on the simulation weather files created during the development of the project, future weather files were constructed in order to predict the performance of the Best Practice case study- zero energy building in future time.
The future simulation files concerned the years 2020, 2050 and 2080. The following graphs are a useful tool for engineers to be able to predict and change, wherever possible, parameters that can be vital for future building performance.
Future weather analysis is based on the best practice case study building and used three future weather files for each town (2020, 2050 and 2080). In this way the project examined the possible impacts on heating and cooling demand of the proposal zero energy building (best practice case study building) in three different locations (towns) of Cyprus.
9.8.1. Future Weather files- Limassol town
2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 HeatingSystems Energy (MWh) 0.8 0.6 0.4 0.2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Limassol 1997-2008 Limassol 2020 Limassol 2050 Limassol 2080
Figure 96: Heating demand and Future weather files
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18 17 16 15 14 13 12 11 10 9 8 7 6
Cooling Systems Energy (MWh) 5 4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Limassol 1997-2008 Limassol 2020 Limassol 2050 Limassol 2080
Figure 97: Cooling demand and microclimate effect
9.8.2. Future Weather files- Nicosia town
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Nicosia 1997-2008 Nicosia 2020 Nicosia 2050 Nicosia 2080
Figure 98: Nicosia Heating demand and Future weather files
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Figure 99: Nicosia cooling demand and microclimate effect 9.8.3. Future Weather files- Larnaca town
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Figure 100: Larnaca Heating demand and Future weather files
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Figure 101: Larnaca Cooling demand and microclimate effect
9.8.4. Weather data results
The impact of weather and microclimate on energy consumption of buildings was a vital issue for this project. As mentioned in Chapter 6 (weather data analysis), the climate and the weather data files are crucial for the accuracy of the building simulation. The development of weather data files for three different towns of Cyprus and the simulation of the Best Case study under the different weather simulation files revealed useful information. The results from Chapter 6 indicate that differences between the weather stations are due to the different locations and microclimate effects and these differences were observed during the simulation of the office building. The seasonal difference between mid-summer and mid-winter temperatures is approximately 19oC for Nicosia and 13oC for Limassol and Larnaca. The comparison of the results showed that the heating demand is higher inland than it is in the coastal areas, Larnaca and Limassol. Concerning the cooling demand, the highest values are presented in the Limassol 2000-2009 weather file and the lowest in Larnaca IES data. The coastal towns appeared to need slightly more cooling during the summer than inland Nicosia. According to the Chapter 6 results, this is because the coastal towns present higher humidity levels which, in combination with high temperatures, create more uncomfortable conditions. What was most significant about this comparison was the fact that the Larnaca IES data underestimated the heating and cooling needs for the Office building.
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Moreover, the comparison stressed the essential role of the updated weather simulation files for accurate simulation results.
What was most noteworthy about the weather analysis in Chapter 6 was the significant differences between the towns and, in general, between inland and coastal towns, that could not be ignored. The IES simulation program offered only one simulation file for Cyprus, the Larnaca weather simulation file, which was unable to cover the microclimate conditions of the whole island. Simulations based on only this weather file would possibly under- or overestimate the cooling and heating demand. At this point, it is essential to mention that the Cyprus Energy Service recognises four major climatological zones (Chapter 6), namely coastal, low land, semi-mountainous and mountainous areas. [174] Hence, the project confirms the need for updated weather simulation files and a specific weather simulation file for each town. The effect of weather is a major factor affecting indoor office conditions and systems operation.
Another aspect of the weather analysis in Chapter 6 was predicted estimations for the weather as well as for building performance for 2020, 2050 and 2080. According to the Chapter 6 results, in the future Limassol is predicted to have colder winters; this means an increase in office building heating demands and summers will be hotter compared with 1997-2008 data. The heating demand for 2050 and 2080 is predicted to decrease which means that winters may be warmer at that time. Moreover, in 2080 the predicted cooling demand will be higher than the previous year which means that 2080 will present higher temperatures in general. For Nicosia and Larnaca there is a predicted decrease in heating requirements for 2020, 2050 and 2080 from November to January. On the other hand, the cooling demand will increase during the summer period (from June to August) and the hottest period seems to be 2080 where the cooling will be higher compared to the previous years even during the winter. The Larnaca future weather files show that the winters of 2020, 2050 and 2050 are expected to be warmer compared to 1997-2008. In comparison with the previous years, 2080 is expected to have a warmer winter and warmer summer. There will be an increasing cooling demand for all the future weather files compared with 1997-2008. Generally, there will be an increasing tendency for cooling and a decreasing tendency for heating, especially for 2080. The importance of this simulation is the fact that in future weather conditions will probably change with winters and summers becoming hotter and, as a result, office building needs for cooling and heating will change.
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The exact degree of change is unpredictable as the changes in weather are caused not only by natural changes but also depend on human activities worldwide. It is impossible to accurately predict the impact of human activity and natural changes using mathematical models. Only conjectures about possible future changes can help engineers improve the future performance of buildings at an early stage.
The outcome of the results in Chapter 6 and the office building simulation indicate that there is a direct connection between the energy performance of the building and the local climatic conditions (represented by the simulation weather data files) that cannot be ignored. In order to design a successful zero energy office building and achieve the best energy performance, it is imperative to take the local weather into account.
9.9. Conclusion
The research results reveal invaluable information for the transformation of the Cyprus building stock into zero energy buildings as well as the construction of new types of buildings. In both cases there are important issues needing to be taken into account by the Cyprus authorities.
According to the project results, the design of a zero energy office building depends on the following basic elements:
1. A good knowledge of the local climate (for hot climates, humidity levels, sunshine duration, orientation of the sun, TRY files available): in both cases, refurbishment and base case study, the microclimate has an important impact on the stage of decision making. The strategy to follow for a particular building is defined by climatic conditions as they strongly influence human behaviour. A good knowledge of the local climate with the use of an automated system can contribute positively to reduced energy consumption by an office building as the hours of space use is specific. At this step, weather data of the local climate will be needed in order to understand the climatic conditions.
2. Priority should be given to the passive design (roof/wall/floor/windows insulation, solar shadings for windows, natural ventilation, use of day-lighting): in both cases refurbishment and base case study the insulation of the building plays a vital role. Old building constructed before the Implementation of the EPBD in Cyprus [168],
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had no insulation [176] and consequently the energy consumption of the buildings was high. In the case of old office buildings, there is the need for refurbishment where external insulation will be installed into the walls and roof, old windows will be replaced with new windows with insulation and solar shadings will be installed wherever necessary. Furthermore, windows will need to be redesigned in order to provide the appropriate daylight and minimize the use of electric lighting.
The construction of new buildings (Base case study) introduces super insulation with external and internal insulation, triple-glazed windows and solar shadings. In the cases of hot climates such as Cyprus, external insulation is vital in order to protect the external building elements and the transfer of the head in the internal partitions. On the other hand, internal insulation maintains the interior conditions of the office to required levels of comfort. Moreover, the initial design and orientation of the building is vital as it will define the window design and size, the natural light of the building and the solar shadings that will be needed.
3. Energy efficiency of systems is mandatory (high SEER for chillers if necessary, Energy Efficient systems.): another important aspect of the zero energy buildings is the systems energy efficiency. In case of refurbishment, old systems should be replaced by new systems with high energy efficiency, low electricity consumption and high output. In hot climates the cooling demand is high and has a considerable impact on energy consumption. Thus effective systems monitoring in combination with energy efficient systems will contribute to the reduced use of building energy.
In the case of new buildings, all systems should be energy efficient with high output and low energy consumption. The cooling demand can be reduced not only by energy efficient systems but also through efficient monitoring and appropriate insulation of the building. In the case of office buildings, the comfort levels and the hours of use of the space are specific which means that a building can be easily controlled by smart systems. The advantage of smart systems is that they provide the correct use of cooling and heating systems, suitable natural ventilation during the night and the maintenance of comfort levels. This will contribute to reduced energy use as the systems will function only when is necessary.
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4. Development of renewable energy systems: once these previous steps have been taken into account, the use of renewable energy can be considered as part of the building design process. The development of renewable energy systems is a vital step in achieving the zero energy office. The development of these systems could also be applied in the refurbishment case study, but in that case an extensive redesign is necessary so that the installation of the systems will be part of the building.
On the other hand, the zero energy building will be a mandatory status for all new buildings constructed after 31st December 2020 for European member states. [177] This implies that, beside energy efficiency, systems based on renewable energy sources must be implemented to provide energy savings and environmental benefits for space conditioning, water heating and energy production. As previously discussed, photovoltaic systems present the best choice due to the long hours of sunshine of the Cyprus climate. Solar systems in general play an important and vital role in the design and development of the zero energy office. It was developed during the research and the office building needs were covered by photovoltaic systems.
The main focus is to reduce energy consumption of the office building to a minimum with the use of with passive techniques and then apply renewable energy systems in order to cover the remaining energy needs. This signifies a huge step for the Cyprus building market since it implies a dramatic change in design methods which will involve focusing on active energy efficient systems (such as air-conditioning, artificial lighting) and enable buildings to cover energy demands through the use of renewable sources.
The results of the research indicate that the development of zero energy office building is possible and achievable. The above basic steps can be adapted and developed by the Cyprus authorities and the building market as they have a direct impact on zero energy building in a hot climate. However, the technologies by themselves are not enough and there is need for a more powerful legislative framework that will be methodical in transforming the building sector to achieve the National European targets of 2020. Nevertheless, the powerful legislative framework will need support with appropriate economic backing and powerful motivation. This in turn will involve the implementation of training/ information programs for those who are involved in the construction process of buildings.
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Chapter 10: Residential Building- Olympic residence case study.
10.1. Introduction
The building chosen as representative of the new type of residential building now being constructed in Cyprus was the very first 19-storey building and the first to use new construction methods. The building parts, external and main internal walls, were made with concrete in contrast to other old buildings which were brick-built.
Due to increasing land prices combined with increasing building construction, the development of taller buildings is now permitted and building companies are now turning to new types of construction in order to maintain their profits. Moreover, due to the limited available land in the small Cyprus towns or old buildings being demolished and replaced with new, building companies increased the number of floors in order to cover high construction costs. Hence the transformation of the Cyprus residential building sector focuses on tall buildings for the future. However, this type of building will have high energy demands not only due to the size but also to the new trends of comfort levels including internal conditions and facilities. Therefore, as the project is based on conditions that will exist in the future, the first 19-storey residential building of Cyprus was chosen as an exemplar building that could be transformed into zero energy building.
The simulation of the Olympic Residence was significant as no similar studies relate to the development of this type of building. The results have significant implications for the Cyprus building sector and contribute to the knowledge related to this type of building in hot climates. Moreover, the project target of converting the building into a ZEB was extremely challenging and may be an example for future building conversion.
The building has a ground floor consisting of shops, restaurants, cafeterias, a lobby/reception area/atrium and offices and 19 floors with 4 apartments on each floor. The total building floor area is 10572.39 m2 and the total volume 32208.79 m3 (Figure 102).
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Figure 102: The Olympic residence buildings. [178]
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During the simulation three different scenarios (the Base case study, the Refurbishment case study and the Best Practice case study) were developed in order to analyse the options related to construction materials, insulation, glazing, shading internal and external factors, HVAC systems, solar heating, photovoltaic systems, climate and microclimate effect, future weather predictions and building orientation.
In order to achieve the target, the simulation analysis included 14 tests with a range of varied parameters. Each test comprised different scenarios involving the parameters being examined concluding with the best scenario (related to energy efficiency) being chosen. The final objective was to minimize the energy consumption (total yearly energy consumption and total yearly energy consumption) per floor of the building.
The project development was based on the Implementation of the EPBD in Cyprus in November 2010 [168] and all the comparisons were made according to the reference building U-values (Table 52).
Table 52: Predetermined U values for the reference building. [168]
The technical characteristics of the construction materials (outside to inside layers) and simulation values for the Olympic residence were provided by the Cyprus Scientific and Technical Chamber (ΕΤΕΚ), the Department of Town Planning and Housing (DTPH) Cyprus authorities and the construction company. [168][169]
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10.2. Olympic Residence building –Base case study
The technical characteristics of the construction materials (from IES program database) (construction layers outside to inside) are given in Table 53.
Table 53: Olympic Residence building (Base case study scenario) construction input simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Residential building (Olympic Residence) –Base case study
1 External Wall 0.32 0.52 0.04 0.13 1.42 2 Internal Partitions 0.09 0.42 0.13 0.13 1.48 3 Ground 1.75 1.44 0.04 0.17 0.61 contact/exposed floors 4 Ground - - - - - contact/exposed floors to air 5 Internal 0.63 0.67 0.10 0.10 1.15 Ceilings/Floors 6 Roofs 0.59 0.75 0.04 0.10 1.12
a/a Description - Construction U-value Net U-value Outside surface inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows 0.01 5.57 5.28 0.04 0.13 Store Windows External Windows 0.02 2.82 2.81 0.04 0.13 Office Windows
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 1.0 1.0 0.0
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 2.0 2.0 2.2 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 0.5 10 60 served by apacheHVAC
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The following assumptions were made during the simulation procedure:
1. Windows remained closed during the simulation. 2. The HVAC system was controlled by sensor in each room so the internal temperature was stable at 21 degrees for heating and 24 degrees for cooling. 3. The weather file data referred to Larnaca (data from meteorological station of Cyprus) and was based on the meteorological station of Larnaca Airport.
See Appendix I for the input simulation data and detailed simulation results of the Residential building - Best Practice case study.
10.2.1. Olympic Residence building -Base case study results analysis
A detailed comparison (Percentage Difference) between the Reference building U-values and the Olympic residence Base case study shows that all the U-values of the base case study were higher except for the ground floor and apartment windows U-value which are lower than the reference building. The input data shown in Table 53 and the results highlight the need for essential construction improvements of building elements for achieving lower U- values and improved building energy performance.
The total annual energy consumption was 1571.5 MWh and the total annual energy consumption per floor area was 148.6 kWh/m2. The peak load for heating was in January (112.1 MWh) and the peak load for Cooling was in August (48.6 MWh). The total heating energy demand was 589.6 MWh per year and the total cooling demand was 198.1 MWh per
year. The Total carbon dioxide emissions (yearly) were 812,461.9 kgCO2 where the total
system emissions were 584,717.2kgCO2, the light total emissions were 111,392.5kgCO2 and
the equipment total emissions were 116,352.3kgCO2.
The simulation weather file was based on Larnaca where the mean dry-bulb temperature was in August (31.15o C) and the mean dry-bulb temperature was in January (15.45 o C). According to the weather data, heating demand is high from mid-November to March and cooling demand is high from the end of April to the end of October. The heating demand shown in graphs from April to October was due to the hot water demand being met by boilers. The lack of solar hot water systems increased the heating energy demand (related to hot water) and at the same time affected heating demand in spring and summer. On the other hand, the cooling demand from November to April can be explained by the Cyprus weather.
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Even in winter in Cyprus there is considerable sunshine and in the base case study the lack of shading factors combined with the permanently closed windows increased the indoor temperature. This may occur where the glazing area is large and the solar radiation penetrates and affects the internal space. The cooling sensor set at 24o C detected this slight increase in internal temperature and the cooling system was set in operation.
The cooling and heating systems used electricity to cover the building’s needs. The peak system electricity load was high during winter and summer and low during spring and autumn. The wide fluctuations of the system power (electricity) were directly affected by outdoor rising and falling temperatures due to the lack of insulation measures and system operation profiles.
The results of the Base case study building confirmed the theoretical research concerns about the need for building improvement in Cyprus as the “old method” of construction failed to meet the European energy targets for buildings. Furthermore, the Base case study also revealed the need for the refurbishment of “old” buildings as the current values of the Base case study represent the old ''way'' of construction and use of materials.
10.3. Olympic Residence building –Refurbishment case study
The Refurbishment case study improved the energy performance of the residential building through application of energy efficient measures to the construction and the use of energy efficient systems (for heating and cooling). The technical characteristics of the construction materials (from IES program database) (construction layers outside to inside) are given in Table 54.
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Table 54: Olympic Residence building (Refurbishment case study scenario) construction input simulation values
a/a Description - Construction R-value Outside surface Inside surface U-value construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Residential building (Olympic Residence) –Refurbishment case study
1 External Wall 0.35 2.03 0.04 0.13 0.45 2 Internal Partitions 0.09 1.92 0.13 0.13 0.46 3 Ground 1.72 2.07 0.04 0.17 0.29 contact/exposed floors 4 Ground - - - - - contact/exposed floors to air 5 Internal 0.64 1.48 0.10 0.10 0.60 Ceilings/Floors 6 Roofs 0.62 1.92 0.04 0.10 0.48
a/a Description - Construction U-value Net U-value Outside surface Inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows 0.04 2.54 2.57 0.04 0.13 Store Windows External Windows 0.028 2.61 2.63 0.04 0.13 Office Windows
a/a Description - heating Type of system Fuel Seasonal efficiency Sensible Heat recovery /cooling systems Coefficient of Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 2.5 2.0 0.5
a/a Description - heating Type of system Fuel Nominal effective Seasonal Energy System /cooling systems exchange rate Efficiency Ratio Seasonal (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 2.5 2.5 2.6 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 0.5 10 60 served by apacheHVAC Solar panels 260 m2 sun exchanger 10 60 effectiveness 0.40
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The following assumptions were made during the simulation procedure:
1. Windows remained closed. 2. The HVAC system was controlled by sensor in each room so the internal temperature was stable at 21 degrees for heating and 24 degrees for cooling. 3. The weather file data referred to Larnaca (data collected from meteorological station of Cyprus) and was based on the meteorological station of Larnaca Airport.
The input simulation data and detailed simulation results of the Residential building - Best Practice case study can be found in Appendix I.
10.3.1. Olympic Residence building -Refurbishment case study results analysis
As previously mentioned, the aim of the Refurbishment case study was to investigate the disparity between the new and old building stock (buildings constructed at a time when energy regulations were non-existent) and to propose a solution for these buildings. The main aim of this case study was the energy reduction of the building and operational improvement with minimal changes to the building.
As the Refurbishment case study included system improvement, the “old” HVAC systems were replaced with newer energy efficient systems resulting in a reduction in energy demand for heating and cooling. Compared to the Base case study, the improvement was a 27.5% decrease for the cooling system and a 71.5% decrease in energy demand for the heating system.
The total annual energy consumption was 1147.1MWh and the total annual energy consumption per floor area was 108.5 kWh/m2. The peak load for heating was in January (32.2 MWh) and the peak load for cooling was in August (33.7 MWh). The total heating energy demand was 167.7 MWh per year and the total cooling demand was 143.5 MWh per
year. The total carbon dioxide emissions (yearly) were 593,033.9kgCO2 where the total
system emissions were 322,049.4kgCO2, the light total emissions were 128,710.3kgCO2 and
the equipment total emissions were142,274.3kgCO2.
The comparison between the Base case study and the Refurbishment case study showed that the improvements resulted in an annual energy reduction of 26.98% and a reduction of 26.98 % on total yearly energy consumption per floor area.
