energies
Article NPC Based Design Optimization for a Net Zero Office Building in Hot Climates with PV Panels as Shading Device
Muhammad Zubair 1,* ID , Ahmed Bilal Awan 1 ID , Abdullah Al-Ahmadi 1 and Ahmed G. Abo-Khalil 1,2
1 Department of Electrical Engineering, College of Engineering, Majmaah University, Majmaah 11952, Saudi Arabia; [email protected] (A.B.A.); [email protected] (A.A.-A.); [email protected] (A.G.A.-K.) 2 Electrical Engineering Department, Faculty of Engineering, Assiut University, University Street, Assiut 71515, Egypt * Correspondence: [email protected]; Tel.: +966-591-014-386
Received: 19 April 2018; Accepted: 28 May 2018; Published: 30 May 2018
Abstract: Hot areas of the world receive a high amount of solar radiation. As a result, buildings in those areas consume more energy to maintain a comfortable climate for their inhabitants. In an effort to design net-zero energy building in hot climates, PV possesses the unique advantage of generating electrical energy while protecting the building from solar irradiance. In this work, to form a net-zero energy building (NZEB), renewable resources such as solar and wind available onsite for an existing building have been analyzed in a hot climate location. PV and wind turbines in various configurations are studied to form a NZEB, where PV-only systems offer better performance than Hybrid PV Wind systems, based on net present cost (NPC). The self-shading losses in PV placed on rooftop areas are analyzed by placing parallel arrays of PV modules at various distances in between them. The effect on building cooling load by rooftop PV panels as shading devices is investigated. Furthermore, self-shading losses of PV are compared by the savings in cooling loads using PV as shading. In the case study, 12.3% saving in the cooling load of the building is observed when the building rooftop is completed shaded by PV panels; annual cooling load decreased from 3.417 GWh to 2.996 GWh, while only 1.04% shaded losses are observed for fully shaded (FS) buildings compared to those with no shading (NS), as PV generation decreases from 594.39 kWh/m2 to 588.21 kWh/m2. The net present cost of the project has been decreased from US$4.77 million to US$4.41 million by simply covering the rooftop completely with PV panels, for a net-zero energy building.
Keywords: shading effect; photovoltaic arrays; energy analysis; renewable energy resources
1. Introduction The modern world is facing extreme weather events every year. In the 20 years from 1996 to 2015, more than 528,000 people died in some 11,000 extreme weather events. Monetary losses add up to around 3.08 trillion US$ [1]. Crops are facing a 10% reduction in productivity because of severe weather events [2]. Global warming by greenhouse gases will melt polar ice, and some areas of the world will be underwater while other will suffer heavy rains and floods, which will cause a shortage of food, as well as desert formation, and mass migrations [3,4]. The main source of global warming is the burning of fossil fuels for electrical energy production and transportation [5]. The solution to global warming the use renewable energy resources, and eventually, completely going green. International efforts against global warming are advancing, with the Paris Accord [6],
Energies 2018, 11, 1391; doi:10.3390/en11061391 www.mdpi.com/journal/energies Energies 2018, 11, 1391 2 of 20 the European Directive 2020 [7], and national directives such as Vision 2030 of Saudi Arabia [8,9]. The Paris Accord seeks to limit the increase in global average temperatures to 1.5 ◦C in 2030, and to achieve net-zero emissions by 2070. The European Union directive focuses on buildings, targeting 20% onsite energy generation, 20% more energy efficiency, and 20% less greenhouse gas emissions from all buildings by 2020. Saudi Arabia announced a plan under Vision 2030 to create a sustainable city, Neom, by the Red Sea on the border of Jordon in Tabuk province. Saudi Arabia also plans to generate 9.5 GW of renewable energy by 2023 [10,11]. In recent years, renewable energy resources are becoming more economically feasible through the development of new technologies. In the past one year, 157 GW of renewable power systems have been installed at a cost of 279.8 billion US$, while 70 GW of fossil fuel energy systems have been decommissioned. China installed an astonishing 53 GW of solar energy systems at a cost of 86.5 billion US$ [12]. Even the Middle East countries such as UAE and Egypt have spent 2.2 and 2.6 billion US$ respectively on solar energy plants. Currently, photovoltaic systems lead the energy production of renewable energy resources in the world [12]. Saudi Arabia awarded a 300 MW project to a ACWA Power, a private investor, in February 2018, with an initial capital cost of 300 million US$ [13]; in March 2018, KSA signed a memorandum with Softbank Group Crop to develop a 200 GW solar plant in multiple phases, with an enormous investment of 200 billion US$ [14]. A lot of research is going on to increase the efficiency of renewable energy resources [15,16]. The research on PV was started analytically in 1950s. Now the dream is to print high energy efficient solar panels on flexible polyethylene terephthalate (PET) substrate, using printed electronics technologies at room temperature and in atmospheric pressure, which can last 25 years [17,18] and retain their efficiencies. The efficiencies of crystalline PV, III-V cell PV, and thin film PV cells have increased to 27.6% [19], 33.3% [20] and 21.7% [21] respectively. Since 2005, PV cell efficiencies have increased at a good rate, as presented by the NREL efficiency chart [22] and review articles [23,24]. PV and Wind energy system prices are decreasing, and producers are finding it difficult to deliver orders on time. This cost is declining as new competitors from Asia have entered this market. The price of solar panels has decreased by 77% from 2010 to 2017 [25–27]. The cost of solar energy systems comprises the system design, panels, inverters, and skilled labor cost. New designs in wind energy with bigger turbines are decreasing technology prices, as these machines have higher power coefficients, which means that they can convert more wind energy into electrical energy. Innovative designs have reduced the use of steel in towers, and methods for making a floating tower for off-grid turbines to place them in deep water are currently in research [12]. The Middle East has abundant renewable resources [10,28,29], and these countries should transform from fossil to renewable. The Kingdom of Saudi Arabia (KSA) is the largest oil exporting country, but huge domestic energy requirements are halting its economic growth [30]. The load profile of Saudi Arabia is unique, as peak load in summers is two times that of winter, because of huge cooling loads of buildings [31,32]. The country has very hot and dry weather [33]. The KSA government has increased electricity prices by 260% from 0.008 US$/kWh. The solution to KSA’s load problems is to curtail building load through the use of onsite renewable resources for buildings. Net-zero energy building (NZEB) can be achieved by generating electrical energy onsite, so that the net energy bought from the grid is equal to the energy sold to the grid. Developed countries have already started to design and build net-zero buildings [34–37], in which smart techniques have been adopted to provide good insulation for buildings, reduce the load by effective use control of heating, ventilation, air conditioning (HVAC), and appliances, and to employ renewable energy systems [38,39]. Modern buildings use both AC and DC energy systems in lighting and appliances to enhance efficiencies and eliminate conversion losses from AC to DC and vice versa [40,41]. Off-grid energy systems require huge capital investment; during periods in which energy from renewable resources is unavailable, energy is taken from storage devices, whereas in net-zero energy systems, backup depends upon the grid. Off-grid systems require more installed capacity to meet the load, and store energy to use later. Energies 2018, 11, 1391 3 of 20
The shading of the building reduces the cooling load [42,43]. The green rooftop has been investigated as a means of lowering building temperatures [44]. PV panels also provide shade and produce energy at the same time [45]. Kim et al. have detailed a net-zero energy by renewable resource system that generates electricity in 30 different projects [46] in various locations in relatively cold climates. In this work, renewable resources for an existing building have been analyzed in a hot weather environment. PV and wind turbines in various configurations are studied to form a net-zero energy building. An area of the rooftop is designed for placement of PV arrays, and self-shading in the PV system is analyzed at various distances between the parallel arrays of the PV modules. The effect on cooling load of the building by rooftop PV panels as shading devices is investigated. Furthermore, self-shading losses of PV are compared to the savings in cooling loads. The site is analyzed for NZEB by solar and wind resources. Finally, the economics of the NZEB with and without rooftop PV arrays are discussed.