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The simulation weather file was based on Larnaca where the mean dry-bulb temperature was in August (31.15o C) and the mean dry-bulb temperature was in February (15.45 o C). According to the weather data, the heating demand is high from mid-November to mid-April and the cooling demand is high from May to November. The decrease (almost to zero) in heating demand from May to mid-November is due to the use of solar panels for hot water and of operation profiles for the HVAC systems. The cooling demand from November to March was due to the increase in internal temperature from sun radiation. The insulation of the building contributed negatively to this as the insulation measures aimed to maintain the indoor temperature and the temperature increase from sun radiation affected the cooling demand during the winter. However, the general profile of the cooling demand presented a highly significant 27.5% decrease. Maintaining constant temperatures during winter and summer was an issue for the project but the purpose was the reduction of energy and not the accurate optimization of cooling or heating demands.
10.4. Olympic Residence building –Best Practice case study (new buildings)
The Best Practice case study (new buildings) complies with the new construction and energy efficiency regulations. Furthermore, all HVAC systems were based on new technological systems that afforded lower energy consumption for the building’s needs. This case study is based mainly on new building construction where the new energy regulations are compulsory.
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Table 55: Olympic Residence building (Best Practice case scenario) construction input simulation values
a/ Description - Construction R-value Outside surface Inside surface U-value a construction thickness (m) (m2K/W) resistance (m2K/W) resistance (W/ m2K) (m2K/W) Residential building (Olympic Residence) – Best Practice case study
1 External Wall 0.45 6.01 0.03 0.12 0.16 2 Internal Partitions 0.14 4.24 0.12 0.12 0.22 3 Ground 0.92 0.84 0.04 0.17 0.19 contact/exposed floors 4 Ground 1.82 4.00 0.30 0.16 0.18 contact/exposed floors to air 5 Internal 0.72 4.75 0.10 0.10 0.20 Ceilings/Floors 6 Roofs 0.69 5.01 0.11 0.11 0.19
a/a Description - Construction U-value Net U-value Outside surface inside surface windows thickness (m) (Glass only) (including frame) air-film resistance air-film construction (W/ m2K) (W/ m2K) (m2K/W) resistance (m2K/W) 7 External Windows 0.044 1.48 1.69 0.03 0.12 Store Windows External Windows 0.054 1.51 1.71 0.03 0.12 Office Windows
a/a Description - Type of system Fuel Seasonal efficiency Sensible Heat recovery heating /cooling Coefficient of systems Performance (SCoP kW/kW)
8 Heating Fan coil systems electricity 3.5 4.0 1.0
a/a Description - Type of system Fuel Nominal effective Seasonal Energy System heating /cooling exchange rate Efficiency Ratio Seasonal systems (Nominal EER (SEER kW/kW) Energy kW/kW) Efficiency Ratio (SSEER kW/kW)
9 Cooling Cooling/ventilatio electricity 3.5 3.5 4.0 n mechanism Air conditioning
a/a Description - water Type of system Fuel Boiler delivery Mean Cold water Hot water boiler efficiency inlet temperature supply (oC) temperature set (oC)
10 Hot water (DHW) was electricity 1.0 10 60 served by apacheHVAC Solar panels 360 m2 sun heat exchanger 10 60 effectiveness was 0.40
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The store and office windows are covered by external shading –louvres and internal shading- blinds all operated with profiles. For this reason summer and winter operation profiles were created in order to offer the best possible performance for the building needs. In winter (February) the louvres and blinds were switched off and in March they were on every day from 12 to 2 p.m. For April the louvres and blinds operated from 9 a.m. to 4 p.m. every day and from May to October they were set continuously to allow only sunlight to pass into the building. In November the louvres and blinds were set from 11 a.m. to 3 p.m. every day and in December they were set from 12 to 2 p.m. every day.
The following assumptions have been made during the simulation procedure:
1. Windows remained closed during the simulation. 2. The HVAC system was controlled by sensor in each room so the internal temperature remained stable at 22 degrees for heating and 24 degrees for cooling.
The input simulation data and the detailed simulation results of the residential building - Best Practice case study is shown in Appendix I.
10.4.1. Renewable energy-Photovoltaic systems
Since the aim of the Best Practice case study is to develop a design for a zero energy building, the best option for minimizing or eliminating electricity demand was to install renewable energy systems on the building roof. Available insulation materials, construction methods and energy efficient systems were used to minimize the building’s energy demand, so the next step was to install photovoltaic systems to cover the building’s energy requirements. The choice of photovoltaics is explained in Chapter 8 - single family house case study in subsection 8.5.1. Renewable energy-Photovoltaic systems.
Although the optimization procedure for a photovoltaics area returned an energy self- sufficient residential building with energy demand fully covered by the installation of photovoltaics, a major issue regarding the PV area was the available space on the building for the systems’ installation. Due to the building’s predicted high energy demand, the PV area required was extremely large in relation to the available roof area. As the installation of the PV systems on the building was not an aim of this research, it was assumed that there was available space to install the PV systems. This area could be the shading systems- louvres or the glazing of the building combined with the available roof space.
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Another recently introduced option was the installation of PV systems in an available area beside or near the building and the transfer of the produced energy to the building.
During the optimization of PV factors monocrystalline silicon photovoltaics were used with PV module nominal efficiency 0.17, reference irradiance for NOCT 1000W/m2 and PV area 4700m2. This combination produced a surplus of energy 1.2 MWh per year which can be used from the grid for other purposes or to cover other energy needs (Figure 104).
Figure 103: The photovoltaics system installation settings
975 0.18 950 925 900 875 850 0.16 825 800 775 750 0.14 725 700 675 650 625 0.12 600 575 550 525 0.1 500 475 450 425 0.08 400 375 350 325 300 0.06 275 250 eficiency nominal PVmodule 225 Total Energy Consumption( MWh) 200 0.04 175 150 125 100 75 0.02 50 25 0 -25 0 0 30 60 120 240 800 2400 2800 3200 3600 4000 4900 4700 Area of PV systems Total Energy Consumption( MWh) PVmodule nominal eficiency
Figure 104: Area Optimization of the PV systems
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Table 56: Photovoltaic system input data
Tests PV type PV module Reference PV area Total yearly nominal irradiance for m2 energy efficiency NOCT (W/m2) consumption of the house (MWh) Test 1 Monocrystalline silicon 0 - 0 962.1 Test 2 Monocrystalline silicon 0.13 800 30 957.6 Test 3 Monocrystalline silicon 0.15 800 60 944.1 Test 4 Monocrystalline silicon 0.15 800 120 910.0 Test 5 Monocrystalline silicon 0.15 800 240 894.5 Test 6 Monocrystalline silicon 0.15 1000 800 710.4 Test 7 Monocrystalline silicon 0.17 1000 2400 456.2 Test 8 Monocrystalline silicon 0.17 1000 2800 350.2 Test 9 Monocrystalline silicon 0.17 1000 3200 330.3 Test 10 Monocrystalline silicon 0.17 1000 3600 243.5 Test 11 Monocrystalline silicon 0.17 1000 4000 163.8 Test 12 Monocrystalline silicon 0.17 1000 4900 -15.8 Test 13 Monocrystalline silicon 0.17 1000 4700 -1.2
All the values used by the project for the simulation procedure were the result of research and collaboration with the Energy Service of the Ministry of Commerce, Industry and Tourism, which has the overall responsibility for Energy in Cyprus. [168][169][173]
10.4.2. Orientation and height effect of the Best Practice case study
The building orientation and the different storeys were studied in order to determine the influence of the height and orientation of the flats on energy consumption but the analysis of 19 floors - each storey having 4 flats - was not possible due to time constraints. The project therefore analysed the orientation impact on energy with 90o rotation of the building (Figure 105). On the other hand, the impact of different height floors was studied for a selection of different floors and the flats on floors one, five, ten, fifteen and nineteen were selected for detailed analysis (Figure 106). Detailed simulation results and graphs for orientation and height effects of the Residential building can be found in Appendix I.
Figure 105: Initial and final orientation of the Residential Building
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Figure 106: Olympic Residence IES model and the selected floors-3D and floor plan
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All the simulation parameters (construction, system parameters and weather file) remained the same while only the orientation of the Olympic residence building changed. The building was turned 90o and the main entrance of the building changed from south facing to west facing (Figure 105).
4800 4.0 4600 4400 4200 4000 3800 3600 3.0 3400 3200 3000 2800 2600 2400 2.0 2200
2000 Orientation 1800 1600 Total energy (kWh) 1400 1200 1.0 1000 800 600 400 200 0 0.0
Total Cooling (kWh) Total Heating (kWh) Orientation
Figure 107: Comparison of the total heating and cooling energy demand (kWh) for height effect impact, where number 1 is South-West orientation, number 2 is East-West orientation, number 3 is West-North orientation and number 4 is North-East orientation. The orientation and height effect were studied during the project development. The initial position of the building was south where the long axis of the building runs east to west. The orientation impact was analysed by turning the building 90o clockwise. Floors one, five, ten, fifteen and nineteen had been chosen for closer study. Apartment number one from south- west facing became west-north facing and presented an increasing tendency of heating demand for all the floors. On the other hand, the cooling demand was reduced for November to March and presented a slight decrease from May to October. Apartment number two from east-south facing became south-west facing and presented a significant decrease of heating demand for all floors. It should be stressed that only in April was the heating demand higher compared to the original orientation. The cooling demand slightly increased from November to March and remained the same from April to October.
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Apartment number three changed from west-north facing to north-east facing and presented a small reduction of heating demand for all the floors. The cooling demand showed a minor increase for March, April and November and remained the same from May to October compared with the original position. Apartment four changed from north-east facing to south- east facing and showed a significant decrease in heating demand for all the apartments. The cooling demand from April to September remained the same compared to the initial position and for October and November the cooling demand increased slightly.
The impact of height effect was analysed for the Olympic Residence Building. The influence on energy (heating and cooling demand) is based on the analysis of floors one, five, ten, fifteen and nineteen with the energy performance of each apartment being analysed separately. Apartment number one with a south-west orientation had the same heating consumption as floors one and five, a reduction for floor ten, a slight increase for floor fifteen and a higher consumption for floor nineteen. The cooling demand from October to April remained almost the same for all floors except floor nineteen where the cooling demand decreased significantly. From June to September the cooling demand was higher for floors one and nineteen. Apartment number two with an east-west orientation presented the same profile of heating and cooling demand. However, from November to March the cooling demand of floor ten was higher than that of the other floors. Apartment number three with a west-north orientation had same heating demand as all the floors except floor nineteen where the heating demand was significantly higher. The cooling demand was the same for all the floors from November to March but in April floor nineteen had a lower cooling demand than the other floors. From May floor nineteen had a significant increase in cooling demand and from June to October the cooling demand was higher for floors one and nineteen. Apartment number four with a north-east orientation had a lower heating demand for floor one and a higher heating demand for floor nineteen. Floors five, ten and fifteen all had the same heating demand from November to April. From May to October the cooling demand was higher for floors one and nineteen. In November and April floor one had a higher cooling demand than the other floors.
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Table 57: Total heating demand Comparison between the selected floors
Heating demand (kWh) Flat 1 Floor Flat 1 Flat 1 Flat 1 Flat 1 1 Floor 5 Floor 10 Floor 15 Floor 19 Flat 1 Floor 1 0% 1% -13% -2% 159% Flat 1 Floor 5 1% 0% -14% -2% 157% Flat 1 Floor 10 15% 16% 0% 13% 198% Flat 1 Floor 15 2% 2% 12% 0% 164% Flat 1 Floor 19 61% 61% 66% 62% 0%
Flat 2 Floor Flat 2 Floor 5 Flat 2 Floor 10 Flat 2 Floor 15 Flat 2 Floor 19 1 Flat 2 Floor 1 0% 2% 7% 1% 83% Flat 2 Floor 5 -2% 0% -8% 1% 80% Flat 2 Floor 10 8% 9% 0% 8% 97% Flat 2 Floor 15 1% 1% 8% 0% 82% Flat 2 Floor 19 45% 44% 49% 45% 0%
Flat 3 Floor Flat 3 Floor 5 Flat 3 Floor 10 Flat 3 Floor 15 Flat 3 Floor 19 1 Flat 3 Floor 1 0% 1% 0% 1% 77% Flat 3 Floor 5 1% 0% 0% 0% 78% Flat 3 Floor 10 0% 0% 0% 0% 78% Flat 3 Floor 15 1% 0% 0% 0% 78% Flat 3 Floor 19 44% 44% 44% 44% 0% Flat 4 Floor Flat 4 Floor 5 Flat 4 Floor 10 Flat 4 Floor 15 Flat 4 Floor 19 1 Flat 4 Floor 1 0% 35% 33% 34% 143% Flat 4 Floor 5 26% 0% 1% 1% 80% Flat 4 Floor 10 25% 1% 0% 1% 82% Flat 4 Floor 15 25% 1% 1% 0% 81% Flat 4 Floor 19 59% 44% 45% 45% 0%
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Table 58: Total Cooling demand comparison between the selected floors
Cooling Demand (kWh) Flat 1 Floor 1 Flat 1 Floor 5 Flat 1 Floor 10 Flat 1 Floor 15 Flat 1 Floor 19 Flat 1 Floor 1 0% -3% -2% -3% 33% Flat 1 Floor 5 3% 0% 1% 0% 37% Flat 1 Floor 10 2% -1% 0% -1% 35% Flat 1 Floor 15 3% 0% 1% 0% 36% Flat 1 Floor 19 -25% -27% -26% -27% 0%
Flat 2 Floor 1 Flat 2 Floor 5 Flat 2 Floor 10 Flat 2 Floor 15 Flat 2 Floor 19 Flat 2 Floor 1 0% -5% -2% -4% 26% Flat 2 Floor 5 5% 0% 3% 0% 32% Flat 2 Floor 10 2% -3% 0% -3% 28% Flat 2 Floor 15 5% 0% 3% 0% 31% Flat 2 Floor 19 -21% -24% -22% -24% 0%
Flat 3 Floor 1 Flat 3 Floor 5 Flat 3 Floor 10 Flat 3 Floor 15 Flat 3 Floor 19 Flat 3 Floor 1 0% -4% -4% -4% 32% Flat 3 Floor 5 4% 0% 0% 0% 38% Flat 3 Floor 10 4% 0% 0% 0% 38% Flat 3 Floor 15 4% 0% 0% 0% 37% Flat 3 Floor 19 -24% -27% -27% -27% 0%
Flat 4 Floor 1 Flat 4 Floor 5 Flat 4 Floor 10 Flat 4 Floor 15 Flat 4 Floor 19 Flat 4 Floor 1 0% -7% -7% -7% 45% Flat 4 Floor 5 8% 0% 0% 0% 56% Flat 4 Floor 10 7% 0% 0% 0% 56% Flat 4 Floor 15 7% 0% 0% 0% 56% Flat 4 Floor 19 -31% -36% -36% -36% 0%
Table 57 shows the total heating demand comparison between selected floors and the percentage difference while Table 58 shows the total cooling demand comparison between selected floors and the percentage difference. Generally floor nineteen had a higher cooling and heating demand than the other floors. The floor comparison presented higher percentages for heating demand and lower for cooling demand, especially for floor nineteen. The top floor appeared to need a more detailed study as the heating and cooling performance was significantly different from that of other floors due to the fact that the top floor had an extra surface (roof) exposed to the external environment conditions.
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10.4.3. Olympic Residence building -Best Practice case study results analysis
The Best Practice case study represents the construction of buildings according to the new European energy regulations. The Implementation of the EPBD in Cyprus was the first to require thermal insulation in Cyprus buildings’ envelope and the EPBD also set minimum energy performance requirements for new buildings, both residential and commercial.[168][169] The Best Practice case study is based on these standards for development o the project, but further measures were also taken to achieve the initial target of zero energy buildings.
Table 59: U-value comparison between the Reference Building and the Office Best Practice case study
Exposed elements Reference building Best Practice case Reduction of U-value study U-value (W/ m2K) U-value (%) (W/ m2K) Roofs 0.6375 0.1944 69.577.5 Walls 0.7225 0.1622 77.5 Internal Partitions / 0.2234 - Floors/ceilings 0.6375 0.2013 68.4 Ground floor 1.6 0.1804 88.7 Windows (store) 3.23 1.6907 47.6 Windows (apartment) 3.23 1.7122 47.0
Construction improvements in the Best Practice case study significantly reduced the U-values of the building while simultaneously improving the building energy performance. All building elements U-values were lower compared to reference building and therefore responded not only to current but also to future energy regulations.
The Best Practice case study included further system improvements compared with Refurbishment and Base case studies. New more energy efficient systems replaced the previous HVAC systems resulting in decreased energy demand for heating and cooling. Compared to the Base case study the improvement was 100 % for the cooling system and 250% for the heating system. Compared to the Refurbishment case study, the improvement was 40% for both the cooling and heating systems. The systems’ efficiency had a significant impact on the reduction of energy demand for maintaining indoor comfort temperatures.
The total annual energy consumption was 962.1 MWh and the total annual energy consumption per floor area was 91.0 kWh/m2. The peak load for heating was in February (10.0 MWh) and the peak load for Cooling was in August (17.9 MWh).
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The total heating energy demand was 59.9 MWh per year and the total cooling demand was
80.5 MWh per year. The Total carbon dioxide emissions (yearly) were 497,417.3kgCO2
while the total system emissions were 226,432.7kgCO2, the light total emissions were
128,710.3 kgCO2 and the equipment total emissions were 142,274.3kgCO2. The comparison between the Base case study and the Best Practice case study showed that the improvements gave rise to an annual energy reduction of 38.76% and a reduction in Total Yearly Energy Consumption per Floor Area of 38.76%. The comparison between the Refurbishment case study and the Best Practice case study showed that the improvements resulted in a yearly energy reduction of 16.13% and a reduction in Total Yearly Energy Consumption per Floor Area of 16.13%.
The simulation weather file is based on Larnaca where the mean dry-bulb temperature was in August (31.15 o C) and the mean dry-bulb temperature was in February (15.45 o C). According to the weather data, the heating demand is high from late November to late March and the cooling demand is high from May to November. The decreased (almost to zero) heating demand from May to mid-November is due to the use of solar panels for hot water, better boiler efficiency and the use of operation profiles for the HVAC systems. The use of shading systems and operation profiles for the HVAC systems contributes positively to energy reduction for cooling and heating. Sun penetration into the indoor space at unnecessary times was minimized by the use of shading systems (external shading system controlled by operation profiles).
The systems, cooling and heating, used electricity to meet the building’s needs. The peak system electricity load was high in summer and low in winter, spring and autumn. The fluctuations of the system power (electricity) were not as extreme as in the Base and Refurbishment case studies due to further improvements of the systems operation and the improved response to the outdoor changes. In general, the use of system electricity fell significantly and thus the building energy needs could easily be covered by renewable energy systems.
In addition, the Best Practice case study investigated the installation of the photovoltaics system on the Olympic Residence building. The main goal was the transformation of the building into a zero energy building where the building’s needs would be covered by a locally renewable system. The optimization procedure of a PV area, PV module nominal efficiency and Reference irradiance for NOCT (W/m2) returned a zero energy building where
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the 4700m2 of photovoltaic system covered the building’s energy needs. Moreover, the minimum PV area offers 1.2 MWh per year surplus of energy. The PV type was monocrystalline silicon with a PV module nominal efficiency 0.17 and the Reference irradiance for NOCT was 1000 W/m2.
The Best Practice case study combined with renewable systems (photovoltaics system) confirmed that the goal of a zero energy building is achievable. The only aspect not included in this project was the cost of this solution which plays a vital role in final decisions. However, the cost of the solution was an issue that needs to be thoroughly examined in order to compare the investment with depreciation time. This subject was not relevant to the research in hand as the goal was the achievement of a zero energy building in a hot climate country.
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10.5. Comparison of the three case studies
Table 60: Comparison of the three case studies
Parameters Base case study Refurbish case Best Practice case Comparison Comparison Comparison (1) study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%) Construction:
External wall U-value (W/m2K) 1.42 0.45 0.16 68.3 90.8 71.1 Internal Partitions U-value (W/m2K) 1.48 0.46 0.22 68.9 85.1 52.2 Ground/Exposed Floors U-value 0.61 0.28 0.18 54.1 70.5 35.7
(W/m2K) Internal Ceiling/Floor U-value 1.15 0.59 0.20 48.7 82.6 66.1 (W/m2K) Roofs U-value (W/m2K) 1.12 0.48 0.19 57.1 83.0 60.4 Store Glazing U-value (W/m2K) 5.29 2.57 1.63 51.4 69.2 37.8 Apartments Glazing U-value (W/m2K) 2.81 2.62 1.65 7.1 41.5 37.0
Heating system:
Fuel Electricity Electricity Electricity - - - Seasonal Efficiency 1.0 2.5 3.5 150 250 40 SCoP kW/kW 1.0 2.0 4.0 100 300 100 Vent. heat recovery effectiveness 0.0 0.5 1.0 - - 5025 Vent. Heat recovery return air temp. 0.0 21.0 oC 21.0 oC - - -
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Parameters Base case study Refurbish case Best Practice case Comparison Comparison Comparison (1) study(2) study(3) 1&2* (%) 1&3*(%) 2&3*(%) Cooling systems: Mechanism Air conditioning Air conditioning Air conditioning - - -
Fuel Electricity Electricity Electricity - - - Seasonal EER kW/kW 2.0 2.5 3.5 25.0 75.0 40 SSEER kW/kW 2.0 2.6 4.0 30.0 100 53.84 Heat rejection (% of rejected heat) 2.2 10 15 - - - Hot Water: Served by ApacheHVAC boiler Yes Yes YES - - - DHW delivery efficiency 0.50 0.50 1.0 - 100 100 Mean cold water inlet temperature 10oC 10oC 10oC - - - Hot water supply temperature 60oC 60oC 60oC - - - Solar water system: Area m2 - 260 300 Heat exchanger effectiveness 0.0 0.4 0.4 - - - Total Yearly Energy Consumption 1571.5 MWh 1147.1 MWh 962.1 MWh 26.98(-)** 38.76(-)** 16.13(-)** Total Yearly Energy Consumption per 148.6 kWh/m2 108.5 kWh/m 2 91.0 26.98(-)** 38.76(-)** 16.13(-)** Floor Area kWh/m 2 *Comparison between the Case studies and Percentage Change between the parameters,**(-)=reduction of energy
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120 110 100 90 80 70 60 50 40 Systems Energy Systems Energy (MWh) 30 20 10 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 108: Monthly system energy comparison for the three case studies-Heating systems
100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25%
Heating Energy Energy Consumption Heating 20% 15%
Percentage Reduction (%) ofMonthly Reduction Percentage 10% 5% 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case 71% 69% 72% 62% 79% 83% 84% 83% 76% 66% 68% 70% study Compare Base with Best Practise case 91% 90% 91% 85% 89% 91% 91% 91% 89% 85% 88% 91% study Compare Refurbish with Best Practise 69% 67% 69% 61% 47% 46% 46% 49% 55% 56% 63% 68% case study
Figure 109: Percentage Reduction (%) of Monthly Heating Energy Consumption
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52 50 48 46 44 42 40 38 36 34 32 30 28 26 24 22 20 18 Systems Energy (MWh) 16 14 12 10 8 6 4 2 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 110: Monthly system energy comparison for the three case studies-Cooling systems
100% 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30%
Energy Consumption Consumption Energy 25% 20% 15% 10% 5% 0% Percentage Reduction (%) of Monthly Cooling Cooling of Monthly (%) Reduction Percentage Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Compare Base with Refurbish case 35% 35% 29% 18% 20% 35% 32% 31% 35% 30% 19% 17% study Compare Base with Best Practise case 71% 76% 59% 48% 52% 65% 64% 63% 65% 58% 34% 56% study Compare Refurbish with Best Practise 55% 64% 42% 36% 41% 46% 47% 47% 45% 39% 19% 47% case study
Figure 111: Percentage Reduction (%) of Monthly Cooling Energy Consumption
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Generally, comparison of these case studies showed that the Best Practice case study achieved larger reductions of energy compared to the Refurbishment case study. Comparing the Best Practice with the Refurbishment case study, the greater heating energy reduction (related only to space heating) was presented in January (69%) and the lower in October (56%). A considerable reduction in the cooling demand (46-47%) was achieved for the summer period (from June to August) when there is an actual need for cooling. However, the scenario of refurbishment cannot be ignored as many Cypriot buildings were constructed before the introduction of the new energy regulations. There is a need to develop a methodology for refurbishing buildings to increase their energy efficiency and bring them closer to being Low energy buildings. However, building refurbishment can be problematic as there are often limitations on the use of available solutions, techniques and materials
80,000.00
70,000.00
60,000.00
50,000.00 Emissions 2 CO 40,000.00
30,000.00
20,000.00
10,000.00
0.00 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 112: Monthly CO2 emissions comparison for the three case studies
The monthly CO2 system emissions comparison shows that the Base case study had higher emissions and the Best Practice case study lower emissions. System emissions are related to energy consumption and therefore as the energy demand of the building was reduced the emissions were also reduced.
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1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 0.9
Peak Room Conditioning Loads (kW) Loads Conditioning Room Peak 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1st room 1 1st room 2 1st room 3 1st room 4 1st room 5 1st room 6 1st room 7 1st room 8 1st room 9 4th room 2 4th room 3 4th room 4 4th room 5 4th room 6 4th room 7 4th room 8 4th room 9 5th room 1 5th room 2 5th room 3 5th room 4 5th room 5 5th room 6 5th room 7 5th room 8 5th room 9 6th room 1 6th room 2 6th room 3 6th room 4 6th room 5 6th room 6 6th room 7 6th room 8 6th room 9 4th room 1 3rdroom 1 3rdroom 2 3rdroom 3 3rdroom 4 3rdroom 5 3rdroom 6 3rdroom 7 3rdroom 8 3rdroom 9 2nd room 1 2nd room 2 2nd room 3 2nd room 4 2nd room 5 2nd room 6 2nd room 7 2nd room 8 2nd room 9 1st room 10 5throom 10 4th room 10 6th room 10 3rdroom 10 2nd room 10
Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 113: Heating Peak Room Conditioning Loads (kW) and Building Orientation: 1st -6th floor
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1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 0.9 0.8 0.7 Peak Room Conditioning Loads (kW) Loads Conditioning Room Peak 0.6 0.5 0.4 0.3 0.2 0.1 0 7th room 1 7th room 2 7th room 3 7th room 4 7th room 5 7th room 6 7th room 7 7th room 8 7th room 9 8th room 1 8th room 2 8th room 3 8th room 4 8th room 5 8th room 6 8th room 7 8th room 8 8th room 9 9th room 1 9th room 2 9th room 3 9th room 4 9th room 5 9th room 6 9th room 7 9th room 8 9th room 9 7th room 10 8th room 10 9th room 10 10th room 1 10th room 2 10th room 3 10th room 4 10th room 5 10th room 7 10th room 8 10th room 9 11th room 1 11th room 2 11th room 3 11th room 4 11th room 5 11th room 6 11th room 7 11th room 8 11th room 9 12th room 1 12th room 2 12th room 3 12th room 4 12th room 5 12th room 6 12th room 7 12th room 8 12th room 9 10th room 10 11th room 10 12th room 10
Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study Linear (Olympic residence Best Practise case study)
Figure 114: Heating Peak Room Conditioning Loads (kW) and Building Orientation: 7st -12th floor
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Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 115: Heating Peak Room Conditioning Loads (kW) and Building Orientation: 13st -19th floor
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Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 116: Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 1st -6th floor
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Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 117: Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 7st -12th floor
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Olympic residence Base case study Olympic residence Refurbish case study Olympic residence Best Practise case study
Figure 118: Cooling Peak Room Conditioning Loads (kW) and Building Orientation: 13st -19th floor
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An important feature of the Olympic residence was the building floor energy analysis, the Peak room conditioning loads (kW). The general picture from the graphs (Figure 113, Figure 114 and Figure 115 heating peak room conditioning loads (kW) and building orientation) was the fact that the energy measures of the Best Practice case study achieved significant reductions in heating and cooling peak room conditioning loads (kW). The reduction of cooling peak room conditioning loads was greater than the Base–Refurbishment case study and the Refurbishment- Best Practice case study. It should be mentioned that room 8 had a higher demand for heating and cooling because it is larger than the other rooms.
10.6. Weather- Microclimate Effect
The weather and microclimate effect were analysed during the project development in order to study their impact on energy consumption of the Olympic Residence. The Olympic Residence Best Practice case study was simulated with different locations of Cyprus and with a different weather file each time. By keeping all other factors constant and changing only the simulation weather file, any increase or decrease of system energy (heating and cooling) was due to the microclimate differences between the towns. Figures 119 and 120 show the results of the simulation tests. There are significant differences between the Cyprus towns that cannot be ignored if estimation of the building energy demand is to be as accurate as possible. The graphs show that simulation based in only one town may possibly underestimate the cooling or the heating demand of the Olympic Residence.
17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 Total Energy Consumption( MWh) 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES data Larnaca 1997-2008 Limassol 1997-2008
Limassol 2000-2009 Nicosia 1997-2008 Nicosia 2000-2009
Figure 119: Heating demand and microclimate effect
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Figure 120 shows the percentage difference for the comparison between the different weather simulation files used during the simulation procedure.
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Heating 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES vs Larnaca 1997-2008 4 2 3 2 13 2 2 2 2 11 7 10 Larnaca IES vs Limassol 1997-2008 14 6 14 0 2 2 2 2 4 40 32 14 Larnaca IES vs Limassol 2000-2009 11 3 11 23 0 2 2 2 4 7 11 18 Larnaca IES vs Nicosia 1997-2008 18 11 19 6 7 2 2 2 4 40 32 17 Larnaca IES vs Nicosia 2000-2009 24 27 20 5 11 0 0 2 2 22 25 38
Figure 120: Percentage difference between the simulation weather files for heating demand
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Figure 121: Cooling demand and microclimate effect
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Figure 122 shows the percentage difference for the comparison between the different weather simulation files used during the simulation procedure.
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Figure 122: Percentage difference between the simulation weather files for cooling demand
10.7. Future Weather files
Based on the simulation weather files created during the development of the project, future weather files were constructed in order to predict the performance of the Best Practice case study- zero energy buildings in future time.
The future simulation files concerned the years 2020, 2050 and 2080. The following graphs enable engineers to predict and change, where possible, parameters that can be vital for future building performance.
The future weather analysis is based on the Best Practice case study building and used three future weather files for each town (2020, 2050 and 2080). In this way the project studied possible impacts on heating and cooling demand of the proposed Zero energy Building (Best Practice case study building) in three different locations (towns).
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10.7.1. Future Weather files- Limassol town
16 15 14 13 12 11 10 9 8 7 6 5 4 Total Energy Consumption( MWh) Consumption( Energy Total 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Limassol 1997-2008 Limassol 2020 Limassol 2050 Limassol 2080
Figure 123: Predicted heating demand and future weather files
34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 Total Energy Consumption( MWh) Consumption( Energy Total 7 6 5 4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Limassol 1997-2008 Limassol 2020 Limassol 2050 Limassol 2080
Figure 124: Predicted cooling demand and microclimate effect
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10.7.2. Future Weather files- Nicosia town
15 14 13 12 11 10 9 8 7 6 5 4 3 2 Total Energy Consumption( MWh) Consumption( Energy Total 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Nicosia 1997-2008 Nicosia 2020 Nicosia 2050 Nicosia 2080
Figure 125: Nicosia heating (predicted) demand and Future weather files
31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 Total Energy Consumption( MWh) Consumption( Energy Total 7 6 5 4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Nicosia 1997-2008 Nicosia 2020 Nicosia 2050 Nicosia 2080
Figure 126: Nicosia cooling (predicted) demand and microclimate effect
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10.7.3. Future Weather files- Larnaca town
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Total Energy Consumption( MWh) Consumption( Energy Total 5 4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES data Larnaca 1997-2008 Larnaca 2020 Larnaca 2050 Larnaca 2080
Figure 127: Larnaca Heating demand and Future weather files
30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 Total Energy Consumption( MWh) Consumption( Energy Total 5 4 3 2 1 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Larnaca IES data Larnaca 1997-2008 Larnaca 2020 Larnaca 2050 Larnaca 2080
Figure 128: Larnaca cooling (predicted) demand and Microclimate effect
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10.7.4. Weather data results
The impact of weather and microclimate on buildings’ energy consumption was a vital issue for this project. As mentioned in Chapter 6 (weather data analysis), the climate and weather data files are crucial for the accuracy of building simulation. The development of weather data files for three different towns of Cyprus and the simulation of the Best Case study under the different weather simulation files revealed invaluable information. The results from Chapter 6 indicate that differences between the weather stations observed during the simulation of the Residential building are due to the different locations and microclimate effects. The seasonal difference between mid-summer and mid-winter temperatures is approximately 19oC for Nicosia and 13oC for Limassol and Larnaca. Comparison of the results showed that heating demand is higher inland than in the coastal areas, Larnaca and Limassol. The most significant aspect of this comparison was the fact that the Larnaca IES data underestimated the heating and cooling needs for the building and the comparison highlighted the essential role of updated weather simulation files for accurate simulation results.
Most noteworthy about the weather analysis in Chapter 6 was the significant differences between the towns and, in general, between inland and coastal towns. The IES simulation program offered only one simulation file for Cyprus, the Larnaca weather simulation file, which was unable to cover the microclimate conditions of the whole island. Simulations based on only this weather file would possibly under- or overestimate the cooling and heating demand. At this point, it is essential to mention that the Cyprus Energy Service recognises four major climatological zones namely coastal, low land, semi-mountainous and mountainous areas.[174] Hence, the project confirms the need for updated weather simulation files and a specific weather simulation file for each town. The effect of weather is a major factor affecting indoor office conditions and systems operation.
Another aspect of the weather analysis in Chapter 6 was predicted estimations for the weather as well as for building performance for 2020, 2050 and 2080. According to the Chapter 6 results, Limassol is predicted to have colder winters in the future; this means an increase in residential building heating demands and summers will be hotter compared with 1997-2008 data. The heating demand for 2050 and 2080 is predicted to decrease which means that winters may be warmer at that time. Moreover, in 2080 the predicted cooling demand will be higher than the previous year which means that 2080 will present higher temperatures in general.
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For Nicosia and Larnaca there is a predicted decrease in heating requirements for 2020, 2050 and 2080 from November to January. On the other hand, the cooling demand will increase during the summer period (from June to August) and the hottest period seems to be 2080 where the cooling will be higher compared to the previous years even during the winter. The Larnaca future weather files show that the winters of 2020, 2050 and 2050 are expected to be warmer compared to 1997-2008. In comparison with the previous years, 2080 is expected to have a warmer winter and warmer summer. There will be an increasing cooling demand for all the future weather files compared with 1997-2008. Generally, there will be an increasing tendency for cooling and a decreasing tendency for heating, especially for 2080. The importance of this simulation is the fact that in future weather conditions will probably change with winters and summers becoming hotter and, as a result, Residential Building needs for cooling and heating will change. The exact degree of change is unpredictable as the changes in weather are caused not only by natural changes but also depend on human activities worldwide. It is impossible to accurately predict the impact of human activity and natural changes using mathematical models. Only conjectures about possible future changes can help engineers improve the future performance of buildings at an early stage.
The outcome of the results in Chapter 6 and the Residential Building simulation indicate that there is a direct connection between a building’s energy performance and the local climatic conditions (represented by the simulation weather data files) that cannot be ignored. In order to design a successful zero energy Residential Building and achieve the best energy performance, it is imperative to take the local weather into account.
10.8. Conclusion
Generally the analysis of the Olympic Residence building provided invaluable information about this new type of tall building and its development in the hot climate of Cyprus. The different case studies indicated significant energy differences based on the construction materials, insulation methods, HVAC systems technology, systems operation profiles, shading elements and orientation of the building. In addition, the analysis stresses the need for further more stringent energy regulations to be introduced in order for zero energy buildings to be achievable in Cyprus.
The project outcome shows that minimizing energy use through efficient building design should be a fundamental design criterion and the highest priority of all zero energy projects.
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Energy efficiency is the most cost-effective strategy with the highest return in investment, and maximizing efficiency opportunities before developing renewable energy plans will minimize the cost of the renewable energy project needed.
During the research special attention was given to energy efficiency measures including design strategies and features such as high-performance envelopes, insulation of the partitions, day- lighting, sun control and shading devices, careful selection of windows and glazing, passive solar heating, natural ventilation, and water conservation. Once building loads are reduced, the loads should be aided with efficient equipment and systems such as high-performance HVAC structures with smart system control units that offer correct management and use.
Once efficiency measures are incorporated, remaining energy needs can be satisfied through renewable energy technologies. The project examined the two cases of on-site and off-site renewable energy. After detailed theoretical research and contact with Cyprus Energy Authorities it was concluded that the common electricity generation strategies for Cyprus include photovoltaics (PV) and solar water heating. However, the project considered the options and priority was given to renewable approaches that are readily-available, replicable, and cost-effective, also taking system maintenance into account. Nevertheless, further research is needed for the life-cycle cost analysis that can be used to evaluate the economic merits of various systems over their usable lifetimes. According to the research, the development of the zero energy residential building is possible and achievable. However, technology alone is not enough and a more powerful legislative framework is needed that will methodically transform the building sector to meet the National European targets of 2020. Nevertheless, that legislative framework will need support with appropriate economic backing and powerful motivation and this in turn will involve the implementation of training/ information programs for those involved in building construction.
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Chapter 11-Discussion
11. Research summary
The project development is based on two elements, first the theoretical research and analysis of zero energy buildings and second the data analysis with building simulation, the target being to investigate theoretically designed zero energy buildings and create appropriate design strategies for ZEB.
The theoretical approach was essential as there is no exact definition of zero energy buildings in Cyprus and this approach highlighted the need for an exact definition and revealed the lack of precise methodology for transforming old and new buildings into ZEBS. The energy regulations and measures introduced after Cyprus’ accession to the EU were unable to achieve the target of zero energy buildings.