2. Methodology The model of an existing building is developed in SketchupPro (Trimble Inc., Sunnyvale, CA, USA). EnergyPlus (National Renewable Energy Laboratory (NREL), Golden, CO, USA) and Euclid (BigLadder Software Inc., Denver, CO, USA) extension for SketchupPro are used for energy consumption analyses. EnergyPlus is a complete building simulation software for analyzing cooling, heating, ventilation, lighting, process load, and water use. The geometry of the building is designed in SketchupPro. Euclid is a toolbar of SketchupPro to run EnergyPlus. An NZEB is achieved with the help of solar and wind resources at the location of the building using HomerPro (NREL). Homerpro is microgrid software for the optimization of the most suitable configuration out of available conventional and renewable energy systems. HomerPro optimizes for a least net present cost (NPC). The placement of PV arrays is proposed on the rooftop and parking area of the building, depending on the load and renewable energy resources of the area. The wind turbines will be placed in an open space beside the building, using a geographic information system (GIS). The self-shading losses in PV panels mounted on the rooftop of the building are analyzed by System Advisory Models ((SAM) (NREL)). SAM uses computer models to evaluate cost and performance of renewable energy projects. The sun daily path is shifted in the winter, and originates in tilt angle variations. The parallel PV arrays are placed at various distances, and the corresponding percentage of losses is recorded. The study of savings in cooling load of the building by shade provided by rooftop PV panels is performed in EnergyPlus (NREL) by placing parallel PV arrays at the same distances as those used for self-shading losses in SAM. The optimal distance for placing parallel PV arrays is evaluated by calculating the net energy analysis by adding energy gains of cooling load to the energy losses due to self-shading. HomerPro (NREL) is used to analyze the renewable energy systems for the building, and achieve a net-zero energy system for various cases such as:
Off-grid hybrid energy system for building with no shading (NS) rooftop by PV arrays to show the benefit of the grid-connected system NZEB with NS on the rooftop with only solar resources NZEB with NS on the rooftop with only wind resources NZEB with NS on the rooftop with solar and wind resources NZEB with fully shaded (FS) rooftop by PV arrays without using wind resources NZEB with FS rooftop by PV arrays using wind resources
The economic benefits of the onsite renewable energy resources by these various configurations are examined to find out the most feasible renewable energy system to attain a NZEB in hot climate areas with and without rooftop shading. Energies 2018, 11, 1391 4 of 20
3. Case Study Analysis KSA has set a target of generating 9.5 GW of electrical energy from renewable energy resources Energies 2018, 11, x FOR PEER REVIEW 4 of 20 byEnergies 2023, 2018 and, 11 of, x FOR building PEER REVIEW a sustainable city by the Red Sea [8,9] under the kingdom Vision4 of 2030.20 KSAhas hasalready already awarded awarded ACWA ACWA Power, Power, a private a private energy energy developer, developer, a contract a contract to develop to develop the first the 300 first has already awarded ACWA Power, a private energy developer, a contract to develop the first 300 300MW MW solar solar power power plant, plant, with withan initial an initial capital capital of 300 MUS$ of 300 in MUS$ February in February 2018 [13]. 2018KSA [and13]. Softbank KSA and MW solar power plant, with an initial capital of 300 MUS$ in February 2018 [13]. KSA and Softbank SoftbankGroup Corp Group signed Corp a signed memorandum a memorandum to develop to developa 200 GW a 200solar GW plant solar with plant an withinvestment an investment of 200 Group Corp signed a memorandum to develop a 200 GW solar plant with an investment of 200 ofBillion 200 billion US$ [14]. US$ In [14 order]. In to order design to designand develop and develop future renewable future renewable energy systems energy in systems KSA and in fill KSA Billion US$ [14]. In order to design and develop future renewable energy systems in KSA and fill andthousands fill thousands of jobs, of Saudi jobs, Saudi students students have haveto be to we bell wellprepared prepared to handle to handle the thehuge huge task task at athand. hand. thousands of jobs, Saudi students have to be well prepared to handle the huge task at hand. UniversitiesUniversities are are the the ideal ideal places places toto developdevelop andand understandunderstand the the potential potential and and methods methods of of utilization utilization Universities are the ideal places to develop and understand the potential and methods of utilization ofof renewable renewable energy energy resources resources andand theirtheir applicationapplication on loads loads such such as as buildings, buildings, to to create create a anet-zero net-zero of renewable energy resources and their application on loads such as buildings, to create a net-zero energyenergy building building (NZEB), (NZEB), and and thenthen spreadspread thethe knowledge.knowledge. In In this this work, work, the the existing existing building building of ofthe the energy building (NZEB), and then spread the knowledge. In this work, the existing building of the CollegeCollege of of Engineering, Engineering, Majmaah Majmaah University,University, isis takentaken asas a case study. College of Engineering, Majmaah University, is taken as a case study. TheThe building building of of the the CollegeCollege ofof EngineeringEngineering has five five floors floors and and is is located located at at 25.890302 25.890302 N Nand and The building of the College of Engineering has five floors and is located at 25.890302 N and 45.3562945.35629 E E in in Majmaah Majmaah City City in in Riyadh Riyadh province, province, Kingdom Kingdom of of Saudi Saudi Arabia Arabia (KSA), (KSA), atat aa heightheight ofof 722722 m 45.35629 E in Majmaah City in Riyadh province, Kingdom of Saudi Arabia (KSA), at a height of 722 fromm from sea level. sea level. The coveredThe covered area ofarea this of building this building is 4859 is m48592, with m2, parkingwith parking space space at the at front the andfront back and of m from sea level. The covered area of this building is 4859 m2, with parking space at the front and back of the building. The satellite image and building model are shown in Figure 1. The CoE theback building. of the Thebuilding. satellite The image satellite and buildingimage and model building are shown model in Figureare shown1. The in CoE Figure building 1. The working CoE building working hours are from 8 a.m. to 8 p.m., where the electrical loads include heating and hoursbuilding are from working 8 a.m. hours to 8 p.m.,are from where 8 thea.m. electrical to 8 p.m. loads, where include the electrical heatingand loads cooling include systems, heating lighting, and cooling systems, lighting, office equipment, and water heating systems. The annual daily average officecooling equipment, systems, andlighting, water office heating equipment, systems. and The water annual heating daily systems. average The load annual is shown daily in Figureaverage2b, load is shown in Figure 2b, where a dip occurs at 12 p.m. for lunch break, and another at 2 p.m., whereload is a dipshown occurs in Figure at 12 p.m.2b, where for lunch a dipbreak, occursand at 12 another p.m. for at lunch 2 p.m., break, when and clerical another staff at leave2 p.m., the when clerical staff leave the building. The annual load in Figure 2a shows the rise of the load with building.when clerical The annual staff leave load the in Figure building.2a shows The annual the rise lo ofad thein Figure load with 2a shows the rise the in rise ambient of the temperature. load with the rise in ambient temperature. The summer holiday months are from mid-June to mid-August; this Thethe summer rise in ambient holiday temperature. months are from The summer mid-June holida to mid-August;y months are this from results mid-June in a curtailment to mid-August; of the this load. results in a curtailment of the load. The system has been designed based on summer peak load, as a Theresults system in a has curtailment been designed of the basedload. The on summer system ha peaks been load, designed as a high based load on is summer observed peak in summer, load, as anda high load is observed in summer, and the designed system will work well in the winter as well. The thehigh designed load is systemobserved will in worksummer, well and in thethe winterdesigned as well.system The will KSA work government well in the haswinter developed as well. aThe data KSA government has developed a data collection station to measure renewable resources collectionKSA government station to measurehas developed renewable a resourcesdata collection throughout station the to kingdom measure for renewable design and resources analysis of throughout the kingdom for design and analysis of future renewable energy system projects for the throughout the kingdom for design and analysis of future renewable energy system projects for the futuretargets renewable set out in energy Vision system 2030. The projects Majmaah for the statio targetsn for setrenewable out in Vision sources 2030. measurement The Majmaah is located station in for targets set out in Vision 2030. The Majmaah station for renewable sources measurement is located in renewableMajmaah sourcesUniversity measurement (MU). This ismeasurement located in Majmaah station is University a Tier II station (MU). with This uncertainty measurement in data station up is Majmaah University (MU). This measurement station is a Tier II station with uncertainty in data up a Tierto ±5%; II station the sensors with uncertaintyare cleaned twice in data a week. up to ±5%; the sensors are cleaned twice a week. to ±5%; the sensors are cleaned twice a week.
Figure 1. College of Engineering Majmaah (a) Model of Building; (b) Satellite Image. FigureFigure 1. 1.College Collegeof of EngineeringEngineering Majmaah ( aa)) Model Model of of Building; Building; (b (b) )Satellite Satellite Image. Image.
Figure 2. The load curve of College of Engineering in Majmaah (a) Monthly average load; (b) Daily Figure 2. The load curve of College of Engineering in Majmaah (a) Monthly average load; (b) Daily Figureaverage 2. Theload. load curve of College of Engineering in Majmaah (a) Monthly average load; (b) Daily average load. average load. 3.1. Renewable Resources 3.1. Renewable Resources Solar resources are available in abundance in Majmaah, with an average of global horizontal Solar resources are available in abundance in Majmaah, with an average of global horizontal irradiance (GHI) of 5.73 kWh/m2/day. Solar resources are high during summer from April to irradiance (GHI) of 5.73 kWh/m2/day. Solar resources are high during summer from April to September, with a highest average GHI of 8.07 kWh/m2/day in June. January, February, November, September, with a highest average GHI of 8.07 kWh/m2/day in June. January, February, November,
Energies 2018, 11, 1391 5 of 20
3.1. Renewable Resources Solar resources are available in abundance in Majmaah, with an average of global horizontal Energies 2018, 11, x FOR PEER REVIEW 5 of 20 irradiance (GHI) of 5.73 kWh/m2/day. Solar resources are high during summer from April to September, with a highest average GHI of 8.07 kWh/m2/day in June. January, February, November, and December receive lower irradiance; December receives the lowest irradiance, 3.31 kWh/m2/day, 2 andas Decembershown in Figure receive 3. lower The irradiance;solar output December is dependent receives on the lowestGHI and irradiance, temperature, 3.31 kWh/mas shown/day, in asEquation shown in(1). Figure The3 .PV The output solar outputincreases is dependentwith the increase on the GHIof GHI, and temperature,but decreases as at shown higher in Equationtemperatures. (1). The The PV output output Equation increases of withPV is the stated increase as [10]. of GHI, but decreases at higher temperatures. The output Equation of PV is stated as [10 ].̅ = 1+ − ̅ , (1) , ! The solar panels used in this work are monocrystallineGT 340 W Canadian Solar CS6X-340M-FG PPV = YPV fPV [1 + αP(Tc − Tc,STC)] (1) modules with an efficiency of 17.49%. These panelsGT,STC have a nominal operating cell temperature of 45 °C, and their temperature effect on power is −0.410 (%/°C).
FigureFigure 3.3. Temperature,Temperature, ClearnessClearness Index and Irradiance of of Majmaah Majmaah University. University.
Wind resources are also available in abundance at the study location, as shown in Figure 4. The The solar panels used in this work are monocrystalline 340 W Canadian Solar CS6X-340M-FG annual average wind speed is 5.11 m/s, as measured by an anemometer at a height of 50 m. The wind modules with an efficiency of 17.49%. These panels have a nominal operating cell temperature of speed does not have significant seasonal variations, as shown in Figure 4a. The highest monthly 45 ◦C, and their temperature effect on power is −0.410 (%/◦C). wind speed is observed in July, at 5.75 m/s, and lowest is in October, at 4.61 m/s. The wind resources Wind resources are also available in abundance at the study location, as shown in Figure4. The show that energy will be generated by wind throughout the year. The wind turbine selected for this annualproject average is the Enercon wind speed E-53 (800 is 5.11 kW). m/s, This as turbine measured has by a rotor an anemometer diameter of at52.9 a height m, with of a 50 hub m. height The wind of speed73 m. does The notcut-in have speed significant of this turbine seasonal is variations,2 m/s and a ascut-off shown speed in Figure of 25 4m/s.a. The The highest power monthlycoefficient wind of speedthis wind is observed turbine in shows July, atthat 5.75 it m/s,can convert and lowest good is portions in October, of wind at 4.61 energy m/s. Theinto windelectrical resources energy show at thatlower energy speeds, will as be shown generated in Figure by wind 5. The throughout average thedaily year. wind The speed wind increases turbine selected during forthe thisdaytime, project iswhich the Enercon can help E-53 in shaving (800 kW). the This peak turbine load, as has shown a rotor in diameter Figure 4b. of The 52.9 low m, withcut-in a speed hub height enables of this 73 m. Theturbine cut-in to speed produce of thiselectrical turbine energy is 2 m/s for 8524 and ah cut-offin a year speed at the of proposed 25 m/s. Thelocation, power which coefficient can be ofseen this windfrom turbine the duration shows curve that itand can histogram convert goodin Figure portions 4c,d respectively. of wind energy into electrical energy at lower speeds, as shown in Figure5. The average daily wind speed increases during the daytime, which can help in shaving the peak load, as shown in Figure4b. The low cut-in speed enables this turbine to produce electrical energy for 8524 h in a year at the proposed location, which can be seen from the duration curve and histogram in Figure4c,d respectively.