The literature review established the basis of research for this project. First it was important to identify the root of the problem, where the problem started and how the energy of buildings corresponded with the energy crisis. The building sector’s increasing energy demands due to population increase and modern lifestyles was an issue for the project. The building type-category (residential and commercial buildings) was scrutinised to determine the impact of building use on energy consumption. At an early stage the theoretical research revealed that although Office buildings (commercial buildings) were particularly difficult to apply the low energy principles to, they actually had more potential for energy saving when those principles were applied. Unfortunately, office users do not care about saving energy or using energy efficient systems while developers and investors actually impede the development of green design technologies/methods. Moreover, another important point was that single family homes have higher energy needs compared to apartments, due to their large size and space and larger exterior wall areas, so the energy profile of a single family house is much higher than that of a multifamily building.
Analysis of the Cyprus building stock showed that a large percentage was constructed years ago; hence the problem of energy reduction in the building sector had to be approached not only from the perspective of new but also from existing buildings. Thus the project had to consider options for the refurbishment of buildings to transform them into low energy buildings. Based on these findings the project development included appropriate design strategies for achieving zero energy building in Cyprus.
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As analysis of building stock showed that the single family house, the office building and the new generation residential buildings comprise the main body of Cyprus building stock, the project focused on these types of building, developing three simulation models, one for each building type.
The problem defined, the factors and parameters related to the development of the zero energy building in Cyprus needed to be identified. The interaction of the main factors such as the building construction materials, geometry, orientation, building structure and systems efficiency were recognised early on and the theoretical research indicated that the simulation weather data and microclimate bear a direct relation to the project development. The IES simulation program provided the weather simulation files but an issue for the project that these were not updated (concerning the current location only- Cyprus). Due to the weather data’s essential role in building simulation results, the project collected the necessary weather parameters for eleven years, analysed them and constructed new updated weather simulation files for three locations in Cyprus. The weather file analysis and comparison with IES data showed significant differences that cannot be ignored if results are to be accurate and correct. Non-updated weather data could have been used to conduct the project but with less precise results which may have resulted in heating and cooling demand being under- or overestimated.
The final factor affecting the success of the project was the simulation of suitable renewable energy systems in the building. After minimizing building energy demand through various energy measures, the application of renewable systems was required to cover the buildings’ minimum energy needs. Due to Cyprus’s sunny climate the solution was the development of photovoltaics on or next to the buildings. The development of other renewable systems such as wind turbines or geothermal systems is an issue for further study.
The results of the theoretical research caused a revision of the project methodology/approach resulting in an improved research structure focusing on the main points. For the practical part of the project the literature review and findings facilitated the most important part of this research, i.e. the simulation of the buildings. Moreover, the simulation results highlight essential points and reveal the gaps in energy regulation while also indicating how various factors impact on building energy consumption and highlighting aspects needing further study and development.
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This thesis investigated the development of zero energy buildings in hot climate countries with Cyprus as the case study. The investigation was based on three different types of buildings (single family house, Residential building and Office building) and on three different scenarios (Base case study, Refurbishment case study and Best Practice case study). The analysis and impact of every factor affecting building energy performance were correlated with heating and cooling demand. The building models were based on actual building plans and contained detailed modelling of the conditions and the constructions. Improvement of the building energy demand was a result of an analysis optimisation of different factors with each factor simulated in an IES program.
11.1. Input data and software settings.
Essential for accurate results are the correct input data and software settings employed by the computer producing the calculations. The following steps were taken to ensure accurate results:
1. Simulation case studies: all the buildings case studies exist and correct and accurate project development took into account the feedback from the field. Moreover, the real case studies allowed the project to meet construction teams and discuss the simulation case studies.
2. Preliminary simulation model: the preliminary simulation model created in order to check the weather data files used by the IES simulation program. By keeping all other factors and values standard and changing only the weather data file, the project checked the impact of the weather files on the building simulation. At that point the project ascertained a problem with the weather data and proceeded with data analysis and construction of the new weather data.
3. Weather data: the accuracy of the weather data and construction of updated weather files were achieved through collaboration with Cyprus Meteorological Services. During the weather analysis the project had meetings with the Meteorological authorities of Cyprus, discussed the weather conditions and collected hourly meteorological data from three different towns, Larnaca, Limassol and Nicosia. The results were discussed in detail with the Meteorological authorities and compared with other similar studies (see Chapter 6-weather data analysis).
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4. IES input data: the correct input simulation data was checked in two directions, the first being contact and meetings with engineers and construction companies of the three case studies. During the meetings with engineering teams the values used in each building were discussed and collected to be used in the simulation. In addition, the collected values were checked according to current building legislation through cooperation with Cyprus Scientific and Technical Chamber (ΕΤΕΚ) and the Department of Town Planning and Housing (DTPH) Cyprus authorities. [168][169]
5. Verification and validation of computer simulation models: the input simulation data passed the verification and validation procedures. During verification the building models tested to find and remedy errors in the implementation of the model.[179][180] The objective of model verification was to ensure that the implementation of the model is correct; this was achieved through preliminary building simulations, discussion of the results with engineers of the three case studies and by making the necessary changes. The models were checked by an expert (architecture and civil engineer) who examined the model output for reasonableness under a variety of settings of the input parameters and using an interactive debugger. The project in collaboration with case studies engineer teams used validation whereby the accuracy of the model's representation of the real system was checked. Subjective reviews were made and all necessary changes were made through the preliminary simulation procedures so as to achieve an accurate representation of the real case studies.
11.2. Important research findings
In 2020, two thirds (or possibly more) of buildings in Cyprus will be the same buildings that exist today. In all the examined case studies (family, commercial and residential building) and according to the results, achieving zero energy in existing building stock is challenging – requiring not only installation of new technology, but a shift in the decisions made during every “compelling event” in a building’s life. However, the results show that the development of new types of building, zero energy will be easier than the renovation of the old buildings stock due to existing limitations during renovation. Once a building is designed and situated in a particular location, some of its energy demand may be locked in.
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For example, its direction of exposure, window-to-wall ratios, and other structural features cannot change. Still, most other features that determine energy usage will need to be replaced at some point in the building’s life.
Based on the research results, in order to transform an existing building (whether family, commercial or residential) into zero energy, the following technologies and practices can enable the design and construction team to optimize energy performance as part of a periodic upgrade or strategic transformation of the building:
1. Installation or improvement of insulation: as there were no energy regulations and measures before Cyprus’ accession to the EU, the old building stock lacks insulation technology. Hence by renovating the envelope of the building by installing external and internal insulation, low U-values will be achieved affecting the energy performance of the building and reducing energy consumption for heating and cooling. Project results shows that external insulation effectively protects the external envelope from outdoor conditions and internal insulation maintains internal space conditions for longer.
2. Improve Heating, Ventilation and Air Conditioning systems: once the energy consumption of the building is reduced by insulation, the improvement or installation of new HVAC systems is necessary for achieving greater energy reductions. Cyprus has a hot climate and, according to the project results, the need for space cooling over a long period increases the energy consumption of the building. However, project results conclude with the following important points needing to be considered at this stage: a. upgrade/modernize new equipment as needed. b. optimize all building systems, updating thermostat set-points, rebalancing the air-handling system, and tuning up mechanical equipment so that the system performs as originally designed. c. install digital controls infrastructure, smarter energy management systems and advanced energy analytics. d. add heat pumps where possible e. install radiant heating and cooling systems.
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3. Install new, high efficiency windows: windows are an important element of the building envelope. The only problem during renovation is the restriction in some cases of window-to-wall ratios. Changing the windows offers two advantages: first the improvement of the building lighting and reduction of artificial light, and second the U-value improvement of the window for achieving better performance and reducing losses. Both improvements result in lower energy consumption particularly in the hot sunny Cyprus climate. Replacing old windows lacking insulation could be considered mandatory during the building renovation.
4. Installation of renewable energy systems-photovoltaic: as mentioned in chapter 6 weather data analysis, Cyprus has high solar potential, with average daily sunshine 9.8 to 14.5 hours. According to the Cyprus Institute of Energy[181] a PV system with nominal output of one kilowatt (1KWp), located in a coastal area of Cyprus, with panels angled 29o and south direction, with fixed frames, produces more than approximately 1600KWh per year, as the average of the first 20 years of operation. Moreover, technology constantly improves and greater efficiency may be achieved in the future. Thus the Cyprus weather combined with the need for immediate measures to transform buildings into zero energy highlights the photovoltaic systems as the best of all solutions while government funding for renovation or installation of renewable sources on existing buildings also focuses on photovoltaic systems.
The project results and simulations indicate that developing zero energy buildings in Cyprus is feasible using the above measures and will contribute positively to reductions in energy demand. Results indicate that the development of zero energy building from the beginning - design phase- is more efficient offering more flexibility and fewer restrictions in the actions taken in building construction. Moreover, the wide range of available construction materials and technology offers more options during the decision making phase with better results on completion of the building.
The development of new generation zero energy buildings is underway in Cyprus and European targets will soon oblige Cyprus to shift to this concept at least for all new buildings. The benefits of this new concept will be the significant reduction of energy-electricity and reduced consumption of fossil fuels leading to Cyprus depending less on oil markets.
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11.3. Findings: Single family house
The above measures were applied during the research with results indicating that there are significant reductions in energy demand. In the case of the Refurbishment improvements were made to insulation, HVAC systems, window insulation, internal shading, boiler and solar water heating, which resulted in lower energy consumption for the building.
Comparison between the Base and Refurbishment case studies show that improvements in building resulted in an energy reduction of 33% in total yearly energy consumption. Table 61 shows the U-values of the two case studies and the percentage difference between the values.
Table 61: Comparison of the Base and Refurbish case studies input U-values
Parameters Base case Refurbishment case Comparison 1&2* study (1) study(2) (%) Construction: External wall U-value (W/m2K) 1.53 0.25 83.7 Internal Partitions U-value (W/m2K) 1.48 0.26 82.4 Ground/Exposed Floors U-value (W/m2K) 1.07 0.38 64.5 Internal Ceiling/Floor U-value (W/m2K) 0.83 0.27 67.5 Roofs U-value (W/m2K) 1.13 0.29 74.3 Glazing U-value (W/m2K) 2.77 2.65 4.33 *Comparison between the Case studies and Percentage Change between the parameters.
The Best practice case study included improvement of all the factors involved in the building’s energy consumption. A comparison of the Best practice case study with the Base case study (Table 62) shows that the total annual energy consumption was 69.1% less and a comparison of the Best practice case study with the Refurbishment case study (Table 63) shows that the total annual energy consumption was 53.1% less.
Table 62: Comparison of the Base and Best practise case studies U-values
Parameters Base case Best practice case Comparison study (1) study(3) 1&3*(%) Construction: External wall U-value (W/m2K) 1.53 0.15 90.2 Internal Partitions U-value (W/m2K) 1.48 0.14 90.5 Ground/Exposed Floors U-value (W/m2K) 1.07 0.16 85.0 Internal Ceiling/Floor U-value (W/m2K) 0.83 0.16 80.7 Roofs U-value (W/m2K) 1.13 0.13 88.5 Glazing U-value (W/m2K) 2.77 1.8 33.1
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Table 63: Comparison of the Best practice and Refurbishment case studies input U-values
Parameters Refurbishment Best practice case Comparison study(3) case study(2) 2&3*(%) Construction: External wall U-value (W/m2K) 0.25 0.15 40.0 Internal Partitions U-value (W/m2K) 0.26 0.14 46.1 Ground/Exposed Floors U-value (W/m2K) 0.38 0.16 57.9 Internal Ceiling/Floor U-value (W/m2K) 0.27 0.16 40.7 Roofs U-value (W/m2K) 0.29 0.13 55.1 Glazing U-value (W/m2K) 2.65 1.8 29.0 *Comparison between the Case studies and Percentage Change between the parameters
The reduction of energy (percentage change) in all the cases was not equivalent to the improvements percentage. For example, the improvements of the input U-value from the base to the refurbishment case study were between 65-85% whereas the energy reduction was 33.1%. This may indicate a need for further study and analysis of other factors involved, such as the lighting and equipment performance. The project analysis is based on only the building’s heating and cooling performance without any optimisation of lighting or equipment performance.
Regarding the single family house, the most significant point was the results from the renewable systems and more specifically from the installation of photovoltaics systems. The analysis of this factor (renewable systems) showed that after the minimization of building energy demand the building could be transformed into zero energy with the installation of photovoltaics systems. Furthermore, the minimum area of photovoltaics (78m2) for the single family house returned 0.6MWh per year of surplus energy, meaning that 600 kWh/year or 50kWh/month can be used from the grid for other energy purposes. Assuming that the total annual energy demand for a single family house (low energy house) is 12600kWh/year, with the construction of 21 zero energy houses with 600kWh/year/house the 22nd house can be powered by the energy surplus from the other houses. Generally, houses can potentially be not only zero energy but can also be transformed into small energy producers and return the surplus energy into the grid.
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11.3.1. Family house simulation results related to other research
The ELIH-MED project [182], includes a comprehensive program of energy interventions in households with low annual income and covers the whole Mediterranean area with 19 partners from 7 countries. The project (SMILEGOV idea) [182] was built on the concept that cooperation between different levels of governance of islands (for example national, regional, local) can play a key role in reaching the 20-20-20 EU goals in the area of energy and climate change. In Cyprus, measures have been taken towards increasing energy efficiency in 25 family house-same types as the project case study, with the collaboration of multiple stakeholders.
In implementing the project ELIH MED in Cyprus, measures were taken to increase energy efficiency in 25 single family houses of low income consumers. The interventions are co- financed 85% by the European Regional Development Fund of the European Union and 15% of the participating Local Authorities and the Cyprus Land Development Corporation.[183]
Moreover, the Electricity Authority of Cyprus sponsored 25 smart meters and members of the Cyprus Association of Renewable Energy Enterprises in Cyprus sponsored photovoltaic systems that were installed and connected with the net metering system. Works were delivered by mid March 2014. Interventions were aimed at improving the energy efficiency of buildings to save energy while at the same time improving living comfort and quality of life. [183]
Interventions were selected based on techno-economic criteria and took into account the existing condition of the buildings and habits of the owners. In each house some of the following interventions or combination of interventions have been used: roof insulation, shell thermal insulation, windows replaced with double energy windows, external shading, replacement of solar water heaters, replacement of air conditioning units with new high energy class, bulbs replaced with new energy-efficient bulbs, traditional fireplace replaced with wood energy source high performance (air fireplace or water type boiler), waterproofing (waterproofing) repaired and photovoltaic system with net metering installed. [183]
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Figure 129: Graph of daily consumption records- electricity production in house[183] For the first time in Cyprus there is evidence of consumption records- electricity production (Figure 129) through the installation of smart meters, per 15 minute recording of electricity consumption and user profile. These records are combined with the production of electricity by photovoltaic systems installed and studied off-setting production-consumption of electricity during one day, week, month or year.[183]
The development in Cyprus of the project ELIH MED first confirms the actions proposed by the research for transforming old buildings into zero energy and secondly it shows that the transformation of the building stock is an achievable goal. However, the case studies of ELIH MED project focus only on small family houses with a low annual household income whereas the research project focuses on family houses which are larger and have a higher annual household income. The ELIH MED project also indicates a need for further studies related to the artificial lighting of Cyprus, which is not examined in the current research. The replacement of artificial light with led technology significantly contributes to energy consumption of a house and could be another research project in the future.
The ‘base case’ of the ELIH MED project is based on the assumptions that the house has: old conventional boiler 60% efficient used for space heating, non insulated heating distribution system, inefficient heating terminal units, inefficient heating control system, 10 years old heat pump units used for cooling, non insulated cooling distribution system, inefficient cooling controls, electric system used for domestic hot water, incandescent lighting throughout (in single family buildings) / incandescent lighting to 80% of floor area and halogen lighting to 20% of floor area (in multi‐family buildings) / incandescent to 70%, halogen 10% and compact fluorescent 20% ‐ in corridors (in high‐rise buildings). [184]
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The ELIH MED project tested a total of three scenarios related to energy improvements of the building envelope for each typology and location[183][184]:
1. Scenario 1: addition of 10 cm of insulation to the roof with U-value 0.35 W/m2K 2. Scenario 2: addition of external thermal insulation system to exterior walls with 7cm insulation material with U-value 0.5 W/m2K 3. Scenario 3: replacement of all windows with double glazed units (without low–e coating) and insulated window frames with U‐value = 1.7 W/m2K combined with reduction of infiltration rates due to improved air tightness
Table 64: Show the single family house U-values comparison between the projects
Single family house ELIH MED Research Project Research Project Research U-values W/m2K project Base case study Refurbishment Project case study Best practice case study Roof insulation 0.35 1.13 0.29 0.13 External thermal 0.5 1.53 0.25 0.15 insulation Windows 1.7 2.77 2.65 1.8
Table 64 shows the U-values used by the two projects. There are significant differences because the ELIH MED project tried to minimize the cost of the project by using the minimum possible values in order to reduce the cost of refurbishment and without targeting the zero energy house in contrast with the research project whose cost was not calculated and whose target was the transformation of the family house into zero. On heating and cooling systems the two projects used similar systems values where the Seasonal efficiency, Sensible Coefficient of Performance, Heat recover, Nominal effective exchange rate, Seasonal Energy Efficiency Ratio and System Seasonal Energy Efficiency Ratio was the same in both cases. The results in both cases give an indication of the energy consumption savings in each case but a more detailed energy study is necessary before carrying out a retrofit project taking into consideration: the project specific technical conditions, the fuel mix used by the building and local energy tariffs, and the energy cost benefits in relation to the capital costs for the proposed improvement.
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The transformation of the old building stock into a zero energy buildings will need lower U- values that the ones were used by ELIH MED project. However, there should be a techno- economic analysis to examine the feasibility of all the possible cases suggested by the research project in terms of cost and investment. This is further research needing to be carried out in the future.
Another study published by Cyprus Energy Agency [185][186][187] concerning the zero energy house developed a real low energy house-close to zero energy where the house was 250m2 and situated in Nicosia. This house was similar to the project case study family house and the U-values that were used can be seen in Table 65.
The Cyprus Energy Agency project is also based on the concept that the energy demand of the house must be reduced before the photovoltaic system can be applied. The house had external shades and geothermal HVAC systems with high energy efficiency.
Figure 130: Cyprus Energy Agency project-single family house [185]
Table 65: Show the single family house U-values comparison between the projects
Single family house Cyprus Energy Research Project Research Project Research U-values W/m2K Agency project Base case study Refurbishment case Project study Best practice case study Roof insulation 0.39 1.13 0.29 0.13 External thermal 0.35 1.53 0.25 0.15 insulation Ground/Exposed 0.47 1.07 0.38 0.16 Floors Windows 2.5 2.77 2.65 1.8
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The Cyprus Energy Agency project-single family house was the Cyprus authorities’ first official attempt to develop and define the zero energy house but the U-values used need further improvement in order to reach zero energy. As stated in the report, the attempt concluded not in a zero energy project but in a low energy project with well insulated envelope. [185]
Further research on the topic is needed starting with a definition of a zero energy house for the Cyprus authorities since Cyprus, an EU country, still has no exact definition of such houses. The only definition so far is that residential buildings’ primary energy use should be lower than 180kWh/m2/yr and at least 25% of the 180kWh/m2/yr of the primary energy must be covered by renewable sources. [188]
The most significant results of the Cyprus Energy Agency project-single family house were:
1. the insulation of the house reduced up to 50% of the heating and cooling energy demand. [185]
2. correct orientation of the house reduced up to 10-20% the heating and cooling energy demand. [185]
3. the use of electronic devices that are in energy category A and the use of led lights reduced the electricity consumption 40%. [185]
4. the use of geothermal heat pumps, photovoltaic systems and solar heaters reduced the heating energy demand 60-70% and the cooling 30-40%.[185]
5. the climatic conditions of each town affect heating and cooling demands and are a basic parameter for the design of a zero energy house. [185]
The conclusions of the Cyprus Energy Agency project-single family house are comparable with current research results and the actions required to achieve the zero energy house in Cyprus. However, the current research did not develop the geothermal heat pump option due to the restrictions of the simulation program. There is need for further study with analysis and evaluation of other renewable sources installation in the single family house.