Energies 2018, 11, 1391 6 of 20 Energies 2018, 11, x FOR PEER REVIEW 6 of 20 Energies 2018, 11, x FOR PEER REVIEW 6 of 20
Figure 4. Wind Resources in Majmaah. (a) Monthly average wind speed; (b) Hourly average wind Figure 4.4. Wind ResourcesResources inin Majmaah.Majmaah. (a) MonthlyMonthly averageaverage windwind speed;speed; ((b)) HourlyHourly averageaverage windwind speed; (c) Wind speed duration curve; (d) Wind speed histogram. speed; ((cc)) WindWind speedspeed durationduration curve;curve; ((dd)) WindWind speedspeed histogram.histogram.
Figure 5. Characteristics of wind turbine Enercon E53 800 kW. Figure 5. Characteristics of wind turbine Enercon E53 800 kW. 3.2. PV Self-Shading AnalysisFigure 5. Characteristics of wind turbine Enercon E53 800 kW.
3.2. PV TheSelf-Shading parallel PV Analysis arrays on the rooftop are sketched in SAM 3D shading losses module. The tilt angle of PV modules is changed on a monthly routine for higher PV output generation. The tilt angle The parallel PV arrays on the rooftop are sketched in SAM 3D shading losses module. The tilt forThe each parallel month is PV shown arrays in on Table the 1. rooftop The data are reveals sketched that in for SAM May, 3D June, shading and July, losses PV module.panels have The to tilt angle of PV modules is changed on a monthly routine for higher PV output generation. The tilt angle anglebe placed of PV modulesat a zero tilt is changedangle, and on there a monthly is no chance routine of self-shading; for higher PV in output winter, generation. the tilt angle The will tilt cause angle for each month is shown in Table 1. The data reveals that for May, June, and July, PV panels have to forself-shading each month as is the shown angle in reaches Table1. a The maximum data reveals value thatof 53° for in May, December. June, and July, PV panels have to be be placed at a zero tilt angle, and there is no chance of self-shading; in winter, the tilt angle will cause placedThe at a sun zero daily tilt angle, path is and shifted there in isthe no winter chance season of self-shading; which originates in winter, in tilt the angle tilt variations. angle will The cause self-shading as the angle reaches a maximum value of 53° in December. self-shadingparallel PV as arrays the angle are placed reaches at a maximumvarious distances value ofand 53 ◦thein December.corresponding percentage of losses is recordedThe sun as daily the maximum path is shifted yearly in output the winter of PV seasonpanel occurring which originates when tilt in angle tilt angleequals variations. the latitude The parallelangle PVof thearrays site. are The placed Tabledistance 1.at The variousis Monthlymeas distancesured Tilt from angle and forthe Majmaahthehorizontal corresponding City projection [47]. percentage ( of ℎ losses × is recordedcos ( as the )maximum) of the top yearly of PV outputmodule ofof PVthe panefirst arrayl occurring to the whenbase of tilt the angle next equalsparallel the array, latitude as angleshownJan. of inthe Figure Feb. site. 6c.The Mar. The distance shading Apr. lossesis Maymeas areured calculated Jun. from Jul. atthe distances horizontal Aug. of 0 Sep. m,projection 0.25 Oct. m, 0.5 ( m, Nov. 0.75 m, ℎ Dec. 1 m, × cos1.25 ( 51 m, 1.5 43m,)) 1.75of the 29m, top 2 m, of 132.25 PV m,module 2.5 0 m, of 2.75 the 0 m, first 3 m, 0array 3.25 tom, 6 the3.5 basem, 233.75 of m,the 39and next 4 parallelm 48between array, 53 the as shownparallel in FigurePV arrays. 6c. TheThe shadingmonthly lossesaverage are shading calculated in the at critical distances months of 0 of m, January, 0.25 m, February,0.5 m, 0.75 March, m, 1 m, 1.25October, m, 1.5 November,m, 1.75 m, and2 m, December 2.25 m, 2.5 are m, shown 2.75 inm, Figure 3 m, 3.257. In m,the 3.5other m, six 3.75 months, m, and the 4 PVm betweentilt angles the The sun daily path is shifted in the winter season which originates in tilt angle variations. The parallelare near PV parallelarrays. Theto the monthly surface average of the roof,shading so no in self-shadingthe critical months is observed of January, in those February, months. March,The parallel PV arrays are placed at various distances and the corresponding percentage of losses is October,shading November, losses are negligible and December at a distance are shown between in Figure the parallel 7. In thePV arraysother sixof 2months, m or more, the asPV shown tilt angles in recorded as the maximum yearly output of PV panel occurring when tilt angle equals the latitude angle areFigure near 7.parallel The number to the of surface PV panels of the that roof, can beso placed no self-shading on the rooftop is observed depend on in itsthose area, months. as well asThe of the site. The distance is measured from the horizontal projection (Module length × cos (tilt angle)) shadingthe distance losses of are the negligible parallel arrays at a distance of PV panels. between As the paralleldistance PVbetween arrays the of PV2 m arrays or more, increases, as shown the in of the top of PV module of the first array to the base of the next parallel array, as shown in Figure6c. Figure 7. The number of PV panels that can be placed on the rooftop depend on its area, as well as the distance of the parallel arrays of PV panels. As the distance between the PV arrays increases, the
Energies 2018, 11, 1391 7 of 20
The shading losses are calculated at distances of 0 m, 0.25 m, 0.5 m, 0.75 m, 1 m, 1.25 m, 1.5 m, 1.75 m, 2 m, 2.25 m, 2.5 m, 2.75 m, 3 m, 3.25 m, 3.5 m, 3.75 m, and 4 m between the parallel PV arrays. The Energies 2018, 11, x FOR PEER REVIEW 7 of 20 monthlyEnergies 2018 average, 11, x FOR shading PEER REVIEW in the critical months of January, February, March, October, November,7 of and 20 December are shown in Figure7. In the other six months, the PV tilt angles are near parallel to the number of PV panels that can be placed on the rooftop decreases. To study the self-shading losses surfacenumber ofof the PV roof, panels so nothat self-shading can be placed is observed on the rooftop in those decreases. months. TheTo study shading the losses self-shading are negligible losses and compare the output energy generated at various distances, the number of PV modules is kept atand a distancecompare betweenthe output the energy parallel generated PV arrays at ofvarious 2 m or distances, more, as shownthe number in Figure of PV7. modules The number is kept of constant. The energy generated by PV panels is reduced by placing PV arrays close to each other as PVconstant. panels The that energy can be generated placed on by the PV rooftop panels depend is reduced on its by area, placing as well PVas arrays the distance close to ofeach the other parallel as the self-shading losses for the PV arrays increases. Figure 8 shows the relation between the number arraysthe self-shading of PV panels. losses As for the the distance PV arrays between increase the PVs. arraysFigure increases,8 shows the the relation number between of PV panels the number that can of PV panels installed on the rooftop and the distance between the PV arrays. beof PV placed panels on installed the rooftop on decreases.the rooftop To and study the thedistance self-shading between losses the PV and arrays. compare the output energy generated at various distances, the number of PV modules is kept constant. The energy generated by Table 1. The Monthly Tilt angle for Majmaah City [47]. PV panels is reduced by placingTable 1. The PV arraysMonthly close Tilt angle to each for Majmaah other as theCity self-shading [47]. losses for the PV arrays increases.Jan.Jan. Feb.Feb. Figure Mar.8Mar. shows Apr.Apr. the relationMayMay betweenJun.Jun. Jul. the numberAug.Aug. ofSeSe PVp.p. panelsOct.Oct. installedNov.Nov. Dec. onDec. the rooftop and the distance5151 43 between43 29 29 the PV 13 13 arrays. 0 0 0 0 6 23 23 3939 48 48 53 53
Figure 6. Study of self-shading by SAM (a) Sun path diagram over College of Engineering building FigureFigure 6. 6. StudyStudy of of self-shading self-shading by by SAM SAM ( a)) Sun path diagramdiagram overover CollegeCollege of of Engineering Engineering building building in SketchupPro; (b) Bird’s eye view of College of Engineering in SAM; (c) 3D scene of placing active inin SketchupPro; SketchupPro; (b (b) )Bird’s Bird’s eye eye view view of of College College of Engineering inin SAM;SAM; ((cc)) 3D3D scene scene of of placing placing active active surfaces (PV panels) in SAM, where the distance between two parallel arrays is shown. surfacessurfaces (PV (PV panels) panels) in in SAM, SAM, where where the the dist distanceance between twotwo parallelparallel arrays arrays is is shown. shown.
Figure 7. Self-shading losses for critical months of January, February, March, October, November, FigureFigureand December. 7. 7. Self-shadingSelf-shading losses losses for for critical critical months months of of January, January, February, March,March, October,October, November,November, andand December. December.
Energies 2018, 11, 1391 8 of 20 Energies 2018, 11, x FOR PEER REVIEW 8 of 20
Figure 8.8.Self-shading Self-shading losses losses for for PV arraysPV arrays and theand PV the output PV correspondingoutput corresponding to the parallel to the placement parallel distance.placement The distance. number The of number PV Panels of dependsPV Panels on depends the rooftop on the area. rooftop area.