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Another study published by Fokaides, P.A. et al. [189] presents practical scenarios for
achieving near zero energy dwellings in Cyprus based on the documentation of developments in the building sector after the adoption of regulations for compulsory building insulation. For this purpose, data concerning the building stock of Cyprus before the adoption of the regulation of thermal insulation, as well as the construction characteristics for sixty dwellings which were built from 2010 to 2012 are compared. [189]
Table 66: Show the single family house U-values comparison between the projects
Single family house Fokaides, P.A. Research Project Research Project Research U-values W/m2K et. al. project Base case study Refurbishment case Project study Best practice case study Roof insulation 0.27 1.13 0.29 0.13 External thermal 0.32 1.53 0.25 0.15 insulation Ground/Exposed 0.27 1.07 0.38 0.16 Floors Windows 2.05 2.77 2.65 1.8
The U-values of the Fokaides, P.A. et. al. [189] project are between the refurbishment and best case studies of the current research project. The Fokaides, P.A. et. al. [189] study aimed to investigate possible scenarios for achieving the target of zero energy dwellings in Cyprus by 2020 and so the evolution of the dwellings stock in Cyprus after the adoption of all the provisions of the EPBD was examined. After relevant legislation was adopted in Cyprus, the energy consumption of dwellings decreased by 40% proving the impact of European directives on buildings’ energy performance in member states. The technologies that can directly contribute to the building sector in the Mediterranean region are photovoltaic, solar thermal and biomass for space heating and normalized quantitative indicators for the required production of each renewable energy technology in the Cypriot system were defined. Possible scenarios in relation to dwellings consumption in Cyprus by 2020 showed that this would range from 65 to 40 kWh/m2 year, depending on the degree of use of renewable energy technologies. It was also concluded that photovoltaics represent the most effective technology the building sector in the Mediterranean due to the high conversion factor of primary to end energy for electricity generation, which is 2.7 for Cyprus.
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It was also proved that a 3.5 kW photovoltaic plant for on-site production could turn a dwellings in Cyprus built according to EPBD into a net zero energy building, given that the domestic hot water and heating requirements are covered by a solar thermal system and a biomass boiler, respectively. These results can be considered as representative of Mediterranean basin states, with climate and building characteristics such as those of Cyprus. [189]
There are both similarities and differences between the current research and Fokaides, P.A. et. al. project. Firstly, the Fokaides project used a smaller house case study with smaller energy demands and so the photovoltaics needed to cover the house needs are 3.5 kW rather than the 12kW needed in the current project case study. Secondly, the Fokaides study covered the domestic hot water with a solar thermal system with heating requirements covered by a biomass boiler and the current study uses a solar thermal system for hot water with heating covered by a HVAC system using electricity. The Fokaides project includes the heating and part of the hot water in total energy demand and the photovoltaic system will probably be close to 12kW.
The comparison of the current project results with other related studies reveals a need for further studies in some sections requiring detailed analysis, such as the development of geothermal heat pumps for heating and cooling needs, the efficiency of the artificial light and the installation of led technology. However, the proposed measures and actions are on much the same lines as the other related studies and result in successful development of a zero energy building.
11.4. Findings: Office building
The second building category for analysis and simulation was the commercial building – an office building. This type of building with large glazed areas has only recently been developed in Cyprus and can be regarded as a new building type. Due to the wide glazed area reducing building energy demand in accordance with energy regulations, the cost of the solution would be very high due to the high cost of the glazing insulation and technology,. The glazing surfaces are more sensitive to outside conditions and the development of high insulation on those surfaces has limitations such as the cost, the design and the use of the building.
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The Office Refurbishment case study included improvements in building construction such as application of insulation, more efficient HVAC systems, installation of shading systems, improved boiler systems and installation of solar water heating (Table 67).
Table 67: Office comparison of the Base and Refurbish case studies input U-values
Parameters Base case Refurbishment Comparison 1&2* study (1) case study(2) (%) Construction:
External wall U-value (W/m2K) 1,44 0.46 68.21 Internal Partitions U-value (W/m2K) 1,48 0.46 68.87 Ground/Exposed Floors U-value (W/m2K) 1,11 0.33 70.07 Ground/Exposed Floors (air) U-value (W/m2K) 1.37 0.42 69.45 Internal Ceiling/Floor U-value (W/m2K) 0.88 0.55 37.27 Roofs U-value (W/m2K) 1.12 0.40 63.99 Store Glazing U-value (W/m2K) 5.28 2.57 51.32 Office Glazing U-value (W/m2K) 2.81 2.63 6.31
The improvements of the buildings resulted in 17% reduction of total yearly energy consumption compared to the Base case study. The office building Best practice case study included improvements of all the factors and systems of the building construction. Comparison of the Base and Best practice case studies showed that the latter had a reduction of 29.58% in total annual energy consumption (Table 68).
Table 68: Office comparison of the Base and Best practice case studies input U-values
Parameters Base case Best practice case Comparison study (1) study(3) 1&3*(%) Construction:
External wall U-value (W/m2K) 1,44 0.24 83.60 Internal Partitions U-value (W/m2K) 1,48 0.26 82.31 Ground/Exposed Floors U-value (W/m2K) 1,11 0.19 82.42 Ground/Exposed Floors (air) U-value (W/m2K) 1.37 0.15 88.68 Internal Ceiling/Floor U-value (W/m2K) 0.88 0.20 77.56 Roofs U-value (W/m2K) 1.12 0.22 80.40 Store Glazing U-value (W/m2K) 5.28 1.85 64.92 Office Glazing U-value (W/m2K) 2.81 1.84 34.30
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Table 69: Office comparison of the Best practice and Refurbishment case studies input U-values
Parameters Refurbishment Best practice Comparison case study(2) case study(3) 2&3*(%) Construction:
External wall U-value (W/m2K) 0.4588 0.2367 48.40 Internal Partitions U-value (W/m2K) 0.4594 0.2610 43.18 Ground/Exposed Floors U-value (W/m2K) 0.3313 0.1946 41.26 Ground/Exposed Floors (air) U-value (W/m2K) 0.4173 0.1546 62.95 Internal Ceiling/Floor U-value (W/m2K) 0.5520 0.1966 64.38 Roofs U-value (W/m2K) 0.4031 0.2193 45.59 Store Glazing U-value (W/m2K) 2.57 1.8520 27.93 Office Glazing U-value (W/m2K) 2.63 1.8444 39.87
Comparing the Refurbishment with the Best practice case study, the reduction in total annual energy consumption was 15.29 % (Table 69).
The reduction percentages of total yearly energy consumption were significantly lower than the percentages of U-value improvements. This is mainly due to the large glazed area of the building and other factors such the need to improve the lighting of the building. The improvements of the glazed area were limited due to the cost of a solution and the limitations of technology. The cost of the construction and the improvements was not considered in the project, but the proposed solutions had to be in a real concept. The results showed that with this kind of building there is a clear-cut need for further and detailed analysis of all relevant factors.
The office Best practice case study had lower total yearly energy consumption and the target was to transform it into a zero energy building. The next step was to install photovoltaics systems and optimization of the PV area showed that the building energy needs could be covered entirely with 2900m2 of photovoltaics. It should be stressed that the minimum area of photovoltaics returned 12.9 MWh/year surplus of energy (2900kWh/year or 1075 MWh/month). Surplus energy can be returned in the grid and entirely cover the energy needs of a zero energy house with an energy demand of 12600kWh/year.
The concept of a building not only covering its energy needs but also producing energy requires further study. The project results showed that even in the case of an office with a high energy demand a zero energy building can be created by using the appropriate measures and a combination of energy efficiency methods/techniques and the installation of renewable systems.
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Generally the highest building demand was for cooling in all the cases (Base-Refurbishment- Best Practice case study) but, the energy measures applied to the building caused a greater reduction in heating demand than in cooling demand. Comparing the base case study with the Best practice case study, the total heating demand was reduced to 74.9% and the total cooling demand was reduced to 69.5%.
11.4.1. Commercial building- office building simulation results related to other research
As previously mentioned, Cyprus has just recently introduced energy regulations and standards for the building sector so the development of zero energy commercial buildings is at an early stage and research in this field is just beginning. As a consequence it was difficult to find related projects and compare them with current case study. However other commercial buildings with similar use and design were compared with the current office building case study.
As Chapter 9-Office building case study stated, the demand for office buildings rose after Cyprus’ accession into the EU and now, after the discovery of natural gas in Cyprus waters, the island is developing into a trade and international business centre exerting new previously non-existent demands on the building market.
The first attempt to transform a commercial building into zero energy was made by the Cyprus Institute, the Energy, Environment and Water Research Center (EEWRC). [190] The Cyprus Institute undertook an energy study whose objective was to develop solutions for retrofitting historically and politically important building towards zero-energy-buildings (ZEB), for example a building applying intensive energy-conservation measures and using its own renewable energy-generating sources to produce the power it consumes. A series of high energy-efficient innovative technologies and measures concerning the Cyprus Presidential Palace were documented related to proposed retrofit solutions for this historic monument. [191] The research team followed a procedure of first minimizing energy demands of the building, and then upgrading the HVAC systems before applying renewable energy systems- photovoltaics. The minimization of energy included insulation of the external walls, installation of shading systems (external and internal), window improvements and artificial lighting improvements. The glazing U-value was 1.7 W/m2K, the insulation width was 10cm and the old oil heating system was replaced with heat pumps for heating and solar collectors for hot water. [191] However, the project is under development with more results expected after project completion.
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Another project recently begun in Cyprus and to be completed in 2016 is the Oval office building (Figure 131). This building is situated in Limassol on the coast and will be the tallest commercial building in Cyprus with 16 floors and 2 parking areas. The building will be zero
energy with energy performance certificate of ‘A’ rating and low CO2 emissions. However, the construction company has not published technical details of the building. [192] The Oval building could be compared with the current research office case study building as it includes many glazing surfaces and there will be an issue with the energy consumption, particularly for cooling demand.
Figure 131: The Oval office building [192] Research published by C. Katafygiotou is "Analysis of structural elements and energy consumption of school building stock in Cyprus: Energy simulations and upgrade scenarios of a typical school" [193] The research investigates the structural and energy consumption details of Cyprus secondary school buildings and identifies the prevailing building practices in school construction in the three climatic zones of Cyprus (Figure 132 ). The research concept is similar to that of the current research and confirms the significant differences between the Cyprus towns related to weather conditions.
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Figure 132: Primary energy consumption of schools [193]
Figure 132 shows that electricity needs are higher in coastal and inland areas whereas mountain schools consume more primary energy for heating oil.
Table 70 shows the thermal conductivity of the building components and electromechanical systems in schools in each climatic zone and confirms the current study’s observations that there is no insulation in most Cyprus buildings and there were no energy measures before Cyprus joined the EU. School construction is comparable with the office base case scenario where no insulation or energy efficiency measures were applied. The school research confirms the significance of the second scenario of office building (refurbishment case study) since old building stock of Cyprus will need renovation with energy demand reduced and renewable energy systems installed. In many countries this type of energy rehabilitation of large (more than 1000 m2) public buildings is best suited for the implementation of European Directive 2002/91/EC on the Energy Performance of Buildings (EPBD). [194]
Table 70: Thermal conductivity of the buildings components and Electromechanical systems in schools in each climatic zone. [193]
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Table 71: energy savings from different retrofitting scenarios. [193]
Table 71 shows energy savings from different retrofitting scenarios from the school research. Comparison of the scenarios with the current research- office building case study indicates that the proposed measures in both cases are almost identical as external insulation on wall and roof, replacement of windows, increase of efficiency of heating and cooling systems and installation of the photovoltaic systems are proposed in both cases for reduction of energy demands of the building. However, the current research takes one step further by suggesting stronger measures (best case study) such as lower U-values, insulated windows and energy efficient systems to minimize building energy demand and so achieve zero energy buildings. According to the school research, insulation of the envelope and the use of HVAC systems especially for cooling are the most suitable design elements for energy efficient school buildings. [193][195]
Furthermore the survey results concluded that a horizontal roof is more efficient than a sloping roof and may be insulated more easily at less cost. Single storey, ground floor buildings require less energy than multi-storey school buildings and the most energy efficient shape for school buildings is the rectangle which, combined with northern or southern exposure, appears to use less total energy
Another project related with current research is the net zero energy office building in Germany, Ruhr Region, which is the 1st part of Daikin nZEB project. Built by Daikin Europe, Zeller Kälte und Klimatechnik and Athoka as a research and demonstration project, the occupied office building (535 m2) has air to water and air to air heat pumps, a ventilation system with heat recovery, lighting through LEDs, thin film photovoltaics and a management system with 500 sensors to continuously monitor the building.
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The thermal characteristics of the building are: outdoor wall 0,23 W/m²K, roof 0,16 W/m²K, floor 0,24 W/m²K and windows 1,30 W/m²K.[196] The two projects have similar thermal characteristics since the office building in Cyprus has outdoor wall 0,24 W/m²K, roof 0,22 W/m²K, floor 0,19 W/m²K and windows 1,85 W/m²K. In order to reach the nZEB-goal the Net Zero energy Office Building in Germany project has a photovoltaic system with a peak power rating of 27.3 kWp installed on the roof. [196] Figure 133 shows the energy measures and concept of the net zero energy office building in Germany. While the heat pumps used for heating and hot water make an important contribution to the energy efficiency of the office building, this type of renewable energy was not developed from the current project due to the limitations of the simulation programs but will be developed in a future study. [196]
Figure 133: Measures to reduce the energy demand of the net zero energy office building in Germany.[196]
Figure 134 presents the monthly energy consumption and generation of nZEB Herten. The most significant point arising from the net zero energy office building in Germany is that during the measuring period the sum of the energy demand amounts to 19,975 kWh. Compared with the yield of the PV-system, 20,970 kWh, the nZEB-energy demand can be covered completely. [196]This result confirms the current project results that after significant energy reduction of the building the remaining energy demand can be covered by photovoltaic systems.
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Figure 134: Monthly energy consumption and generation of nZEB Herten [196]
As a building’s energy consumption is always affected by its construction elements and alternative strategies, techniques for energy efficiency need to be used to create a comfortable indoor environment while simultaneously conserving energy. As buildings’ energy performance is directly influenced by their construction characteristics, selecting suitable construction elements and design strategies is an important stage of constructing or renovating a building.
11.5. Findings: Olympic residence building
The third building to be analysed and simulated with the IES program was the Olympic Residence building. It should be stressed that the Olympic residence project was the first 19- storey residential building in Cyprus and was constructed entirely with a concrete body and external walls. Each of the 19 floors contains 4 luxury flats and the ground floor includes shops, restaurants, cafeterias, a reception area and offices.
The large size of the building in combination with a high energy demand for the different facilities was a real challenge for the project. In addition, the range of different spaces, such as offices, restaurants, gym, shops and cafeterias, added an extra difficulty to the energy balance of the building. Due to the high cost of the apartments and the high facility services, energy reduction needed to be approached so as not to reduce comfort levels.
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The building was analysed in three different case studies: the Base case study, the Refurbish case study and the Best practice case study. The energy measures and improvements applied on the building were the same as the office building case study.
The Refurbishment case study included improvements in building construction such as the application of insulation and more efficient HVAC systems. installation of shading systems, improvement of the boiler systems and installation of solar water heating (Table 72). The improvements in the buildings resulted in a 26.98% reduction of the total annual energy consumption compared to the Base case study, a useful scenario in the case of current residential buildings of Cyprus needing renovation in order to have lower energy consumption.
Table 72: Olympic Residence comparison of the Base and Refurbish case studies input U-values
Parameters Base case Refurbishment Comparison study (1) case study(2) 1&2* (%) Construction: External wall U-value (W/m2K) 1.42 0.45 68.30 Internal Partitions U-value (W/m2K) 1.48 0.46 68.90 Ground/Exposed Floors U-value (W/m2K) 0.61 0.28 54.10 Internal Ceiling/Floor U-value (W/m2K) 1.15 0.59 48.70 Roofs U-value (W/m2K) 1.12 0.48 57.10 Store Glazing U-value (W/m2K) 5.29 2.57 51.40 Apartments Glazing U-value (W/m2K) 2.81 2.62 7.10
Tables 73 and 74 show the input U-values during the simulation of each case study and the last column shows the comparison between the two case studies and the percentage difference between the input U-values which can be characterized as improvements on the building elements and construction.
The Olympic Residence Best practice case study included improvements of all the factors and systems of the building construction. The simulation of this case study showed a total annual energy consumption of 962.1MWh and a total annual energy consumption per floor area of 91.0 kWh/m2.
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Table 73: Olympic Residence comparison of the Base and Best practice case studies input U-values
Parameters Base case Best practice case Comparison study (1) study(3) 1&3*(%) Construction: External wall U-value (W/m2K) 1.42 0.16 90.80 Internal Partitions U-value (W/m2K) 1.48 0.22 85.10 Ground/Exposed Floors U-value (W/m2K) 0.61 0.18 70.50 Internal Ceiling/Floor U-value (W/m2K) 1.15 0.20 82.60 Roofs U-value (W/m2K) 1.12 0.19 83.00 Store Glazing U-value (W/m2K) 5.29 1.63 69.20 Apartments Glazing U-value (W/m2K) 2.81 1.65 41.50
Comparison of the Base and Best practice case studies showed that the lattery had a reduction of 238.76% total yearly energy consumption (Table 73). Comparison of the Refurbishment and Best practice case study indicated that the reduction in total annual energy consumption was 16.13% (Table 74).
Table 74: Olympic Residence of the Best practice and Refurbishment case studies U-values
Parameters Refurbishment Best practice Comparison case study(2) case study(3) 2&3*(%) Construction:
External wall U-value (W/m2K) 0.45 0.16 71.10 Internal Partitions U-value (W/m2K) 0.46 0.22 52.20 Ground/Exposed Floors U-value (W/m2K) 0.28 0.18 35.70 Internal Ceiling/Floor U-value (W/m2K) 0.59 0.20 66.10 Roofs U-value (W/m2K) 0.48 0.19 60.40 Store Glazing U-value (W/m2K) 2.57 1.63 37.80 Apartments Glazing U-value (W/m2K) 2.62 1.65 37.00
The improvements in building fabric and systems resulted in a lower energy consumption of the building. The comparison between the Base and Best practice case studies showed that the greater reduction of energy was achieved for the heating demand (89.9% lower on total yearly heating demand) and the total annual cooling demand was reduced by 59.4%. The building energy performance responded positively to the energy measures applied to the building and achieved significant reductions in energy for cooling and heating.
Another significant factor was the reduction of the CO2 emissions resulting from the building improvements and energy measures applied to the building.
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Comparison of the Base case study and the Best practise case study indicates that the
reduction of CO2 emissions was 61.3%. Comparison between the Base case study and the
Refurbishment case study showed a reduction of 44.9% in CO2 emissions.
After minimization of the building’s energy demands the next step towards achieving the zero energy building was to cover its energy needs with renewable energy. The installation of photovoltaics systems on the building or in a location close to the building was investigated during the project development and optimization of the PV area showed that the building needs could be covered by 4700m2 of photovoltaics meaning 783,3 kW. The current photovoltaics had a nominal efficiency of 0.17 and reference irradiance for NOCT 1000W/m2. The minimum area of photovoltaics not only covered the building’s needs but also produced 1.2MWh surplus energy per year. Where the cost or the available area is not an issue, the installation of 4900m2 of PVs and the production surplus energy of 15.8 MWh per year should be considered. However, the optimization of the PV installation took into account the minimization of area and the minimum cost.
The current project investigated the renewable energy solution but it was not a primary target to examine in detail the available area for PV installation, optimal design and cost. Nevertheless, the values for the PV systems were real and were used in simulation in order to have the best possible estimation for the building’s needs. There is always a chance the system will not always perform as required due to the building type and complexity.
The highest energy demand for the building was the heating demand for the Base and Refurbishment case studies. In the Base case study the cooling was 66.4% less than the heating demand and in the Refurbishment case study the cooling was 14.4% less than the heating demand. The reduction in the difference was due to the building fabric and system improvements.
In the Best practice base case the demand changed and the heating demand was 25.6% less than the cooling demand. This change was caused by the energy measures and design methods applied to the building in order to make it a Zero energy building. Nonetheless, the energy measures applied to the building gave a greater reduction in heating demand than in cooling demand. Comparing the Base case study with the Best practice case study shows that the total heating demand was reduced to 89.9% and the total cooling demand was reduced to 59.4%.
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11.5.1. Findings: Olympic residence building- orientation and height simulation results
The impact of a building’s orientation on heating and cooling demand was analysed during the project development. The building’s initial position was south facing and it was rotated 90o in order to check the effects of different orientations.
The project selected for analysis was flats from five different floors of the building (floors one, five, ten, fifteen and nineteen). Flat one appeared to have an increased heating demand comparing the initial position (south facing) with the final position (west facing). However, the cooling demand of flat one presented a small reduction for all floors. From south-east flat two faced south-west and presented an increase in heating demand while the cooling demand remained the same.
The cooling demand increased slightly for flat one from November to February. From north- west flat three turned east-north and presented a reduction in heating demand for all floors. The cooling demand was the same for all floors with the initial position except for April and November when the cooling appeared to be slightly more than in the initial position. Flat four changed from north-east to south-east and presented a significant decrease in heating demand for all floors. The cooling demand presented a minor increase for all floors compared to the new position. In the main the orientation of the building affected energy performance and demand for heating and cooling.
The height effect was analysed during the simulation of the Olympic Residence. The analysis included the first, fifth, tenth, fifteenth and nineteenth floors of the building. The heating and cooling demand for each flat was examined in relation with the height of each floor.
The results showed that the first and nineteenth floors had a higher heating and cooling demand than the other floors. The energy performance of the bottom and top floors had a different energy performance from the floors in the middle because they had a greater area exposed to external conditions than the other floors and were therefore more sensitive to external environmental conditions leading to a need for more energy to maintain internal conditions.
Overall the analysis showed that the height of the floors affected the energy consumption of the flats and hence the heating and cooling demand. External conditions - temperature and wind speed - varied according to the height of a floor so the conditions on the first (lower) floors were different from the conditions on higher floors.
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Temperature fluctuations due to height were a major issue for this tall building and further in- depth studies are needed to investigate the impact of the height effect on this type of building in Cyprus.
The simulation of the Olympic Residence, which was new type of building for Cyprus, provided useful information for future use. The building construction, building materials and HVAC systems were directly related with the building’s energy performance and interaction with the external environment. Furthermore, the building use and specifically the use of the different spaces need to be studied carefully in order to apply correct operational profiles and achieve the best comfort levels with the lowest energy consumption.
However, in this type of building multiple factors are involved in energy performance and these need to be analysed separately and in combination to achieve the best results. The best optimization of all the factors is not feasible and sometimes compromises need to be made to achieve the aims of the project. The transformation of this building into a low energy building with the refurbishment method and into a Zero energy building through the use and application of new regulations was shown to be feasible. Zero energy buildings can be developed for hot climates and can produce not only enough energy to satisfy their own needs but also surplus energy that can be used from the grid.
11.5.2.Residential building- Olympic Residence simulation results related to other research
Generally zero energy building projects focus on family houses and office buildings while the development of projects, such as the Olympic Residence in Cyprus, which represents a large residential building offering facilities like a hotel, have not yet been sufficiently developed. This type of building - the so called ‘tower building’ - is only now being researched and developed.
A paper titled "Towards Zero energy: A Case Study of the Pearl River Tower, Guangzhou, China" describes the Pearl River Tower which is claimed to be the most energy efficient tall tower in the world. The climate conditions (hot and very humid – subtropical) of Guangzhou city are similar with Cyprus conditions and this allowing the comparison of the energy measures and methods that were used in two buildings.[197][198]
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The aim of the Pearl River Tower design was to approach “net zero energy” and achieve carbon neutrality for the project. During the project development the site, energy sources both active and passive, materials, indoor air quality, were considered including how they could be integrated into a building. Simple concepts were considered such as site analysis, building orientation, wind direction, sun path analysis as well as sophisticated approaches and technologies. [197][198]However, the Pearl River Tower is still an office tower building with high facilities and the methodology and concept followed by the design team can be compared with the Olympic residence methodology. In both cases all the combined strategies form the basis of the design approach in an effort to achieve a zero energy goal. Both projects attempted first to minimize the energy demand of the building using different methodologies and then to cover the remaining energy demand with renewable energy sources. The Pearl River Tower used a combination of renewable sources such as photovoltaic systems, wind turbine technology and heat pumps in contrast with the Olympic residence that used only photovoltaic systems. This always depends on current weather conditions and in the case of the Olympic Residence the lack of efficient wind power in combination with the limitations of the simulation program hindered the development of such a system. As previously mentioned, further study and development of different renewable sources in the Cyprus building sector are needed to possibly contribute to the zero energy goal.
Another paper titled "Measures to improve the cooling energy performance of student halls in Greece" [199] examined student residence buildings and their energy performance while the possibility of applying environmental design principles in order to improve the cooling energy performance and indoor environment of the residences was investigated. [199] The paper resembles the current project inasmuch as it relates to the refurbishment of a large residential building. The climatic conditions of Greece are similar to those of Cyprus and the project aimed at the minimization of cooling energy through the improvement of the building. The project did not target the zero energy building but the project concept can be considered as part of the current project zero energy goal.
The main energy saving measures proposed for the student hall buildings were the following:
1) Insulation of the roof with a 7 cm thick layer resulting at a U-value change from U=1.72 W/m2K in the current condition to U’=0.31 W/m2K. [199]
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2) Light colour painting on the external roof surface, thus increasing the reflectiveness of the roof surface. [199]
3) Insulation of the support frame elements (e.g. support columns, beams) with a 5cm thick layer improving the U-value of the whole wall from U=1.12 W/m2K to U= 0.88 W/m2K. . [199]
4) Replacement of existing window panes with double-glaze (2cm 5) Replacement of the existing window frames with new fitted frames and reduced air infiltration altering the infiltration rate from 0.5 ACH to 0.15 ACH. [199] 7) Combination of all above mentioned strategies. [199] The above comparisons highlight the need for renovation of old building stock to reduce energy consumption and transform them into zero energy buildings. The refurbishment of the current building stock will apply measures to reduce energy demand such as external and internal insulation of the building, window improvements, improvement of the HVAC systems, correct management of the systems, installation of energy efficient appliances, use of led technology and minimization of use of artificial lighting. However, every project has to analyse technical details and decisions in detail as there are many variables to take into consideration. Another project aimed at accelerating the rate of refurbishment of existing hotels into nearly zero energy buildings (nZEB) is being promoted by European Union in response to the European Directive on the energy performance of buildings (2010/31/EU, EPBD which directly contributes to the EU 2020 targets and supports EU Member States in plans for increasing the number of nZEBs. Nearly zero energy buildings are buildings with a very high energy performance and the nearly zero or very low amount of energy required should be mainly covered by energy from renewable sources. This initiative will run for three years (2013-2016) and is co-funded by the Intelligent Energy Europe Programme (IEE) of the European Commission. [200] 349 | Page The results of the current European project will include pilot projects in seven countries (Croatia, Greece, France, Italy, Romania, Spain and Sweden) and could be compared in future with the Olympic residence project with its focus on large residential units with high energy demands. 11.6. Orientation of the case study buildings-simulation results Concerning the effect of building orientation upon energy performance of the case study buildings, building orientation generally has a considerable impact on energy consumption because it affects the heating and cooling demand. The orientation analysis confirmed that the optimal orientation was achieved when the long axis of the building runs east to west. According to results from the three case studies, the south facing building had the lowest energy demand related to the heating and cooling, the north facing building had the highest heating demand and the lowest cooling demand while the east facing building had the highest cooling demand. Comparison between the different orientations of the single family house showed a percentage difference between South and West of 4.2% for heating and 4.3% for cooling for a whole year. Comparing the south with the north facing orientation the heating demand was 20.7% more for north facing the cooling demand was the same. Comparison between the south and east showed that the east facing building needed 17.9% more energy for heating and 12% more energy for cooling. The office building comparison showed the highest cooling demand in the east facing orientation of the building. Comparing the west and the south facing orientations, the former had 3.9% lower heating demand and 1% higher cooling demand. Comparison between the south and north facing orientation showed that the latter had 3.2% lower heating demand and 0.8% lower cooling demand. The east facing orientation had 2.6% lower heating demand and 2.5% higher cooling demand, compared to south facing. In general, the office building analysis showed that the building design and construction materials had a major impact on building performance. For instance, the extensive glazing surfaces in Cyprus buildings without external or internal shading create increased cooling requirements of the building in summer. On the other hand, in the winter large glazing surfaces without proper insulation contribute to considerable heating losses. Hence, decisions concerning the construction materials and the design of the building need to be made at an early stage. 350 | Page The Olympic residence (residential building) comparison showed that the highest cooling demand occurred in the east-west orientation of the building and the lowest cooling demand in the north-east orientation. The heating demand was highest in east-west orientation and the lowest in the south-west orientation. According to the Cyprus Energy Agency report titled "Low energy consumption buildings[201] the cooling reduction due to the orientation was 11% and the peak cooling load reduction was 19% due to the orientation (Figure 135) Figure 135: Comparison of cooling loads for a building in different orientations on the hottest day in August. [201] Sunshades comprised another important factor studied and developed in the current project. According to the Cyprus Energy Agency, with the use of sunshades the cooling load reduction was 23% and the peak cooling load reduction was18%. (Figure 136) [201] Figure 136: Comparison of cooling loads for building with and without sunshades.[201] 351 | Page Because of the Cypriot climate with its many hours of sunshine per year, building orientation is significant since the penetration of solar radiation is directly related to the orientation of the house, the construction design and use of shading factors. Hence, it is important at an early stage (design stage) to identify potential problems related to the orientation of the building. 11.7. Simulation case studies- weather data results The weather and microclimate was an issue for this project so in order to analyse the impact of the microclimate and the importance of the updated weather files, the building was simulated with different weather files. Analysis results indicate that there were significant differences between the simulation weather files. Results showed that heating demand was underestimated in the IES weather simulation file and there were even differences between the files of the same town, depending on which period the weather file was based. Furthermore, cooling demand was not the same for the different simulation weather files. These factors serve not only to highlight the importance of the weather data in the simulation procedure but also to demonstrate how important it is to use up-to-date weather files for simulation purposes. Calculations based on old data files are inadequate for making accurate predictions for a building’s energy demand. In addition, the weather analysis demonstrates the importance of the microclimate and its impact on the building’s energy consumption. The results showed that even in a small place like Cyprus, the precision of the simulation results were directly related to the microclimate and location of the building because of geomorphological differences between various locations (e.g. in or near the mountains or the sea, height above sea level). Hence it was decided to simulate the building by using weather simulation data taken as near as possible to the place of simulation An important point concerning the heating and cooling demand results was that for the same location the IES overestimated or underestimated the heating or cooling needs for the building. This may be due to the differences between weather data files. As previously mentioned, the IES data uses old data and the files generated by the author use revised data which is more representative of current weather conditions in Cyprus. According to the Cyprus Energy report, the cooling load differentiation due to the location was 21% and peak load differentiation due to the location was 21%. (Figure 137) 352 | Page Figure 137: Comparison of cooling loads for buildings in different locations. [201] The Cyprus Energy report also stresses the effect of location on a building’s thermal losses where the differentiation because of the location was 31% (Figure 138) Thus the location plays a key role in the heating/cooling requirements in a building. Figure 138: Comparison of thermal losses of building in a different location. [201] A further study titled "The energy behaviour of the building stock in Cyprus in view of the Energy Performance of Buildings Directive implementation" recognises four major climatological zones (Figure 139), namely coastal, low land, semi-mountainous and mountainous regions.[174] The study stresses the fact that the climatological zone in which the building is built is crucial both in terms of weather conditions, architectural style and therefore energy behaviour. 353 | Page Figure 139: Map of Cyprus showing the four major climatological zones.[174] A further study "Cyprus building energy performance methodology: a comparison of the calculated and measured energy consumptions results" published by G. Panayiotou et.all investigated the impact of climatic conditions on the calculated energy demand. The research concluded that climatic conditions have an influence on buildings’ energy demand even in the case of a small island such as Cyprus.[202] Figure 140: Calculated final energy demand for 4 locations (zones) .[202] As indicated in Figure 140the calculated energy demands vary with the lowest demand in the plains and the highest in the mountains. The highest cooling demand and the lowest heating demand occur on the coast whereas the highest heating demand and lowest cooling demand occur in the mountains. Finally in the three most densely inhabited zones the cooling demands exceed the heating demand. 354 | Page Table 75: Investigation of the effect of the location of building on the energy demand.[202] The energy demand of a typical non-insulated and insulated dwelling was calculated for four different locations representing the different climatic zones in Cyprus. (Table 75).[202] The total energy demand for a non-insulated dwelling, depending on its location, varies from 297 kWh/m2 to 348 kWh/m2 with the highest observed in the mountainous area and the lowest in the lowland. Energy demand is considerably reduced for an insulated dwelling and varies from 116 kWh/m2 to 131 kWh/m2. For the insulated dwelling the coastal and semi- mountainous dwellings exhibit the lowest energy demand. Finally, it was concluded that the dwellings location and the respective climatic conditions influence the final energy consumption by up to 35%. The influence of weather on energy demand is confirmed by the simulation approach, albeit to a smaller spectrum of up to 20%.[202] Results from the above support the current research conclusions that there are significant climatological differences between the Cyprus towns which, in combination with other building factors such as insulation, affect energy consumption. Moreover, the research conducted during the development of this project (Chapter 6 Weather data analysis) stresses weather differences between the different locations and takes into account their possible impact on the simulation procedure and building energy demand. The IES program simulation file cannot be representative for all the towns of Cyprus and it is possible to underestimate or overestimate the energy demand of a building. Thus an important step during the building simulation is the check the weather data file and the location of the weather file, the date of construction and any possible changes during the collection of the data. Even the best design and the best simulation program cannot give accurate results if the weather data file is not updated or is not close to the location of the building. 355 | Page 11.8. Outcome of the research Project results from the three different case studies show that the building of the future should be bioclimatic with a more passive design approach and target the concept of zero energy. The building envelope should not only be dedicated to thermal insulation but should also be multi-functional for protection from the outside environment while utilising the free sources of energy such as wind, sun and soil. Also the analysis shows that the summers will be hotter and in combination with the air-tightness of low consumption buildings, summer comfort becomes an issue and should be studied further. The systems used should be more energy efficient and combine several types of energy production to improve their efficiency. Building management systems should be installed to regulate heating, ventilation, cooling, and lighting systems so they are used only when really needed for the comfort of the occupant. However, the design of a zero energy building needs a standard approach regardless of the type of building and with a more general approach. In all case studies the design concept remains the same and this concept was also found in other research mentioned in the current project. Hence the proposed approach to a zero energy building design includes four important steps: 1. Reduction: The first step to a high performance design is to identify as many opportunities as possible to reduce the amount of energy consumed with a need to focus on the largest consumers within the building, namely the HVAC and lighting systems. This project used high energy efficient systems for the zero energy buildings but the lighting systems were not studied in detail or analysed. This could be a future project that will contribute to zero energy building development in countries having a lot of sunshine during the day. Effective insulation of the buildings plays a vital role in the building energy consumption especially during the heating and cooling time. Building orientation and design are other important factors needing to be taken into account for lower energy consumption. 2. Absorption: the second to high performance design was to include absorption strategies which are defined as those that take advantage of the natural and passive energy sources that pass around, over and under the building’s envelope. 356 | Page The use of solar-heaters for hot water, the use of the extensive glazing to minimize artificial lighting, the use of photovoltaic systems integrated to the building’s external solar shading system and glass outer skin are some of the absorption strategies used during the development of the current project. However, there are more strategies that could be proposed and studied in a future project, e.g. daylight harvesting using daylight responsive controls integrated with automated blinds and building integrated vertical axis wind turbines designed to use the building’s geometry to enhance turbine performance. However, some strategies depend on the microclimate conditions of the building. 3. Reclamation: the third step to a high performance design is to include reclamation strategies, the basis of which is to harvest the energy already existing within the building. Once energy has been added to the building, it can be repeatedly reused. The project includes systems that utilise re-circulated air for pre heat/cooling of outside fresh air prior to delivery of the occupied but these measures depend on the time of year and outside air conditions, and the use of absorption chillers. 