3.3. Shading Effect on Cooling Load of Building Analysis 3.3. Shading Effect on Cooling Load of Building Analysis The CoE building has an air conditioner in each room to cool the building in the blazing The CoE building has an air conditioner in each room to cool the building in the blazing summer summer season. Each side of the building has small windows which remain mostly closed because season. Each side of the building has small windows which remain mostly closed because of dust of dust in the air and extreme weather throughout the year. The car park in front of the building has in the air and extreme weather throughout the year. The car park in front of the building has fabric fabric shading, while that in the back of the building is open; this space can therefore be used to shading, while that in the back of the building is open; this space can therefore be used to place place renewable energy systems. The PV arrays placed on the rooftop protect the building from the renewable energy systems. The PV arrays placed on the rooftop protect the building from the direct direct impact of solar radiation. The fully shaded building rooftop during the daytime receives heat impact of solar radiation. The fully shaded building rooftop during the daytime receives heat by by convection instead of radiation, as radiationis blocked by PV arrays. The building model is convection instead of radiation, as radiationis blocked by PV arrays. The building model is simulated simulated in EnergyPlus to assess the roof interior and exterior temperatures and cooling load in EnergyPlus to assess the roof interior and exterior temperatures and cooling load requirements. The requirements. The heat flux into the building from the roof by convection is given by [48]: heat flux q into the building from the roof by convection is given by [48]: =ℎ( − ) (2) q = h T − T (2) The heat flux into the building determinesc sur f theair cooling load required to maintain the temperature inside the building. The Building rooftop is heated in three ways: (a) the shortwave The heat flux into the building determines the cooling load required to maintain the temperature radiations that are directly horizontal and diffused horizontal radiations, (b) longwave radiations inside the building. The Building rooftop is heated in three ways: (a) the shortwave radiations that that are from the environment, and (c) heat exchange by convection with the outside air. This are directly horizontal and diffused horizontal radiations, (b) longwave radiations that are from the relation can be stated by Equation [49] environment, and (c) heat exchange by convection with the outside air. This relation can be stated by Equation [49] + + − =0 (3) qn + qn + qn − qn = 0 (3) Applying the Stefan-Boltzmannshortwave lawlongwave to each aircomponent convection producesheat f lux [49]:
Applying the Stefan-Boltzmann law to each component produces [49]: = − + − + − (4)
0 4 4 4 4 4 4 In theqheat case f lux of= PVεσ FarraysPV TPV covering− Tsur f acethe rooftop,+ εσFsky theTsky solar− T surradiation f ace + εσis Fabsoair Trbedair − byTsur PV f ace arrays and(4) increases in longwave radiations, but the rooftop is saved from the shortwave radiation of the sun. The EquationIn the case for of shaded PV arrays rooftop covering is [49]: the rooftop, the solar radiation is absorbed by PV arrays and increases in longwave radiations, but the rooftop is saved from the shortwave radiation of the sun. = − + − (5) The Equation for shaded rooftop is [49]: Further linearized radiative heat transfer coefficient is used to make the Equations more 0 4 4 4 4 compatible with the qbalancedheat f lux = heatεσF transfer;PV TPV − theTsur Eq f aceuation+ εσ forFair theT airrooftop− Tsur with f ace no shading becomes(5) [49]:
Further linearized radiative heat transfer coefficient is used to make the Equations more =ℎ , − +ℎ , − +ℎ , − (6) compatible with the balanced heat transfer; the Equation for the rooftop with no shading becomes [49]: where [49] 0 qheat f lux = hr,PV TPV − Tsur f ace + hr,sky T sky − Tsur f ace + hr,air Tair − Tsur f ace (6) − ℎ = (7) , − where [49] 4 4 εσ FPV T −− T ℎ = sur f ace PV (8) hr , ,PV = − (7) Tsur f ace − TPV − ℎ , = (9) −
Energies 2018, 11, 1391 9 of 20
4 4 εσFsky Tsur f ace − Tsky hr,sky = (8) Tsur f ace − Tsky
4 4 εσFair Tsur f ace − Tair hr,air = (9) Tsur f ace − Tair Further including the view factor to sky, the Equations become [49]:
4 4 εσFPV Tsur f ace − Tair hr,PV = (10) Tsur f ace − Tair
4 4 εσFskyβ Tsur f ace − Tsky hr,sky = (11) Tsur f ace − Tsky
4 4 εσFair(1 − β) Tsur f ace − Tair hr,air = (12) Tsur f ace − Tair where β is the tilt angle [49]: q β = 0.5(1 + cos ϕ) (13)
The final Equation for fully shaded rooftop is [49]:
0 qheat f lux = hr,PV TPV − Tsur f ace + hr,air Tair − Tsur f ace (14)
The weather file of the area was added to EnergyPlus, which has hourly data for GHI, DHI, DNI, air temperature, humidity, and wind speed. An annual energy simulation was run with the building parameters shown in Table2. The surface temperatures and annual building utility performance summary is recorded for analysis.
Table 2. Parameters for Building Energy simulation in EnergyPlus.
Parameter Values Number of people/100 m2 5.382 Lighting Power Density 10.7639 Electrical Equipment Power Density 10.7639 Thermostat (Cooling) 25.0 ◦C Thermostat (Heating) 20.0 ◦C Exterior Wall Outside Layer M01 100 mm brick Layer 2 M15 200 mm heavyweight concrete Layer 3 I02 50 mm insulation board Layer 4 F04 Wall air space resistance Layer 5 G01a 19 mm gypsum board Exterior Roof Outside Layer M11 100 mm lightweight concrete Layer 2 F05 Ceiling air space resistance Layer 3 F16 Acoustic tile Interior Ceiling Outside Layer M11 100 mm lightweight concrete Layer 2 F05 Ceiling air space resistance Layer 3 F16 Acoustic tile Energies 2018, 11, 1391 10 of 20
Table 2. Cont.
Parameter Values Exterior Window Outside Layer Clear 3 mm Layer 2 Air 13 mm Layer 3 Clear 3 mm Window Thickness {m} 0.003 Solar Transmittance at Normal Incidence 0.837 Visible Transmittance at Normal Incidence 0.898 Infrared Transmittance at Normal Incidence 0 Conductivity {W/m-K} 0.9 Office Lights Schedule Weekdays Weekends Holidays Until: 05:00 0.05 Until: 06:00 0.05 Until: 24:00 0.05 Until: 07:00 0.1 Until: 08:00 0.1 Until: 08:00 0.3 Until: 12:00 0.3 Until: 17:00 0.9 Until: 17:00 0.15 Until: 18:00 0.5 Until: 24:00 0.05 Until: 20:00 0.3 Until: 22:00 0.2 Until: 23:00 0.1 Until: 24:00 0.05 Office Equipment Schedule Weekdays Weekends Holidays Until: 08:00 0.40 Until: 06:00 0.30 Until: 24:00 0.30 Until: 12:00 0.90 Until: 08:00 0.4 Until: 13:00 0.80 Until: 12:00 0.5 Until: 17:00 0.90 Until: 17:00 0.35 Until: 18:00 0.50 Until: 24:00 0.30 Until: 24:00 0.40 Office Occupancy Schedule Weekdays Weekends Holidays Until: 06:00 0.0 Until: 06:00 0.0 Until: 06:00 0.0 Until: 07:00 0.1 Until: 08:00 0.1 Until: 18:00 0.0 Until: 08:00 0.2 Until: 12:00 0.3 Until: 24:00 0.0 Until: 12:00 0.95 Until: 17:00 0.1 Until: 13:00 0.5 Until: 19:00 0.0 Until: 17:00 0.95 Until: 24:00 0.0 Until: 18:00 0.3 Until: 20:00 0.1 Until: 24:00 0.05
The cooling load increases with the decrease in shading provided by PV panels. The FS rooftop is achieved by placing PV arrays at a distance of 0.75 m at a tilt angle of 53◦ in December, which will result in a fully covered rooftop in summer with the tilt angle of 0◦. Here, a 12.3% saving in the cooling load of the building is observed. As the distance between the PV arrays increases, the advantage in cooling load decreases. When the PV arrays are placed apart at a distance of 4 m, a 4.4% saving in cooling load is still observed, as shown in Figure9. The net energy for cooling is calculated by subtracting rooftop PV generation from the cooling load. The analysis of the net energy requirements for cooling by placing the PV arrays on rooftop shows that the closer the PV arrays are to one another, the more savings in cooling load are achieved. In total, 4088 PV modules can be placed on the FS rooftop, which has an area of 4891 m2. The higher number of PV panels of the FS rooftop also means Energies 2018, 11, x FOR PEER REVIEW 10 of 20
Until: 08:00 0.3 Until: 12:00 0.3 Until: 17:00 0.9 Until: 17:00 0.15 Until: 18:00 0.5 Until: 24:00 0.05 Until: 20:00 0.3 Until: 22:00 0.2 Until: 23:00 0.1 Until: 24:00 0.05 Office Equipment Schedule Weekdays Weekends Holidays Until: 08:00 0.40 Until: 06:00 0.30 Until: 24:00 0.30 Until: 12:00 0.90 Until: 08:00 0.4 Until: 13:00 0.80 Until: 12:00 0.5 Until: 17:00 0.90 Until: 17:00 0.35 Until: 18:00 0.50 Until: 24:00 0.30 Until: 24:00 0.40 Office Occupancy Schedule Weekdays Weekends Holidays Until: 06:00 0.0 Until: 06:00 0.0 Until: 06:00 0.0 Until: 07:00 0.1 Until: 08:00 0.1 Until: 18:00 0.0 Until: 08:00 0.2 Until: 12:00 0.3 Until: 24:00 0.0 Until: 12:00 0.95 Until: 17:00 0.1 Until: 13:00 0.5 Until: 19:00 0.0 Until: 17:00 0.95 Until: 24:00 0.0 Until: 18:00 0.3 Until: 20:00 0.1 Until: 24:00 0.05
The cooling load increases with the decrease in shading provided by PV panels. The FS rooftop is achieved by placing PV arrays at a distance of 0.75 m at a tilt angle of 53° in December, which will result in a fully covered rooftop in summer with the tilt angle of 0°. Here, a 12.3% saving in the cooling load of the building is observed. As the distance between the PV arrays increases, the advantage in cooling load decreases. When the PV arrays are placed apart at a distance of 4 m, a 4.4% saving in cooling load is still observed, as shown in Figure 9. The net energy for cooling is calculated by subtracting rooftop PV generation from the cooling load. The analysis of the net Energiesenergy2018 requirements, 11, 1391 for cooling by placing the PV arrays on rooftop shows that the closer the11 PV of 20 arrays are to one another, the more savings in cooling load are achieved. In total, 4088 PV modules can be placed on the FS rooftop, which has an area of 4891 m2. The higher number of PV panels of the thatFS rooftop higher electricalalso means energy that higher generation electrical is achieved. energy generation The energy is achieved. generated The by energy FS rooftop generated PV panels by metFS rooftop 96.5% of PV the panels cooling met load 96.5% of of the the complete cooling load building. of the Hence,complete the building. advantages Hence, of the FS rooftopadvantages with 4088of FS panels rooftop outweigh with 4088 the panels disadvantages outweigh ofthe self-shading disadvantages losses of self-shading of 1.039%. losses of 1.039%.