4. Generation: The final step to a high performance design is to include energy generation measures. Once all possible measures are used to reduce a building’s energy consumption, the final step is to satisfy remaining energy needs from renewable sources. This can be combined with the absorption step and will target available local sources such as the sun, the wind and the soil. The current project used solar energy, photovoltaic panels, in order to satisfy the building's needs and achieve the zero energy goal. This concept was also supported by other previously mentioned projects but other sources such as wind turbines and geothermal energy could also be studied and developed for zero energy buildings. These sources were not developed in this project and could be part of a future study. Table 76 summarises the proposed aspects of technology and equipment identified as important for future zero energy buildings through the current project development and results. These considerations are not all-inclusive, but represent areas where guidelines could aid technology selection and use. 357 | Page Table 76: Suggested technology and equipment aspects of future zero energy buildings Building Envelope High Priority 1. optimization of insulation measures resulting in a comfortable environment for occupants. 2. maximizing the benefits of day-lighting and efficient light technologies will be important aspects of future zero energy buildings to reduce lighting needs. 3. assorted materials, assemblies, and technologies (for example cool roofs, insulation exterior to framing) will minimize envelope loads (conduction, solar, infiltration, and moisture). 4. triple-glazed windows will minimize cooling or heating energy losses. 5. use of renewable technologies such as photovoltaic systems integrated into building envelope will increase energy generation Intelligent Home Operation High Priority 1. Automation and advanced controls will minimize electricity use for plug and process loads (smart lights, appliances.); lighting, comfort and electronics are installed to respond independently to occupants; appliances and HVAC are completely integrated; fault detection diagnostics are employed; and all systems work seamlessly with the smart grid. Lower Priority 1. Feedback to occupants on energy management performance could be possible through monitoring and display systems (for example electricity, water). 2. Maintaining a reasonable or feasible energy budget could be part of the zero energy buildings operation. HVAC systems High Priority 1. High-efficiency, affordable systems will be readily available (HVAC/air distribution systems to recover heat from air and water, hot water systems); comfort conditioning and hot water generation are integrated and all distributed within the conditioned space. On-Site Energy Generation and Storage High Priority 1. Homes will utilize suitably sized, on-site renewable/alternative energy equipment such as solar photovoltaics, solar thermal, fuel cells, micro-turbines for cogeneration to generate power and heat; these will potentially have energy storage capacity and communicate with the smart grid to optimize pricing and meet critical electrical loads. The results of this project stress that the biggest challenge for all zero energy projects is the best fit of energy saving design and technology combined with renewable energy utilization. These challenges are especially challenging if a renovation project is intended to be a net zero energy building. 358 | Page 11.9. Assessment of the project methodology and the building models The project methodology used to analyse the three different types of buildings was based on three different case studies: the Base, the Refurbishment and Best practice case. The basic idea was the simulation of buildings in different chronological periods: construction in the past, the present and the future. This approach included three dimensional analyses. The first concerned the building type and energy performance based on the use of the building space and provided valuable information about the energy demands of the different types of building and different uses of the building. This was why one essential factor was the systems operational profiles where the real energy needs of the building were adequately covered by autonomous systems. The second dimension was the type of construction and construction materials. This analysis revealed key information about the construction of the building and the impact of the construction materials on energy performance. Additionally, the analysis stressed the importance at an early stage of decisions that affect the whole building performance during its life. The third dimension was the evaluation of the various energy measures and regulations developed for the building sector over a period of time. This approach tried to set out the steps made in the Cyprus building sector until now, the measures that could be carried out for existing buildings to become low energy, and the steps needed in order for future buildings to be Zero energy. The essential feature of this analysis was the suggested bridging between old and new buildings in order to achieve the desired low energy buildings in accordance with European regulations. Another important aspect of the methodology used during the project analysis was the climatic conditions. The building was analysed as a living body which interacts with the external environment with external conditions playing a vital role in the building energy performance and interior conditions. A major part of the project success was the updated simulation weather files due to their impact on the building fabric and systems. The building models: the single family house-the office building-and the residential building were chosen carefully to be representative of the Cyprus building stock. Furthermore, the three building models existed not only on paper but were real buildings that had been developed in Cyprus. 359 | Page This made it possible to obtain feedback from the engineers responsible for the construction and their feedback and experience from the field contributed positively so that the results would be more realistic and representative of the case studies. The realistic approach was a priority for this research and is the main reason why all the building plans are based on contracted buildings. Generally the methodology of the research covered a wide range of building factors related to reducing energy and transforming the building into a Zero energy building. The deep analysis of multiple factors returned a complete picture of the development of zero energy buildings in hot climate countries and the results provide engineers and architects with a basis for choosing optimal building design and construction while at the same time proposing effective methods for the achievement of zero energy building. 360 | Page Chapter 12: Conclusion 12.1. Conclusions The objective of this project was to develop a zero energy building for hot climate countries using theoretical analysis and building simulation. The project is based on two axes: the first being the theoretical approach and the second the design/simulation approach. However, since there is no commonly accepted definition of “zero energy buildings”, before taking an experimental approach a theoretical approach had to be taken through the simulation of building models. The objective of this project was formulated taking into account both global and Cyprus energy problems as well as the latest scientific progress in building sectors and renewable energy resources. However, an important issue arising from the literature review revealed the lack of a common definition or common understanding of what zero energy building means. In European countries there are various definitions and approaches targeting different goals in energy reduction but the aims of zero energy building as defined in the literature review influenced the options chosen to achieve the development of zero energy building. The second issue discussed in the literature review concerned Cyprus weather conditions and weather files used for energy simulations. The issue of weather was an important element in the development and success of the project as the simulation is based on weather data sets. However, due to the lack of updated weather simulation files, these weather data sets needed updating during the simulation program in order to give more accurate results closer to actual weather conditions. Thus, new files needed to be constructed from the collected eleven years of data of Cyprus weather conditions and used by the simulation program to provide an accurate estimation of the energy performance of the simulation buildings. The third significant outcome of the literature review was the analysis of the Cyprus electricity power generation and distribution systems, This analysis was essential for understanding the building sector’s impact on the overall energy supply scenario and revealed future problems with the Cyprus electricity supplies as demand grows and the power plants will be either unable to cope or, if they can cope, the cost of covering electricity needs will be extremely high. In fact, during the latter stages of the project, difficulties arose with the Cyprus supply system. Without major measures being put in place, the Cyprus grid will be unable to meet future increasing demand. As the building sector has a strong impact on the 361 | Page energy supply, immediate measures will help Cyprus to reduce energy demand while creating more energy efficient buildings. Transformation of the building sector will help not only to save energy in general but will also make a positive contribution to the generation of energy through the development of renewable systems in buildings. The aim of this analysis was to describe the problem of the energy sector in Cyprus and stress the importance of the development of Zero Energy buildings. The transformation of the building sector in combination with other energy measures will offer low cost solutions and make an immediate contribution to the energy supply. The project went on to address the development of three different building simulation models: the single family house, the office buildings and the residential buildings of the Cyprus market. The building models were actually based upon existing buildings located in Limassol, which provided the project with the unique opportunity to obtain feedback from the field and from the contractor engineers. Collaboration between the research team and the contractor engineers made a positive and valuable contribution during the project development resulting in the approach of the case studies being as realistic as possible. The simulation values of the HVAC systems, construction materials, method of construction and insulation were taken from the field to achieve accurate results from the simulation procedure. Case studies findings showed that refurbishing and transforming buildings into low energy buildings is actually feasible and the reduction of energy consumption in existing buildings is highly significant as they represent the larger percentage of building stock. However, the author believes that in order to transform the findings of this thesis into accepted practice, radical review and tightening of energy regulations and standards for Cyprus are imperative, as at the time of writing, Cyprus appears to be unable to meet its obligations arising from the EPBD. Furthermore, the theoretical analysis combined with the building simulation revealed the need for an exact definition of zero energy buildings in Cyprus to clarify for the benefit of engineers and construction companies how this goal may be achievable,. The project attempted to highlight the factors involved in the considerable reduction of energy and set out guidelines for a successful zero energy building. Finally, the project results stress the need for a transformation of the building market in order to achieve the potential benefits of zero energy buildings in hot climate countries like Cyprus. 362 | Page 12.2. Limitations of the project The theoretical research of the project explores the global and European problem concerning the issue of zero energy buildings and their development. However, the experimental research is limited to one European country, the Island of Cyprus. The project studies the two main building categories: residential and commercial, focusing on new generation buildings under development in Cyprus. Criteria are chosen based on their relevance to the aim of this project focusing on construction and insulation materials, glazing type, HVAC systems, thermal comfort and building operation profiles. Furthermore the simulation weather files were comprehensively analysed and, apart from the weather file included in the simulation program, the project used files constructed after gathering real meteorological data from Cyprus Another project limitation was the analysis of lighting and renewable energy systems. The IES programs offered the lighting analysis but at that time failed to include the option to use led lights and study the impact on the building’s energy consumption compared with common lighting systems. In addition, the section on renewable energy systems was not fully developed and did not include all available renewable systems. The use of led lighting analysis in combination with the use of different renewable systems on zero energy building is essential because small things make the difference in reaching zero. 12.3. Barriers and difficulties that may lead to delays in achieving zero energy buildings in Cyprus. Investigating the development of zero energy buildings in Cyprus involved examining many parameters and factors; one of the most important findings is that as you approach zero, small items become significant. Thus the theoretical research in combination with the experimental procedure for zero energy buildings identified the barriers and difficulties that may lead to delays in achieving the national energy targets for 2020 and the development of zero energy buildings. These barriers are classified in three categories related to broader institutional and economic environment, the characteristics of the construction sector, and the quantitative and qualitative fulfilment of skills needs. 363 | Page In the first category, broader institutional and economic environment, as the main barriers for this category the project identifies the economic crisis, poor enforcement of town planning and building regulations, the weaknesses of policies for the improvement of energy efficiency and energy saving and the small market for energy saving and RES systems. In the second category, construction sector characteristics, the project identifies the fragmentation of the construction sector, the large number of small enterprises and self- employed and the large number of EU and third country nationals employed in Cyprus systems. In the third category, quantitative and qualitative fulfilment of skills needs, the main barriers for this category were identified as low enrolment percentage in technical vocational education, the technical vocational education and training infrastructure and trainers and the absence of a framework for the regulation and certification of technical occupations. However, there is considerable room for improvement for the achievement of zero energy building targets if the government authorities continuously monitor the construction sector, hire adequately skilled and trained human resources and take measures to meet the needs of the market related to zero energy building construction. Various challenges and barriers can impede the installation and efficient use of technology and equipment in zero energy buildings, the first being risk factors involved in the use of new technology, limited ways of assessing the benefits, non-integration of zero energy ideas, initial and operating costs, and a general reluctance to accept unfamiliar new technology with unknown benefits. Secondly, government energy policies inspire uncertainty about investment decisions involving energy efficiency and investment cost for renewable energy systems may discourage developers, designers, and owners from choosing technologies only because they are energy-efficient. Thirdly, there is as yet no standard definition of a zero energy building, but only many different definitions. Lack of standard definitions makes it difficult for consumers to determine the quality of the zero energy building and a standard definition for zero energy building would give builders and consumers a specific context for the benefits of zero energy buildings. 364 | Page 12.4. Suggestions for improving the energy performance of building in Cyprus The first essential step towards zero energy buildings concerns the building codes which play a vital role in developing and improving buildings energy efficiency as they stipulate mandatory energy standards of buildings during the construction of new buildings or renovation of old ones. In Cyprus the promotion of energy efficiency in buildings through public policy is quite new and the recasting of the EPBD is still under consideration with no significant action having been taken. The building codes in Cyprus are new so the effects of the policies have so far not been assessed and the Cyprus building codes need to be strengthened to ensure effective enforcement of energy efficiency in buildings. The results of the refurbishment of the buildings showed that the method of operational improvements and retrofitting on existing buildings is an essential ingredient for achieving extensive improvements in energy efficiency. Until now retrofitting building codes do not include energy measures or energy efficiency improvements of the building so it is important to introduce building codes related to the improvement of building energy and force owners to apply the necessary measures during renovation. Monitoring and evaluation is essential for supporting public policy approaches but development projects lack control and monitoring on the part of the Cyprus authorities. Effective monitoring and evaluation combined with the training and certification of experts is the key to successful action in the direction of zero energy buildings. Another important point is the issue of construction materials and design. For instance, the use of extensive external glazing surfaces should be avoided in hot climate countries as air conditioning, cooling or heating, is more problematic and demands more energy due to the considerable losses of the glazing surfaces. Moreover, in Cyprus cooling demand is high and is satisfied by split unit heat pumps. In contrast to other EU countries where heating demand is satisfied by central heating systems, the heating demand of more than half the dwellings in Cyprus is covered by split unit heat pumps, meaning that the “quick start up” heat pumps are used for a shorter time periods per day.[177] Additionally, insulation - particularly externally – impacted considerably impact on the building performance with the external insulation protecting the building from overheating due to long exposure to sun radiation. 365 | Page In hot climate countries external shading is essential for the comfort of internal spaces. The use of external shadings controlled by operational profiles improved building performance and reduced cooling demand during the spring and summer so it is imperative that building codes include measures for the development of external shading incorporating photovoltaic systems. Due to the weather conditions there is great potential for the integration of photovoltaic systems on new and old buildings. Until now there has been no policy to force contractors to integrate renewable systems on buildings for reducing energy demand and it is vital for the Cyprus building sector to transform each building from an energy consumer into an energy producer. 12.5. The most important elements identified for a future guidance. The research results respond to the project stated research question which arose at an early stage. The research results permit the establishment of design criteria for building types encountered in Cyprus which will deliver zero energy performance under the weather conditions likely to be experienced and in addition highlight the key factors involved in improving building performance. The project identified and summarised some of the main elements for future guidance on zero energy buildings. The first concerns guidelines for HVAC equipment for zero energy buildings applications. In some cases, there are standards which contractors fail to keep to resulting in oversized HVAC systems and less efficient buildings. The contractors’ perspective is that failing to over-size may increase the number of callbacks for insufficient capacity. Secondly, guidelines are needed concerning automation and controls of building components such as lighting, appliances, plug loads and so on in order to aid the use of automation and controls for reducing power usage throughout the building. Already existing standards could be adapted, such as the Smart Energy Profile 2.0, by the ZigBee Alliance, and the ASHRAE/ National Electrical Manufacturers Association (NEMA) Standard 201—Facility Smart Grid Information Model for management of electrical loads. [178][179] Thirdly, better guidance is needed to encourage greater use of day-lighting as a regular component of zero energy buildings and studies should show the secondary benefits of natural lighting, such as increased worker efficiency. 366 | Page Fourth is the control of indoor air quality: Tighter construction of zero energy buildings requires better ventilation so guidelines are essential to make sure that the construction and technology of zero energy buildings do not affect indoor air quality. Indoor air quality can be controlled by limiting emissions, and improving filtering, cleaning, and ventilation systems. Fifth concerns guidelines for building envelope load control: There should be guidelines for control of envelope loads, including solar, conduction, convection, moisture, air, and infiltration as well as for commissioning and inspection. The potential unintended consequences of high-performance buildings need to be understood (for instance, structural deterioration, corrosion, mold, moisture in walls etc) when the systems are not integrated or suitable construction/installation practices not adhered to. 12.6. Project recommendations and contribution Definitions of what constitutes zero energy buildings are not yet available in Cyprus but they are essential in order to inform the building sector and propose equipment solutions. Some of the proposed zero energy definitions fail to provide satisfactory information on the desired “energy threshold” for optimizing building energy consumption.. Government authorities need to produce a framework for the construction of zero energy buildings which will serve the purpose of energy efficiency. This is a preliminary step towards aiding the establishment of a building design strategy that will contribute to the goal of global sustainability. Government authorities should focus on: 1. Renewable energy options needed to assist understanding and enable the selection of on- site power and heat generation, including fuel cells, solar, wind and geothermal systems. 2. Incentives needed to encourage designers, builders and homeowners, to select zero energy technologies and properly operate and maintain them. 3. Consumers, builders, government, insurers, and realtors need to be educated on the value and benefits of zero energy buildings. Furthermore, the project results stress the importance of the weather data, the Cyprus power system and the construction materials, issues that were directly related with the project development but not the main focus of the research. The results of the weather research showed that only in one location was it not possible to give accurate estimations due to the microclimate differences. In addition, using the 367 | Page calculations based on old files it was impossible to obtain the climate changes and incorrect estimations for the building performance were returned. It is suggested that the IES company provides the simulation weather files stating the time period of the weather file, the origin of weather data, the station where the data was collected and the method used for data collection (such hourly data, monthly data or something else). Another significant omission was noted with hourly weather data provided by the Cyprus Meteorological services. During collaboration with the responsible authority the project searched for test reference years (TRY) for Cyprus towns but these types of data were non- existent or, if they existed, they were not up to date. There was also a limitation to the available data the project could use due to the cost of the weather data sets. The project needed to find a solution and create update weather files by using the available hourly data from the Cyprus Meteorological Services. The project proposes that the Cyprus Meteorological Services should create test reference years for all the towns based on 20-30 year averages. These weather files could be used in simulation procedures and return accurate estimations for the building performance in each location. The future weather predictions that will be based on these files will return better results as they will take into account the 20 or 30 years data. The construction materials and systems included in the simulation program need updating. During the simulation some construction materials that are widely used (such as Cyprus bricks) could not be found in the simulation data base, which was a serious issue during the construction of the simulation model. Furthermore, new materials, such as the phase change materials (PCM) or the super multi-layer insulation were also non-existent in the database of the program. These materials could be widely use in zero energy buildings and in combination with design and energy measures they will further reduce the energy demand (heating and cooling) of the building. To make the simulation more realistic and achieve better efficiencies, the IES Company needs to include new materials and new systems (database upgrades) so that building simulation projects could include high technology materials and systems to achieve zero energy goals. The IES Company also needs to revise the standards (such as comfort levels) used on the program for comparison purposes. Most of these are based on United States rather than EU values and while some were close to or similar to EU regulations, the comparison and results were presented according to United States standards (ASHRAE). Consequently, the 368 | Page simulation program needs upgrading to offer comparisons and results based on the EU standards. By basing project recommendations on the development procedure of the research with different parameters identified in the early stage, the project could focus on fundamental issues directly related with the project development and completion. This enabled the project to respond to the research needs and to contact responsible authorities in order to make the essential recommendations. 