Figure 9. Comparison between the saving in cooling load of building with the self-shading of PV Figure 9. Comparison between the saving in cooling load of building with the self-shading of PV arrays arrays by placing them at a various distance on building rooftop, and the net energy required to by placing them at a various distance on building rooftop, and the net energy required to maintain the maintain the temperature in the building by using rooftop PV energy generation. temperature in the building by using rooftop PV energy generation.
4. Net-Zero Energy Analysis NZEB can be achieved by using renewable energy resources that can be placed on the rooftop and in the parking areas of the building. The university campus has plenty of space for placing solar or wind farms for energy generation. The following main cases are simulated in HomerPro for the minimum NPC.
Scenario 1 Off-grid with NS hybrid solar and wind energy system Scenario 2 NZEB with NS with PV only Scenario 3 NZEB with NS with wind only Scenario 4 NZEB with NS with hybrid solar and wind energy system Scenario 5 NZEB with FS rooftop with PV only Scenario 6 NZEB with FS rooftop with hybrid solar and wind energy system
In the first scenario, an off-grid system is simulated to compare the off-grid system with a grid-connected system. The next three scenarios (2, 3 and 4) present the PV only, wind only, and a hybrid PV wind system without shading on the rooftop where the annual load of the building is 5,377,307 kWh and cooling load consists of 3,416,861 kWh. The rooftop is fully exposed to solar radiation, so the building’s cooling load is the major portion of the annual load. To understand the real advantages of PV arrays on a rooftop in hot climate, scenarios 5 and 6 are simulated, where the fully shaded rooftop require a lower cooling load, i.e., 2,995,738 kWh, so the annual load for a building with fully shaded rooftop is 4,957,456 kWh. The parameters for solar and wind energy system are shown in Table3. The EPC, PDC, and IDC form the initial cost of projects, while O&M and insurance form the project operating costs. In this work, land cost is eliminated, as the University campus has enough space to install PVs or wind turbines. The cheaper costs of renewable resource energy systems [12,50] and increasing costs of electricity in KSA are making renewable energy systems more feasible. Government buildings such as the CoE has a flat tariff of 0.085 US$, since 1 January 2018. The utility-scale solar projects have a lower cost of energy than the standard 0.085 US$, due to the decline in prices of PV on the international market. Recently, KSA awarded AWCA energy a 300 MW solar project with an LCOE of 0.02342 US$/kWh [13]. The project in this work is much smaller than the AWCA energy awarded project; it is in an urban environment, in an area which is not in the top ten locations for solar production in KSA [10]. The cost of this project is higher than that of the utility level project of 300 MW. Energies 2018, 11, 1391 12 of 20
Table 3. Cost parameters of Solar and Wind [51].
Description Cost EPC Cost (US$/MW) 1,021,431 PDC (US$/MW) 36,658 IDC (US$/MW) 10,714 Solar Net Initial Cost (US$/kW) 1068.80 O&M US$/kW/year 7.82286 Insurance US$/kW/year 3.37714 EPC Cost + PDC + IDC (MUS$/MW) 1.93 Wind O&M (USC/kWh) 1.1986 Insurance (USC/kWh) 0.2523
The schematic diagram of a hybrid system in HomerPro is shown in Figure 10. The results of simulations based on NPC, initial cost, and LCOE, grid sales, grid purchases, and renewable penetration are tabulated in Table4. The scenario 5, PV only FS rooftop system, has the lowest NPC, while scenario 6, a hybrid FS system with PV and a wind turbine, has the second-lowest NPC. The EnergiesLCOE is2018 also, 11, lowestx FOR PEER for scenarioREVIEW 5, the FS rooftop PV only system. 12 of 20
FigureFigure 10. 10. SystemSystem schematic schematic of of Hybrid Hybrid Sola Solarr Wind Wind Energy System in HomerPro.
The off-grid system shows a huge capital investment of 17.5 MUS$ and NPC of 26.1 MUS$, and The off-grid system shows a huge capital investment of 17.5 MUS$ and NPC of 26.1 MUS$, and the LCOE of electricity is 0.375 US$/kWh. This off-grid hybrid is five times more expensive than an the LCOE of electricity is 0.375 US$/kWh. This off-grid hybrid is five times more expensive than an FS FS hybrid system. The initial cost of the off-grid system consists of two wind turbines, of 1.6 MW hybrid system. The initial cost of the off-grid system consists of two wind turbines, of 1.6 MW installed installed capacity, and a cost of 7.275 MW of installed PV modules. The cost of batteries used for the capacity, and a cost of 7.275 MW of installed PV modules. The cost of batteries used for the storage of storage of electricity for the night is an astonishing 12.2 MUS$. Analysis shows that the electricity for the night is an astonishing 12.2 MUS$. Analysis shows that the grid-connected systems grid-connected systems are much cheaper and more dependable. are much cheaper and more dependable. The next three scenarios (2, 3, and 4) are of NS with PV only, wind only, and a hybrid case with The next three scenarios (2, 3, and 4) are of NS with PV only, wind only, and a hybrid case with PV PV and wind energy systems. The scenario 2, the solar only case at NS, has the lowest NPC of 4.77 and wind energy systems. The scenario 2, the solar only case at NS, has the lowest NPC of 4.77 MUS$, MUS$, while hybrid and wind only have 5.37 MUS$ and 7.18 MUS$ respectively. The PV appears to while hybrid and wind only have 5.37 MUS$ and 7.18 MUS$ respectively. The PV appears to be the be the most promising renewable resource in Majmaah. The price of wind is a bit more for such a most promising renewable resource in Majmaah. The price of wind is a bit more for such a small-scale small-scale project. The LCOE is 0.0472 US$/kWh, 0.0550 US$/kWh, and 0.0658 US$/kWh for PV project. The LCOE is 0.0472 US$/kWh, 0.0550 US$/kWh, and 0.0658 US$/kWh for PV only, and only, and the hybrid and wind only system, respectively. The advantage of adding wind resources the hybrid and wind only system, respectively. The advantage of adding wind resources into the into the energy mix leads to more renewable energy penetration, as a wind turbine produces energy mix leads to more renewable energy penetration, as a wind turbine produces electrical energy electrical energy throughout a day, while PV can only produce during sunlight hours. throughout a day, while PV can only produce during sunlight hours. Finally, the last two scenarios are to show the effect of PV shading on the building in a hot climate, where the annual load has decreased by installing PV on the rooftop from 5,377,307 kWh to 4,957,456 kWh, according to the EnergyPlus analysis shown in Figure 9. In scenario 5, the PV only case with FS, the NPC of the system is 4.41 MUS$ and the initial cost of 3.64 MUS$, while in scenario 6, a hybrid case with FS, the net present cost increases to 5.00 MUS$, and the initial cost is 4.14 MUS$. The LCOE by the scenario 5 of PV only is 0.0472 US$/kWh, while that of scenario 6 is 0.0556 US$/kWh. The analysis shows that the most feasible case is scenario 5, with an FS rooftop with PV only energy system. Furthermore, system energy analysis and economic analysis is performed for the most feasible system of scenario 5.
Energies 2018, 11, 1391 13 of 20
Table 4. Comparison of six scenarios of renewable energy systems.
Installed Installed System Grid Renewable NPC Capital Cost LCOE Batteries Grid Sales Scenario PV Wind Converter Purchase Penetration MUS$ MUS$ (US$/kWh) MW MW MW Qty GWh GWh % 1. Off-grid Hybrid 26.1 17.5 0.3750 7.382 1.6 3.250 18,384 - - 100 2. PV only (NS) 4.77 3.95 0.0472 3.055 - 2.270 - 2.54 2.44 68.8 3. Wind only (NS) 7.18 6.18 0.0658 - 3.2 - - 3.06 2.72 67.8 4. Hybrid (NS) 5.37 4.44 0.0550 2.238 0.8 1.670 - 2.17 2.17 71.2 5. PV (FS) 4.41 3.64 0.0472 2.815 - 2.097 - 2.25 2.25 68.8 6. Hybrid (FS) 5.00 4.14 0.0556 2.005 0.8 1.495 - 1.99 1.99 71.4 Energies 2018, 11, 1391 14 of 20
Finally, the last two scenarios are to show the effect of PV shading on the building in a hot climate, where the annual load has decreased by installing PV on the rooftop from 5,377,307 kWh to 4,957,456 kWh, according to the EnergyPlus analysis shown in Figure9. In scenario 5, the PV only case with FS, the NPC of the system is 4.41 MUS$ and the initial cost of 3.64 MUS$, while in scenario 6, a hybrid case with FS, the net present cost increases to 5.00 MUS$, and the initial cost is 4.14 MUS$. The LCOE by the scenario 5 of PV only is 0.0472 US$/kWh, while that of scenario 6 is 0.0556 US$/kWh. The analysis shows that the most feasible case is scenario 5, with an FS rooftop with PV only energy system. Furthermore, system energy analysis and economic analysis is performed for the most feasible systemEnergies 2018 of scenario, 11, x FOR 5. PEER REVIEW 14 of 20
4.1.4.1. EnergyEnergy AnalysisAnalysis TheThe monthly average average and and hourly hourly average average of energy of energy analysis analysis of scenario of scenario 5 is shown 5 is in shownFigures in11 Figuresand 12 11respectively. and 12 respectively. In Figure 11, In Figurethe energy 11, the produced energy producedby PV is byin accordance PV is in accordance with the withsolar theirradiance solar irradiance and temperature. and temperature. June is the June best is the mont besth monthfor PV forenergy PV energygeneration, generation, with high with GHI, high while GHI, whileDecember December has the has minimum the minimum energy energy output, output, with with low low GHI. GHI. The The months months of of July July and August havehave beenbeen affected affected by by the the high high temperature. temperature. The The load, load sales,, sales, and purchasesand purchases from thefrom grid the show grid that show during that summerduring summer months, months, more energy more is energy bought is from bought the from grid, the while grid, in thewhile winter in the months, winter the months, grid sales the grid are higher.sales are The higher. hourly The average hourly PV average output inPV Figure output 12 inshows Figure that 12 energy shows generation that energy follows generation the GHI. follows The loadthe GHI. of the The building load of is the satisfied building by is the satisfied PV generation by the PV during generation the day, during and extra the day, energy and is extra sold energy to the grid,is sold while to the energy grid,is while purchased energy during is purchased the night. duri Theng datamapthe night. in The Figure datamap 13 shows in Figure the PV 13 generation, shows the girdPV generation, purchase, grid gird sales, purchase, and renewable grid sales, energy and penetrationrenewable energy percentage penetration for the completepercentage year. for The the negativecomplete effect year. onThe the negative output effect of PV on in thethe summeroutput of months PV in the at highsummer temperatures months at canhigh be temperatures seen in this Figure.can be seen There in isthis huge Figure. grid There purchase is huge after grid sunset, purcha as buildingse after sunset, office as hours building are up office to 8 hours p.m., whereasare up to most8 p.m., grid whereas sales are most during grid the sales weekend are during and winter the weekend months, and when winter the load months, of the when building the isload less of than the PVbuilding generation. is less The than national PV generation. energy peak The ofnational KSA occurs energy around peak of 2 p.m.KSA [occurs52]. The around digital 2 metersp.m. [52]. record The peakdigital hours meters from record 12 p.m. peak to hours 5 p.m. fr [om53,54 12]. p.m. The to energy 5 p.m. generated [53,54]. The during energy the generated day is at theduring time the of theday firstis at national the time energy of the first peak, national so this systemenergy ispeak, shaving so this off system the load is and shaving reducing off the the load stress and of reducing the national the grid,stress and of the also national supporting grid, the and national also supporting grid by selling the national extra energy grid toby it.selling During extra the energy off-peak to hours, it. During the systemthe off-peak is purchasing hours, the from system the grid, is purchasing which will from enhance the grid, the loadwhich factor. will enhance The rooftop the ofload the factor. building, The 2 withrooftop an area of the of 4859building, m , is wi capableth an ofarea housing of 4859 4086 m PV2, is panels, capable with of anhousing installed 4086 capacity PV panels, 1390 kW with from an theinstalled required capacity 8280 panels, 1390 kW to meetfrom the the annual required load 8280 with panels, an installed to meet capacity the annual of 2815 load kW. with The an remaining installed 4185capacity PV panels of 2815 of kW. installed The remaining capacity 1425 4185 kW PV will panels be installedof installed in thecapacity car parking 1425 kW area will or inbe openinstalled space in onthe the car university parking area campus. or in open space on the university campus.