12.7. Future work The project development investigation of the research proposal for zero energy buildings revealed new areas for research requiring further in depth investigation to achieve more accurate results concerning the development of zero energy buildings in hot climates. Firstly, since climatic conditions affect the building envelope and interior conditions, climate and microclimate conditions also need further study. Updated weather files are essential as well as a need to investigate how microclimate conditions affect the construction of test reference years. The impact of the updated weather files on simulation results also needs further study as many of the estimations are based exclusively on the simulation weather files. Generally interaction between buildings and hot-humid climates needs further analysis as it was not one of the main priorities of this research. Secondly, the combination of the project energy saving measures using natural processes such as natural ventilation and natural lighting together with the use of natural ventilation and thermal mass activation also need further investigation. The improvement in daylight use will contribute positively to the energy reduction policy as interior space lighting is a current issue due to its use for decoration purposes. These two issues play key roles in building energy consumption. Thirdly, for many years most buildings in Cyprus were constructed with bricks and concrete and the “traditional” construction methods and materials used need replacing with new methods and high tech materials. The use of new materials and methods may reduce construction costs, require less time for project completion and reduce energy demands of building. These areas require further investigation as the method and materials of construction play a decisive role in building energy performance. 369 | Page Finally, a detailed examination of Life Cycle Assessment and building energy use of zero energy buildings (life cycle environmental impacts of the materials phase of a zero energy building) is needed. Rising numbers of zero energy buildings increase the need to consider embodied energy from building materials, especially as it affects the building’s life cycle energy use. 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Do background research 3. Project rationale(justification) 4. Write report on Literature review 5. Establish Design Criteria 6. Design investigation and identify resources available 7. Learn how to use computer packages 8. Prepare Preliminary Designs 9. Analyse data 10. Build and Test a Prototype 11. Redesign & Retest as Necessary 12.Present Results 13. Write report-Make changes 14. Meeting with supervisor 15. Holidays 16. Write report on findings (First draft of 18 month report) 17. Final draft of 18 month report 18. First draft of 24 month report, including second investigation 19. Final draft of 24 month report 20. Carry out further research and/or analysis 21. Prepare chapter headings and drafts 22. Complete and submit paper for conference (drafts and completed paper) 23. Prepare second drafts of chapters 24. Complete and submit paper to journal 25. Complete and submit final draft of thesis 26. Prepare for Viva 385 | Page 2st year Numbered tasks Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1. Literature review-Define a need 2. Do background research 3. Project rationale(justification) 4. Write report on Literature review 5. Establish Design Criteria 6. Design investigation and identify resources available 7. Learn how to use computer packages 8. Prepare Preliminary Designs 9. Analyse data 10. Build and Test a Prototype 11. Redesign & Retest as Necessary 12.Present Results 13. Write report-Make changes 14. Meeting with supervisor 15. Holidays 16. Write report on findings (First draft of 18 month report) 17. Final draft of 18 month report 18. First draft of 24 month report, including second investigation 19. Final draft of 24 month report 20. Carry out further research and/or analysis 21. Prepare chapter headings and drafts 22. Complete and submit paper for conference (drafts and completed paper) 23. Prepare second drafts of chapters 24. Complete and submit paper to journal 25. Complete and submit final draft of thesis 26. Prepare for Viva 386 | Page 3rd year Numbered tasks Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1. Literature review-Define a need 2. Do background research 3. Project rationale(justification) 4. Write report on Literature review 5. Establish Design Criteria 6. Design investigation and identify resources available 7. Learn how to use computer packages 8. Prepare Preliminary Designs 9. Analyse data 10. Build and Test a Prototype 11. Redesign & Retest as Necessary 12.Present Results 13. Write report-Make changes 14. Meeting with supervisor 15. Holidays 16. Write report on findings (First draft of 18 month report) 17. Final draft of 18 month report 18. First draft of 24 month report, including second investigation 19. Final draft of 24 month report 20. Carry out further research and/or analysis 21. Prepare chapter headings and drafts 22. Complete and submit paper for conference (drafts and completed paper) 23. Prepare second drafts of chapters 24. Complete and submit paper to journal 25. Complete and submit final draft of thesis 26. Prepare for Viva 387 | Page Appendix B: Reference Building Detailed definition of Reference Building in Cyprus Calculation Methodology (MAEPB) 1. The reference building has the same size, shape and zoning arrangements as the actual building, with the same conventions relating to the measurement of dimensions. 2. Each space contains the same activity as proposed for the equivalent space in the actual building. The activity of each space is selected from the list of activities as defined in the activity database. 3. The reference building has the same orientation and is exposed to the same weather as the actual building. The reference building is subject to the same site shading from adjacent buildings and other topographical features as are applied to the model of the actual building. 4. Whatever system type (heating, ventilation, cooling) is specified in a zone in the actual building is also being provided in the reference building. However, if heating were provided to either of these spaces in the actual building, then heating is correspondingly be specified in the reference building, and then both buildings are heat those spaces to the heating set point specified for the zone type in the database. Building fabric 5. The U-values of the reference building are specified in the table 123. The reference constructions conforming to these U-values are identified in the table by their reference identities. 6. In addition, the U-values of display windows are taken as 6 W/m2K in both the Reference building and the actual building for residential and non-residential building. Table 77: U-values in the reference building 7. Thermal bridge heat losses for each element (including windows etc) is assumed have no effect on the U-values for both residential and non-residential building. 8. Special considerations apply to ground floors; the U-value is 1,6 W/m2K in reference building regardless the value in the actual building. 9. When modelling an extension, the boundary between the existing building and the extension can be disregarded (i.e. assume no heat transfer across it) 10. The thermal capacity of the construction elements in reference building are defined in Table 124. 11. The air permeability of the Reference building is 10m3/(h.m2) at 50 Pa. The calculation method used to predict the infiltration rate use the air permeability as the parameter defining the envelope leakage. 388 | Page Table 78: Effective thermal capacity (KJ/m2.K) of construction elements in the reference building Solar and daylight transmittance 12. Total solar energy transmittance of glazing and the daylight transmittance are given in the following table. These data apply to all windows, roof windows, roof lights and display windows. The data are based on a normal incidence value of 0,655 for solar transmittance and 0,8 for daylight transmittance for both residential and non-residential building. Appropriate values for intermediate orientations can be based on linear interpolation. 13. This variation in the solar and daylight transmittance with orientation is not an attempt to model varying daylight availability when using an overcast sky model. It is a pragmatic solution to achieving a building design that meets the heat loss and the avoiding solar overheating requirements. Table 79: Solar and daylight transmittances 14. The areas of windows, doors and rooflights in the reference building are determined as set out in the following sub-paragraphs. For the residential building a. All external walls have windows, and roof lights use the copy of the areas of windows and roof lights from actual building. b. Copy the areas of pedestrian doors, vehicle access doors and display windows that exist in the corresponding element of the actual building. c. If the total area of these elements is less than the appropriate allowance from Table 4, the balance need to made up of windows or roof lights as appropriate. d. If the total area of the copied elements exceeds the allowance from Table 4, the copied areas need to be retained but no windows or roof lights added. 389 | Page For the non-residential building e. Copy the areas of windows, roof lights, pedestrian doors, vehicle access doors and display windows that existing in the corresponding element of the actual building for all types of the buildings. For the residential & non-residential building f. The areas as defined in Table 4 represent the areas of opening in the wall or roof, and comprise the area of the glass plus frame. The windows have a frame factor of 25% (i.e. 75% of the area of the opening is glazed) and as well as the roof lights. Table 80: Opening areas in the Reference building 15. In addition, the following rules apply: a. The reference building has the same area of any high usage entrance doors as present in actual building. b. In the reference building, pedestrian and vehicle access doors are taken as being opaque, i.e. with zero glazing. c. No glazed area should be included in basements. In semi-basements, i.e. where the wall of the basement space is mainly below ground level but part is above ground, the Table 126 percentages apply to the above ground part, with zero glazing for the below ground part. HVAC System definition 16. Each space in the Reference building will have the same level of servicing as the equivalent space in the actual building. In this context, “level of servicing” means the broad category of environmental control, i.e.: a. unheated b. heated only with natural ventilation c. heated only with mechanical ventilation d. air conditioned e. mixed mode, where cooling only operates in peak season to prevent space temperatures exceeding a threshold temperature higher than that normally provided by an air conditioning system. 17. A space is only considered as having air-conditioning if the system serving that space includes refrigeration. Night cooling using mechanical ventilation is not air-conditioning. If the same mechanical ventilation system that is used for night cooling is also used to provide normal ventilation, then the space should be regarded as being mechanically ventilated. Any boosted supply 390 | Page rate required to limit overheating is ignored in the Reference and actual building, but it will be necessary to separately demonstrate that the space will not overheat. If the mechanical ventilation system only operates in peak summer conditions to control overheating and during normal conditions ventilation is provided naturally, then the space is regarded as naturally ventilated and the mechanical ventilation system can be ignored in both Reference and actual buildings. 18. By maintaining the increased natural ventilation until internal temperatures fall to the (high) heating set point, the temperatures at start up next day will be neither artificially high or low. 19. If the actual building includes humidity control, this be ignored in both the Reference and the actual building. 20. In the reference building, for hot water, the main fuel is Diesel oil regardless the fuel type used in the actual building for both residential and non-residential building 21. The heating, cooling and auxiliary energy be taken as powered by grid-supplied electricity. 22. The system performance definitions follow the practice set out in EN 15243(EN 15243, Ventilation for Buildings - Calculation of room temperatures and of load and energy for buildings with room conditioning systems, CEN, 2007) : a. Auxiliary energy is the energy used by controls, pumps and fans associated with the HVAC systems. b. Heating Seasonal Coefficient of Performance (SCoP) is the ratio of the sum of the heating demands of all spaces served by a system to the energy content of the fuels (or electricity) supplied to the boiler or other heat generator of the system. The SCoP includes boiler efficiency, heat losses in pipe work, and duct leakage, It does not include energy used by fans and pumps, but does include the proportion of that energy that reappears as heat within the system. c. The Seasonal System Energy Efficiency Ratio for cooling (SSEER) is the ratio of the sum of the sensible cooling demands of all spaces served by a system to the energy content of the electricity (or fuel) supplied to chiller or other cold generator of the system. Inter alia, chiller efficiency, heat gains to pipe work and ductwork, duct leakage and removal of latent energy (whether intentional or not), It does not include energy used by fans and pumps (but does include the proportion of that energy that reappears as heat within the system). Table 81: HVAC Seasonal system efficiencies in the Reference building Residential Building 391 | Page 23. The auxiliary energy per unit floor area be calculated as follows: a. For heated only spaces: the product of 0,61 W/m2 and the annual hours of operation of the heating system from the activity database. b. For mechanically ventilated spaces: the product of the outside air rate for the space, the annual hours of operation (both from the activity database) and the appropriate specific fan power from Table 128. c. For air-conditioned spaces: the product of the annual hours of operation times the greater of: i. the product of the fresh air rate and the appropriate SFP from Table 82 and ii.8,5W/m2. Table 82: Specific fan power for different ventilation systems 24. In the reference building a. No allowance is made for heat recovery equipment. b. No allowance is made for demand control of ventilation. 25. HWS overall system efficiency (including generation and distribution) is taken as 45% with the fuel assumed to be diesel oil. The energy demand be taken as that required to raise the water temperature from 10oC to 60oC based on the demands specified in the activity database. 26. The reference building is assumed to have no power factor correction or automatic monitoring and targeting with alarms for out of range values. Installed lighting power density in the Reference Building 27. For general lighting: a. In office, storage and industrial spaces, divide by 100 the illuminance defined for the space as given in the activity database, then multiply by 3.75 W/m2 per 100 lux. This includes all spaces that accommodate predominantly office tasks, including classrooms, seminar rooms and conference rooms, including those in schools. b. For other spaces, divide the illuminance appropriate to the activity in the space by 100, and then multiply by 5,2 W/m2 per 100 lux. 28. For display lighting, take the Reference display lighting density appropriate to the activity from the activity parameter database. 29. In all cases, the duration of the lighting demand is as per the activity schedule in the database. 30. It is assumed that the general lighting in the Reference building has local manual switching in all spaces. 392 | Page Appendix C: Results presentation with Climate Consultant (example pages) All the results of future weather predictions for 2020, 2050 and 2080 are presented for three Cyprus towns (Limassol, the Larnaca and Nicosia) in e-Appendix 1, which is included on the cd under the name I-e-APPENDIX 1. The following graphs present the weather simulation files with the future predictions for 2020, 2050 and 2080. • Larnaca weather data for 2020: Figure 141: Larnaca 2020 Monthly Diurnal Averages for Temperature and Radiation 393 | Page Figure 142: Larnaca 2020 Radiation Range, Hourly Averages. 394 | Page Figure 143: Larnaca 2020 Dry Bulb vs Humidity. 395 | Page Figure 144: Larnaca 2020 Wind Speed 396 | Page Figure 145: Larnaca 2020 Psychometric chart 397 | Page Appendix D (example pages): The CYP_Larnaca.176090_IWEC weather data file All the results of IES program weather data file are given in e-Appendix 2, which is included on the cd under the name I-e-APPENDIX 2. The following information was taken from the CYP_Larnaca.176090_IWEC and showed clearly the simulation data based on 30 years data for the period 1969 till 1999. Table 83: Statistics for CYP_Larnaca.176090_IWEC A/C Statistics for CYP_Larnaca.176090_IWEC 1 Location -- LARNACA - CYP -{N 34° 52'} {E 33° 37'} {GMT +2.0 Hours} 2 Elevation -2m above sea level- Standard Pressure at Elevation -101301Pa 3 Data Source -IWEC Data- Year 1969-1999- WMO Station 176090 4 Using Design Conditions from "Climate Design Data 2009 ASHRAE Handbook". If the design condition source is ASHRAE, the design conditions are carefully generated from a period of record (typically 30 years) to be representative of that location and be suitable for use in heating/cooling load calculations 5 Climate details: 3442 annual cooling degree-days (10°C baseline) 22 annual heating degree-days (10°C baseline) 1259 annual cooling degree-days (18°C baseline) 759 annual heating degree-days (18°C baseline) 6 Climate type "Cfa" (Kφppen classification)** Humid subtropical (mild with no dry season, hot summer, lat. 20-35°N) **Note that the Kφppen classification shown here is derived algorithmically from the source weather data. It may not be indicative of the long term climate for this location. 7 Climate type "3A" (ASHRAE Standards 90.1-2004 and 90.2-2004 Climate Zone)** Warm - Humid, Probable Kφppen classification=Cfa, Humid Subtropical (Warm Summer) **Note that the ASHRAE classification shown here is derived algorithmically from the source weather data. It may not be indicative of the long term climate for this location. 8 Typical/Extreme Period Determination Summer is Jun-Aug Extreme Summer Week (nearest maximum temperature for summer) Extreme Hot Week Period selected: Jul 27: Aug 2, Maximum Temp=36.50°C, Deviation=| 7.272|°C Typical Summer Week (nearest average temperature for summer) Typical Week Period selected: Jun 29: Jul 5, Average Temp=26.58°C, Deviation=| 0.054|°C 9 Winter is Dec-Feb Extreme Winter Week (nearest minimum temperature for winter) Extreme Cold Week Period selected: Feb 3: Feb 9, Minimum Temp=1.00°C, Deviation=| 8.019|°C Typical Winter Week (nearest average temperature for winter) Typical Week Period selected: Jan 27: Feb 2, Average Temp=12.28°C, Deviation=| 0.002|°C 10 Autumn is Sep-Nov Typical Autumn Week (nearest average temperature for autumn) Typical Week Period selected: Oct 27:Nov 2, Average Temp= 21.36°C, Deviation=| 0.040|°C 11 Spring is Mar-May Typical Spring Week (nearest average temperature for spring) Typical Week Period selected: Apr 12-Apr 18, Average Temp= 17.12°C, Deviation=| 0.617|°C 398 | Page The Figure 146 shows the IES weather data Average (arithmetic mean) Hourly Statistics for Dry Bulb temperatures °C for Larnaca town, during the period 1969-1999. Figure 146: Average (arithmetic mean) hourly statistics for dry bulb temperatures °C for Larnaca town, during the period 1969-1999 399 | Page Appendix E (example pages): The IES weather data (LarnacaWYEC.fwt) All the results of IES program weather data file are given in e-Appendix 3, which is included on the cd under the name I-e-APPENDIX 3. • Weather data and results: IES weather data (LarnacaWYEC.fwt) The following weather data were extracted from the LarnacaWYEC.fwt, a weather simulation file that is based on data from 1985 to 1995. The data format included repetitive months in order to construct the 10-year weather simulation file. The file included data for dry bulb temperature, relative humidity, wind direction and wind speed. The extracted data was compared with the Cyprus weather data that was collected by the Cyprus Meteorological Services for the period 1997-2008. The green bars are showing the percentage difference from the comparison of the two different sources of data. 400 | Page 28 9.0 27 8.5 26 25 8.0 24 23 7.5 22 7.0 21 20 6.5 19 6.0 18 5.5 C 17 ° 16 5.0 15 14 4.5 13 Temperatures Temperatures 4.0 12 11 3.5 Percentage difference % 10 9 3.0 8 2.5 7 6 2.0 5 1.5 4 3 1.0 2 0.5 1 0 0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of the day Percentage difference % MAY(1985) MAY(1997-2008) Figure 147: Comparison of average (arithmetic mean) hourly statistics for dry bulb temperatures °C for May and Percentage difference % 401 | Page 22 30 21 28 20 26 19 24 18 17 22 16 20 15 18 14 C 16 ° 13 12 14 11 12 10 Temperatures Temperatures 10 9 8 Percentage difference % 8 6 7 6 4 5 2 4 0 3 -2 2 1 -4 0 -6 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of the Day Percentage difference % DEC(1985) DEC(1997-2008) Figure 148: Comparison of average (arithmetic mean) hourly statistics for dry bulb temperatures °C for October and Percentage difference % 402 | Page Appendix F: Cyprus Meteorological Office weather data analysis (example pages) All the results of Cyprus Meteorological Office weather data analysis file are given in e- Appendix 4 , which is included on the cd under the name I-e-APPENDIX 4. The Figures 149 show the temperature comparison between the Limassol and Nicosia meteorological stations data. 40 16 38 15 36 14 34 32 13 30 12 28 11 C ° 26 10 24 22 9 20 8 18 Temperatures Temperatures 7 16 6 14 Percentage Percentage difference % 12 5 10 4 8 3 6 2 4 2 1 0 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Mean Values Percentage difference % Mean Temperature -Nicosia Mean Temperature Limassol Figure 149: Comparison of mean temperature values and percentage difference % for Nicosia and Limassol (1997-2008). 403 | Page 42 50 40 38 45 36 34 40 32 30 35 28 C ° 26 30 24 22 25 20 Temperatures Temperatures 18 Percentage difference % 20 16 14 12 15 10 8 10 6 4 5 2 0 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Month Highest Values Percentage difference % Lowest Values Percentage difference % Highest Temperature -Nicosia Highest Temperature Limassol Lowest Temperature -Nicosia Lowest Temperature Limassol Figure 150: Comparison of mean temperature values and percentage difference % for Nicosia and Limassol (1997-2008). 404 | Page Appendix G: Single family house-Detail simulation input data (example pages) All the Detail simulation input data is given in e-Appendix 5 , which is included on the cd under the name I-e-APPENDIX 5. 1. Single family house-drawings Figure 151: Single family house simulation model in IES (front and site view) 405 | Page Figure 152: Single family house simulation model in IES-plan view ground and first floor 406 | Page Figure 153: Single family house simulation model in IES- axonometric view 407 | Page Figure 154: Single family house simulation model in IES-dimensions view(front site) 408 | Page Appendix H- Office Building-Detail simulation input data(example pages) All the Detail simulation input data is given in e-Appendix 6 , which is included on the cd under the name I-e-APPENDIX 6. 1. Office Building-drawings Figure 155: Office Building simulation model in IES (front view) 409 | Page Figure 156: Office Building simulation model in IES (site view) 410 | Page Figure 157: Office Building simulation model in IES (back view) 411 | Page Figure 158: The original office buildings plans in AutoCAD software- plan view 412 | Page Figure 159: Office Building simulation model in IES (axonometric right view) 413 | Page Appendix I- Olympic Residence building-Detail simulation input data(example pages) All the Detail simulation input data is given in e-Appendix 7 , which is included on the cd under the name I-e-APPENDIX 7. 1. Olympic Residence building-drawings Figure 160: Olympic Residence building simulation model in IES (front view) 414 | Page Figure 161: Olympic Residence building simulation model in IES (site view) 415 | Page Figure 162: Olympic Residence building simulation model in IES (back view) 416 | Page Figure 163: Olympic Residence building simulation model in IES (top view) 417 | Page Figure 164: Olympic Residence building simulation model in IES (right view) 418 | Page