Figure 11. Hourly average PV energy generation, electrical load, grid sales, grid purchases, GHI, and Figure 11. Hourly average PV energy generation, electrical load, grid sales, grid purchases, GHI, and temperature in a year. temperature in a year.
Figure 12. Hourly based yearly average PV energy generation, electrical load, grid sales, grid purchases, and GHI.
Energies 2018, 11, x FOR PEER REVIEW 14 of 20
4.1. Energy Analysis The monthly average and hourly average of energy analysis of scenario 5 is shown in Figures 11 and 12 respectively. In Figure 11, the energy produced by PV is in accordance with the solar irradiance and temperature. June is the best month for PV energy generation, with high GHI, while December has the minimum energy output, with low GHI. The months of July and August have been affected by the high temperature. The load, sales, and purchases from the grid show that during summer months, more energy is bought from the grid, while in the winter months, the grid sales are higher. The hourly average PV output in Figure 12 shows that energy generation follows the GHI. The load of the building is satisfied by the PV generation during the day, and extra energy is sold to the grid, while energy is purchased during the night. The datamap in Figure 13 shows the PV generation, gird purchase, grid sales, and renewable energy penetration percentage for the complete year. The negative effect on the output of PV in the summer months at high temperatures can be seen in this Figure. There is huge grid purchase after sunset, as building office hours are up to 8 p.m., whereas most grid sales are during the weekend and winter months, when the load of the building is less than PV generation. The national energy peak of KSA occurs around 2 p.m. [52]. The digital meters record peak hours from 12 p.m. to 5 p.m. [53,54]. The energy generated during the day is at the time of the first national energy peak, so this system is shaving off the load and reducing the stress of the national grid, and also supporting the national grid by selling extra energy to it. During the off-peak hours, the system is purchasing from the grid, which will enhance the load factor. The rooftop of the building, with an area of 4859 m2, is capable of housing 4086 PV panels, with an installed capacity 1390 kW from the required 8280 panels, to meet the annual load with an installed capacity of 2815 kW. The remaining 4185 PV panels of installed capacity 1425 kW will be installed in the car parking area or in open space on the university campus.
EnergiesFigure2018, 1111., 1391 Hourly average PV energy generation, electrical load, grid sales, grid purchases, GHI, and15 of 20 temperature in a year.
Figure 12.12.Hourly Hourly based based yearly yearly average average PVenergy PV energy generation, generation, electrical electrical load, grid load, sales, grid grid sales, purchases, grid Energiesandpurchases, 2018 GHI., 11, x and FOR GHI. PEER REVIEW 15 of 20
Figure 13.13. The datamap of the system (a) SolarSolar Energy generationgeneration in kW (b) EnergyEnergy PurchasedPurchased fromfrom thethe GridGrid inin kW;kW; ((cc)) EnergyEnergy SoldSold toto thethe GridGrid inin kW;kW; ((dd)) PercentagePercentage ofof RenewableRenewable EnergyEnergy Penetration.Penetration.
4.2. Economics Analysis This section presents the detail economic analysis of scenario 5, FS with PV only system, due to itsits lowestlowest NPCNPC shown shown in in Table Table4. The 4. The economics economics of the of system the system is presented is presented in terms in NPC terms with NPC respect with torespect the components to the components cost and cost cost and types cost in Figuretypes in14 .Figu There capital 14. The cost capital of the cost system of the consists system of consists the cost of the cost of PVs and the converters. The operational and maintenance cost includes the routine PVs and the converters. The operational and maintenance cost includes the routine weekly cleaning of weekly cleaning of PV panels and payments to the grid. Dust in the environment can reduce the PV panels and payments to the grid. Dust in the environment can reduce the system output energy. system output energy. Dust storms usually occur in Majmaah in the months of March and April, so Dust storms usually occur in Majmaah in the months of March and April, so PV modules require PV modules require frequent cleaning after each such event. The lifetime of converters is 15 years, frequent cleaning after each such event. The lifetime of converters is 15 years, after which they must after which they must be replaced. The yearly cash flow diagrams of the system are shown in be replaced. The yearly cash flow diagrams of the system are shown in Figures 15 and 16, by cost type Figures 15 and 16, by cost type and components, respectively. The cash flow diagrams show that the major expenditure of the project is the capital cost. The annual worth of the system is 27,406 US$, with a ROE of 19.7%. The simple payback time of the project is 3.79 years, and discounted payback time 4.42 years.
Figure 14. Net present cost (NPC) of scenario 5 with respect to components and cost type.
Energies 2018, 11, x FOR PEER REVIEW 15 of 20
Figure 13. The datamap of the system (a) Solar Energy generation in kW (b) Energy Purchased from the Grid in kW; (c) Energy Sold to the Grid in kW; (d) Percentage of Renewable Energy Penetration.
4.2. Economics Analysis This section presents the detail economic analysis of scenario 5, FS with PV only system, due to its lowest NPC shown in Table 4. The economics of the system is presented in terms NPC with respect to the components cost and cost types in Figure 14. The capital cost of the system consists of the cost of PVs and the converters. The operational and maintenance cost includes the routine weekly cleaning of PV panels and payments to the grid. Dust in the environment can reduce the system output energy. Dust storms usually occur in Majmaah in the months of March and April, so
PVEnergies modules2018, 11 require, 1391 frequent cleaning after each such event. The lifetime of converters is 15 years,16 of 20 after which they must be replaced. The yearly cash flow diagrams of the system are shown in Figures 15 and 16, by cost type and components, respectively. The cash flow diagrams show that the majorand components, expenditure respectively. of the project The is cashthe capital flow diagrams cost. The show annual that worth the major of the expenditure system is of27,406 the project US$, withis the a capitalROE of cost. 19.7%. The The annual simple worth payback of the time system of the is project 27,406 US$,is 3.79 with years, a ROE and ofdiscounted 19.7%. The payback simple timepayback 4.42 timeyears. of the project is 3.79 years, and discounted payback time 4.42 years.
Energies 2018FigureFigure, 11, x FOR14. 14. Net PEERNet present present REVIEW cost cost (NPC) (NPC) of of scenario scenario 5 5 with with respect respect to to components components and and cost cost type. type. 16 of 20 Energies 2018, 11, x FOR PEER REVIEW 16 of 20
Figure 15. Yearly cash flow diagram of scenario 5 by cost type. Figure 15. Yearly cash flowflow diagram ofof scenarioscenario 55 byby costcost type.type.
Figure 16. Yearly cash flow diagram of scenario 5 by components. Figure 16. Yearly cash flowflow diagram of scenarioscenario 55 byby components.components. KSA is planning huge projects to harness solar energy to shift the nation dependence on fossil KSA is planning huge projects to harness solar energy to shift the nation dependence on fossil fuel toKSA renewable is planning energy. huge The projects plan toof harness200 GW solarsolar energyenergy tosystems shift the in nationKSA, accompanied dependence onby fossilhigh fuel to renewable energy. The plan of 200 GW solar energy systems in KSA, accompanied by high fuelvoltage to renewableDC transmission, energy. can The power plan of future 200 GW energy solar needs energy of systems European in KSA,countries. accompanied The Middle by highEast voltage DC transmission, can power future energy needs of European countries. The Middle East voltagecan transform DC transmission, energy production can power from future fossil energyfuel to renewable needs of European energy. In countries. this work, The the Middle advantages East can transform energy production from fossil fuel to renewable energy. In this work, the advantages canof on-site transform solar energyenergy productionare shown where from fossil not only fuel solar to renewable power has energy. shaved In off this the work, building the advantages load from of on-site solar energy are shown where not only solar power has shaved off the building load from ofnational on-site grid solar and energy improved are shown the national where not grid only load solar factor power without has shavedany transmission off the building losses, load butfrom also national grid and improved the national grid load factor without any transmission losses, but also nationalreduced the grid building and improved cooling theload national by providing grid load shade factor to the without rooftop any of transmissionthe building. losses, but also reduced the building cooling load by providing shade to the rooftop of the building. reduced the building cooling load by providing shade to the rooftop of the building. 5. Conclusions 5. Conclusions A net-zero energy office building design for the building of College of Engineering, Majmaah A net-zero energy office building design for the building of College of Engineering, Majmaah UniversityA net-zero is analyzed energy for office the buildingavailable designonsite rene for thewable building resources. of College PV and of wind Engineering, turbines in Majmaah various University is analyzed for the available onsite renewable resources. PV and wind turbines in various Universityconfigurations is analyzed are studied for the to availableform a net-zero onsite renewable energy building. resources. A PVPV andsystem wind is turbinesfound to in be various most configurations are studied to form a net-zero energy building. A PV system is found to be most configurationsfeasible for this arelocation, studied on tothe form basis a of net-zero net pres energyent value. building. The rooftop A PV and system parking is found area tois used be most for feasible for this location, on the basis of net present value. The rooftop and parking area is used for feasiblethe placement for this of location, PV panels. on the The basis self-shading of net present in value.PV system The rooftop is analyzed and parking by varying area is the used distance for the the placement of PV panels. The self-shading in PV system is analyzed by varying the distance between the parallel PV arrays. The self-shading losses of 1.039% have been observed at a distance of between the parallel PV arrays. The self-shading losses of 1.039% have been observed at a distance of 0.75 m, fully shaded rooftop, as the mean annual PV energy generation decreases from 594.39 0.75 m, fully shaded rooftop, as the mean annual PV energy generation decreases from 594.39 kWh/m2 to 588.21 kWh/m2. The effect on cooling load of building by rooftop PV panels as shading kWh/m2 to 588.21 kWh/m2. The effect on cooling load of building by rooftop PV panels as shading devices offers a 12.3% saving in cooling load for a fully shaded rooftop, as annual cooling load devices offers a 12.3% saving in cooling load for a fully shaded rooftop, as annual cooling load decreased from 3.416 GWh to 2.996 GWh. The 2.815 MW installed capacity of PV generates 5.3 GWh, decreased from 3.416 GWh to 2.996 GWh. The 2.815 MW installed capacity of PV generates 5.3 GWh, to satisfy a load of 4.96 GWh annually, to form a net-zero energy system where the grid sales and to satisfy a load of 4.96 GWh annually, to form a net-zero energy system where the grid sales and purchase are equal to 2.25 GWh. The hours of operation for PV are 4,379, with a capacity factor of purchase are equal to 2.25 GWh. The hours of operation for PV are 4,379, with a capacity factor of 21.5%. The NPC of project has been decreased from 4.77 million US$ to 4.41 million US$ by simply 21.5%. The NPC of project has been decreased from 4.77 million US$ to 4.41 million US$ by simply covering the rooftop completely by PV panels. The annual worth of the system is 27,406 US$, with a covering the rooftop completely by PV panels. The annual worth of the system is 27,406 US$, with a return on investment of 19.7%. The simple payback time of the project is 3.79 years, and discounted return on investment of 19.7%. The simple payback time of the project is 3.79 years, and discounted payback time 4.42 years. The fully shaded hybrid PV Wind case for NZEB is the second best payback time 4.42 years. The fully shaded hybrid PV Wind case for NZEB is the second best scenario, with an NPC of 5 MUS$, and capital costs of 4.14 MUS$. This case has shown more scenario, with an NPC of 5 MUS$, and capital costs of 4.14 MUS$. This case has shown more renewable penetration than a PV only case of 71.4%. The on-site solar energy generation shows not renewable penetration than a PV only case of 71.4%. The on-site solar energy generation shows not only that solar power has shaved off the building load from national grid and improved the national only that solar power has shaved off the building load from national grid and improved the national grid load factor without any transmission losses, but also that it has reduced the building load by grid load factor without any transmission losses, but also that it has reduced the building load by providing shade to the rooftop. providing shade to the rooftop.
Energies 2018, 11, 1391 17 of 20 placement of PV panels. The self-shading in PV system is analyzed by varying the distance between the parallel PV arrays. The self-shading losses of 1.039% have been observed at a distance of 0.75 m, fully shaded rooftop, as the mean annual PV energy generation decreases from 594.39 kWh/m2 to 588.21 kWh/m2. The effect on cooling load of building by rooftop PV panels as shading devices offers a 12.3% saving in cooling load for a fully shaded rooftop, as annual cooling load decreased from 3.416 GWh to 2.996 GWh. The 2.815 MW installed capacity of PV generates 5.3 GWh, to satisfy a load of 4.96 GWh annually, to form a net-zero energy system where the grid sales and purchase are equal to 2.25 GWh. The hours of operation for PV are 4379, with a capacity factor of 21.5%. The NPC of project has been decreased from 4.77 million US$ to 4.41 million US$ by simply covering the rooftop completely by PV panels. The annual worth of the system is 27,406 US$, with a return on investment of 19.7%. The simple payback time of the project is 3.79 years, and discounted payback time 4.42 years. The fully shaded hybrid PV Wind case for NZEB is the second best scenario, with an NPC of 5 MUS$, and capital costs of 4.14 MUS$. This case has shown more renewable penetration than a PV only case of 71.4%. The on-site solar energy generation shows not only that solar power has shaved off the building load from national grid and improved the national grid load factor without any transmission losses, but also that it has reduced the building load by providing shade to the rooftop.
Author Contributions: M.Z. conceived the idea, A.A.-A. and A.B.A. performed the simulations. A.G.A.-K. analyzed the data and reviewed the manuscript. M.Z. and A.B.A. wrote the paper. Acknowledgments: This research was supported by the Deanship of Scientific Research, Majmaah University, Majmaah, 11952, Kingdom of Saudi Arabia (Contract No. 38/109). Conflicts of Interest: The authors declare no conflict of interest.
Nomenclature
NZEB Net Zero Energy Building PV Photovoltaic NPC Net Present Cost FS Fully Shaded NS No Shading SAM System Advisor Model hc The convective heat transfer coefficient Tsur f Surface temperature of rooftop Tair Outside air temperature of rooftop PPV Is the output of the PV array The rated capacity of the PV array, meaning its power output under standard test Y PV conditions [kW] fPV The PV derating factor [%] 2 GT Solar radiation incident on the PV array in the current time step [kw/m ] 2 GT,STC Incident radiation at standard test conditions [1 kw/m ] ◦ αP Temperature coefficient of power [%/ C] ◦ Tc PV cell temperature in the current time step [ C] ◦ Tc,STC PV cell temperature under standard test conditions [25 C] ε Long wave emittance σ Stefan-Boltzmann constant FPV View factor of the rooftop surface to PV surface [Range: 0–1] Fsky View factor of the rooftop surface to sky [Range: 0–1] Fair View factor of the rooftop surface to air [Range: 0–1] TPV Temperature of PV Tair Temperature of air Tsky Temperature of sky Tsur f ace Temperature of the rooftop EPC Engineering procurement and construction Energies 2018, 11, 1391 18 of 20
O&M Operation and maintenance IDO Cost, insurance during operation IDC Insurance during construction PDC Project development cost ROE Return on equity CoE College of Engineering LCOE Levelized cost of energy (US$/kwh)
References
1. Kreft, S.; Eckstein, D.; Melchior, I. Global Climate Risk Index 2017 Who Suffers Most from Extreme Weather Events? Weather-Related Loss Events in 2015 and 1996 to 2015; Germanwatch e.V.: Bonn, Germany, 2017. 2. Lesk, C.; Rowhani, P.; Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 2016, 529, 84–87. [CrossRef][PubMed] 3. Naumann, G.; Alfieri, L.; Wyser, K.; Mentaschi, L.; Betts, R.A.; Carrao, H.; Spinoni, J.; Vogt, J.; Feyen, L. Global Changes in Drought Conditions under Different Levels of Warming. Geophys. Res. Lett. 2018.[CrossRef] 4. Spliethoff, H. Effect of Slag, Ash and Flue Gas on Furnace Walls and Convective Heat Transfer Surfaces (Operational Problems); Academic Press: Cambridge, MA, USA, 2010; ISBN 9780874216561. 5. Oreskes, N. The Scientific Consensus on Climate Change: How Do We Know We’re Not Wrong? In Climate Modelling; Springer International Publishing: Cham, Switzerland, 2018; Volume 306, pp. 31–64. 6. United Nations Paris Agreement, FCCC/CP/2015/L.9. Available online: https://unfccc.int/resource/docs/ 2015/cop21/eng/l09r01.pdf (accessed on 12 January 2018). 7. Directive No. 2009/28/EC of the European Parliament and of the Council of 23 April 2009, on the Promotion of the Use of Energy from Renewable Sources and Amending and Subsequently Repealing Directives No. 2001/77/EC and No. 2003/30/EC. © European Union, 1998–2015. Available online: http://www.wipo.int/ wipolex/en/details.jsp?id=15751 (accessed on 12 January 2018). 8. Yamada, M. Vision 2030 and the Birth of Saudi Solar Energy; Middle East Institute: Washinton, DC, USA, 2016. 9. Government of Saudi Arabia a Renewable Energy Market, Saudi Arabia Vision 2030. Available online: http://vision2030.gov.sa/en/node/87 (accessed on 12 January 2018). 10. Awan, A.B.; Zubair, M.; Praveen, R.P.; Abokhalil, A.G. Solar Energy Resource Analysis and Evaluation of Photovoltaic System Performance in Various Regions of Saudi Arabia. Sustainability 2018, 10, 1129. [CrossRef] 11. Khan, H.; Asif, M. Impact of Green Roof and Orientation on the Energy Performance of Buildings: A Case Study from Saudi Arabia. Sustainability 2017, 9, 640. [CrossRef] 12. BNE Finance. Global Trends in Renewable Energy Investment; Frankfurt School: Frankfurt am Main, Germany, 2018. 13. Power, A. ACWA Power Wins the First Ever Utility Scale Renewable Energy Project in Saudi Arabia. Available online: http://www.acwapower.com/en/news/press-releases/acwa-power-wins-the-first-ever- utility-scale-renewable-energy-project-in-saudi-arabia/ (accessed on 9 April 2018). 14. Bloomberg Saudis, SoftBank Plan World’s Largest Solar Project. Available online: https://www.bloomberg. com/news/articles/2018-03-28/saudi-arabia-softbank-ink-deal-on-200-billion-solar-project (accessed on 9 April 2018). 15. He, Z.; Xiao, B.; Liu, F.; Wu, H.; Yang, Y.; Xiao, S.; Wang, C.; Russell, T.P.; Cao, Y. Single-junction polymer solar cells with high efficiency and photovoltage. Nat. Photonics 2015, 9, 174–179. [CrossRef] 16. Li, W.; Hendriks, K.H.; Furlan, A.; Wienk, M.M.; Janssen, R.A.J. High quantum efficiencies in polymer solar cells at energy losses below 0.6 eV. J. Am. Chem. Soc. 2015, 137, 2231–2234. [CrossRef][PubMed] 17. Green, M.A. Thin-film solar cells: Review of materials, technologies and commercial status. J. Mater. Sci. 2007.[CrossRef] 18. Zubair, M.; Mustafa, M.; Lee, K.; Yoon, C.; Doh, Y.H.; Choi, K.H. Fabrication of CdSe/ZnS quantum dots thin film by electrohydrodynamics atomization technique for solution based flexible hybrid OLED application. Chem. Eng. J. 2014, 253, 325–331. [CrossRef] Energies 2018, 11, 1391 19 of 20
19. Yoshikawa, K.; Kawasaki, H.; Yoshida, W.; Irie, T.; Konishi, K.; Nakano, K.; Uto, T.; Adachi, D.; Kanematsu, M.; Uzu, H.; et al. Silicon heterojunction solar cell with interdigitated back contacts for a photoconversion efficiency over 26%. Nat. Energy 2017, 2, 17032. [CrossRef] 20. Cariou, R.; Benick, J.; Feldmann, F.; Höhn, O.; Hauser, H.; Beutel, P.; Razek, N.; Wimplinger, M.; Bläsi, B.; Lackner, D.; et al. III–V-on-silicon solar cells reaching 33% photoconversion efficiency in two-terminal configuration. Nat. Energy 2018, 3, 326–333. [CrossRef] 21. Kato, T.; Handa, A.; Yagioka, T.; Matsuura, T.; Yamamoto, K.; Higashi, S.; Wu, J.L.; Tai, K.F.; Hiroi, H.; Yoshiyama, T.; et al. Enhanced Efficiency of Cd-Free Cu(In,Ga)(Se,S)2Minimodule Via (Zn,Mg)O Second Buffer Layer and Alkali Metal Post-Treatment. IEEE J. Photovolta. 2017, 7, 1773–1780. [CrossRef] 22. NREL PV Efficiency Chart. Available online: https://www.nrel.gov/pv/assets/images/efficiency-chart.png (accessed on 10 April 2018). 23. Green, M.A.; Hishikawa, Y.; Dunlop, E.D.; Levi, D.H.; Hohl-Ebinger, J.; Ho-Baillie, A.W.Y. Solar cell efficiency tables (version 51). Prog. Photovolt. Res. Appl. 2018, 26, 3–12. [CrossRef] 24. Kurtz, S.; Repins, I.; Metzger, W.K.; Verlinden, P.J.; Huang, S.; Bowden, S.; Tappan, I.; Emery, K.; Kazmerski, L.L.; Levi, D. Historical Analysis of Champion Photovoltaic Module Efficiencies. IEEE J. Photovolt. 2018, 8, 363–372. [CrossRef] 25. Frankfurt School and UNEP Global Trends in Renewable Energy; Frankfurt School: Frankfurt am Main, Germany, 2016; pp. 1–84. 26. Fu, R.; Chung, D.; Lowder, T.; Feldman, D.; Ardani, K.; Fu, R.; Chung, D.; Lowder, T.; Feldman, D.; Ardani, K.U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017 U.S. Solar Photovoltaic System Cost Benchmark: Q1 2017. Nrel 2017.[CrossRef] 27. Breyer, C.; Bogdanov, D.; Aghahosseini, A.; Gulagi, A.; Child, M.; Oyewo, A.S.; Farfan, J.; Sadovskaia, K.; Vainikka, P. Solar photovoltaics demand for the global energy transition in the power sector. Prog. Photovolta. Res. Appl. 2017, 1–19. [CrossRef] 28. Praveen, R.P.; Baseer, M.A.; Awan, A.B.; Zubair, M. Performance Analysis and Optimization of a Parabolic Trough Solar Power Plant in the Middle East Region. Energies 2018, 11, 741. [CrossRef] 29. Awan, A.B.; Khan, Z.A. Recent progress in renewable energy—Remedy of energy crisis in Pakistan. Renew. Sustain. Energy Rev. 2014, 33, 236–253. [CrossRef] 30. Farnoosh, A.; Lantz, F.; Percebois, J. Electricity generation analyses in an oil-exporting country: Transition to non-fossil fuel based power units in Saudi Arabia. Energy 2014, 69, 299–308. [CrossRef] 31. Fattouh, B. Summer Again: The Swing in Oil Demand in Saudi Bassam Fattouh; Oxford Energy Comment; The Oxford Institute for Energy Studies: Oxford, UK, 2013; pp. 1–8. 32. Collins, R.D.; Gowharji, W.; Habib, A.; Alwajeeh, R.; Stephen, R. Evaluating scenarios of capacity expansion given high seasonal variability of electricity demand: The case of Saudi Arabia. In Proceedings of the 31st International Conference of the System Dynamics Society, Cambridge, MA, USA, 21–25 July 2013; pp. 1–15. 33. Rafique, M.M.; Rehman, S.; Lashin, A.; Al Arifi, N. Analysis of a solar cooling system for climatic conditions of five different cities of Saudi Arabia. Energies 2016, 9, 75. [CrossRef] 34. Cellura, M.; Campanella, L.; Ciulla, G.; Guarino, F.; Lo Brano, V.; Cesarini, D.N.; Orioli, A. The redesign of an Italian building to reach net zero energy performances: A case study of the SHC Task 40-ECBCS Annex 52. Presented at ASHRAE Transactions, Montreal, QC, Canada, 1 July 2011. 35. Mohamed, A.; Hasan, A.; Sirén, K. Fulfillment of net-zero energy building (NZEB) with four metrics in a single family house with different heating alternatives. Appl. Energy 2014, 114, 385–399. [CrossRef] 36. Kilki¸s, ¸S.Energy system analysis of a pilot net-zero exergy district. Energy Convers. Manag. 2014, 87, 1077–1092. [CrossRef] 37. Kolokotsa, D.; Rovas, D.; Kosmatopoulos, E.; Kalaitzakis, K. A roadmap towards intelligent net zero- and positive-energy buildings. Sol. Energy 2011.[CrossRef] 38. Wells, L.; Rismanchi, B.; Aye, L. A review of Net Zero Energy Buildings with reflections on the Australian context. Energy Build. 2018, 158, 616–628. [CrossRef] 39. Doroudchi, E.; Alanne, K.; Okur, Ö.; Kyyrä, J.; Lehtonen, M. Approaching net zero energy housing through integrated EV. Sustain. Cities Soc. 2018, 38, 534–542. [CrossRef] 40. Tsangrassoulis, A.; Li, D.H.W. Energy efficient lighting strategies in buildings. Energy Build. 2018, 165, 284–285. [CrossRef] Energies 2018, 11, 1391 20 of 20
41. Gobbato, C.; Kohler, S.V.; de Souza, I.H.; Denardin, G.W.; de Pelegrini Lopes, J. Integrated Topology of DC-DC Converter for LED Street Lighting System Based on Modular Drivers. IEEE Trans. Ind. Appl. 2018, 9994.[CrossRef] 42. Al Dakheel, J.; Tabet Aoul, K. Building Applications, Opportunities and Challenges of Active Shading Systems: A State-of-the-Art Review. Energies 2017, 10, 1672. [CrossRef] 43. Kirimtat, A.; Koyunbaba, B.K.; Chatzikonstantinou, I.; Sariyildiz, S. Review of simulation modeling for shading devices in buildings. Renew. Sustain. Energy Rev. 2016, 53, 23–49. [CrossRef] 44. Peng, L.L.H.; Jim, C.Y. Green-roof effects on neighborhood microclimate and human thermal sensation. Energies 2013, 6, 598–618. [CrossRef] 45. Dominguez, A.; Kleissl, J.; Luvall, J.C. Effects of solar photovoltaic panels on roof heat transfer. Sol. Energy 2011, 85, 2244–2255. [CrossRef] 46. Kim, J.H.; Kim, H.R.; Kim, J.T. Analysis of photovoltaic applications in zero energy building cases of IEA SHC/EBC Task 40/Annex 52. Sustainability 2015, 7, 8782–8800. [CrossRef] 47. NASA NASA Surface Meteorology and Solar Energy. Available online: https://eosweb.larc.nasa.gov/ cgi-bin/sse/grid.cgi?&num=178144&lat=53&submit=Submit&hgt=100&veg=17&sitelev=&email=luke.s@ wildmail.com&p=grid_id&step=2&lon=-3 (accessed on 1 April 2018). 48. Scherba, A.; Sailor, D.J.; Rosenstiel, T.N.; Wamser, C.C. Modeling impacts of roof reflectivity, integrated photovoltaic panels and green roof systems on sensible heat flux into the urban environment. Build. Environ. 2011, 46, 2542–2551. [CrossRef] 49. NREL. EnergyPlus Engineering Reference; NREL: Golden, CO, USA, 2018; pp. 1–1716. 50. EnergySage. Solar Marketplace Intel Report H1 H2 2017; EnergySage: San Francisco, CA, USA, 2018. 51. NTDC. Upfront Generation Tariff for Solar PV Power Plants and Wind Turbines; NTDC: Lahore, Pakistan, 2018; p. 63. 52. Electricity & Cogeneration Regulatory Authority (ECRA). Annual Statistical Booklet for Electricity and Seawater Desalination Industries 2016; ECRA: Riyadh, Saudi Arabia, 2016. 53. Almasoud, A.H.; Gandayh, H.M. Future of solar energy in Saudi Arabia. J. King Saud Univ. Eng. Sci. 2015, 27, 153–157. [CrossRef] 54. Saudi Electric Company. Electrical Data 2000–2014; Saudi Electric Company: Cambridge, UK, 2014; Volume 1.
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