UNIVERSITY OF CALGARY
Biomass Energy for Rural Electrification:
An Analysis of Small Scale Implementations
by
Ganesh H D Doluweerawatta Gamage
A THESIS
SUBMITTED TO THE FACULTY OF GRADUATE STUDIES
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE
DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
CALGARY, ALBERTA
September, 2006
© Ganesh H D Doluweerawatta Gamage 2006
UNIVERSITY OF CALGARY
FACULTY OF GRADUATE STUDIES
The undersigned certify that they have read, and recommend to the Faculty of Graduate
Studies for acceptance, a thesis entitled " Biomass Energy for Rural Electrification: An
Analysis of Small Scale Implementations" submitted by Ganesh H D Doluweerawatta
Gamage in partial fulfilment of the requirements of the degree of Master of Science.
Supervisor, Dr. Dave Irvine-Halliday Department of Electrical and Computer Engineering
Dr. Ed P. Nowicki Department of Electrical and Computer Engineering
Dr. William D. Rosehart Department of Electrical and Computer Engineering
Dr. Owen R. Fauvel Department of Mechanical and Manufacturing Engineering
______Date
ii Abstract
Lack of access to electrical energy sources is a barrier for development in the rural sector
in developing countries. Escalating costs of fossil energy resources and increasing
concerned on environmental pollution caused by fossil energy burning make rural
electrification a challenge. Biomass energy is an alternative source for electrical power
generation for rural electrification in developing countries. With short rotation forestry techniques and energy conversion technologies such as modern gasification and pyrolysis techniques, biomass energy is a sustainable electrical power source for rural communities in developing countries. An analysis of village scale biomass energy system implementations is presented in this thesis. System economics, greenhouse gas emission reduction benefits and barriers to implement biomass energy systems were analysed in this research work.
iii Acknowledgements
Firstly, I convey my sincere thanks to my supervisor, Dr. Dave Irvine-Halliday for the guidance, advice, encouragement and support given not only in the preparation of this thesis, but also in all the endeavours in the course of my studies at the University of
Calgary.
I wish to thank Dr. Ray Wijewardene for his inspiration and guidance and I am grateful for his mentorship and friendship. I would like to thank Mr. Lalith Seneviratne and Dr. Priyantha Wijayatunga for all the support given for this study. I would like to thank Mr. Ajith Sandanayake and the executives of the Endagalayaya United Solar
Energy Preservation Society for their valuable support in my field surveys. I also thank
Rodolfo Peon and Rashaad Sader for their support for this work. Special thank goes to
Dr. Ed Nowicki for his support particularly in fulfilling my teaching assistantship duties.
I also want to thank the technical staff of the Department of Electrical and Computer
Engineering for their help in many ways. I wish to thank my friends, Arjuna, Achala,
Thushara, Sidantha, Chamika, Kasun and others for all the help throughout my stay in
Calgary.
Finally, I am deeply grateful to my parents, to my wife Yamuni and my sister
Anjana who supported and encouraged me throughout the years.
This thesis was made possible due to a grant from the Natural Sciences and
Engineering Research Council (NSERC) of Canada and a Graduate Teaching/Research
Assistantship at the University of Calgary.
iv Dedication
To,
Dr. Ray Wijewardene,
Chancellor, University of Moratuwa, Sri Lanka
v Table of Contents
Approval Page...... ii Abstract...... iii Acknowledgements...... iv Dedication...... v Table of Contents...... vi List of Tables ...... ix List of Figures...... x List of Equations...... xii List of Symbols and Abbreviations...... xiii
CHAPTER ONE: INTRODUCTION...... 1 1.1 Electricity and human development ...... 1 1.2 Status of rural electrification in developing countries...... 2 1.3 Attempts for rural electrification ...... 4 1.4 Biomass energy for rural electrification ...... 5 1.5 Contribution in this thesis...... 6 1.5.1 Methodology used ...... 7 1.5.2 Layout of this thesis...... 8
CHAPTER TWO: ASSESSMENT OF BIOMASS RESOURCES AND TECHNOLOGY FOR ELECTRICITY GENERATION...... 10 2.1 Biomass resources...... 10 2.1.1 Residues...... 11 2.1.2 Biomass from existing forests ...... 13 2.1.3 Dedicated energy plantations ...... 13 2.2 Technology for electricity production from biomass ...... 18 2.2.1 Biomass gasification...... 18 2.2.1.1 Gasification process...... 19 2.2.1.2 Gasifier types ...... 22 2.2.1.3 Prime movers to generate electricity using producer gas ...... 28 2.2.2 Electricity generation through combustion and steam turbines ...... 31 2.3 Summary...... 32
CHAPTER THREE: CASE STUDIES...... 33 3.1 Case study I - Endagalayaya village biomass power system...... 33 3.1.1 The power system...... 34 3.1.2 Biomass supply...... 36 3.1.3 Capital and operating costs of the system ...... 39 3.1.4 System ownership and management ...... 41 3.1.5 Observations made at Endagalayaya...... 41 3.1.6 Problems and challenges faced by the power system...... 42 3.1.7 Present status of biomass energy usage in Endagalayaya and nearby area.....43 3.2 Case study II – Biomass power plant in “Kohombe” coconut plantation ...... 44
vi 3.2.1 The power system and the energy usage ...... 45 3.2.2 Biomass energy crops in Kohombe estate...... 47 3.2.3 Byproducts from the Gliricidia energy crop...... 47 3.3 Summary and discussion ...... 50
CHAPTER FOUR: ECONOMIC ANALYSIS OF VILLAGE SCALE BIOMASS ENERGY SYSTEMS ...... 51 4.1 Methods and models ...... 52 4.1.1 Component models...... 54 4.1.1.1 Wood gasifier...... 54 4.1.1.2 Internal combustion engine and generator system...... 55 4.1.2 Load profiles...... 56 4.1.3 Generator operating capacity calculation ...... 58 4.1.4 Total energy and fuel calculation ...... 59 4.1.5 Economic analysis...... 61 4.2 Analysis and results ...... 63 4.2.1 Analysis for load profile I...... 64 4.2.2 Analysis for load profile II ...... 71 4.2.3 Biomass energy system with battery storage system ...... 74 4.2.3.1 Battery bank and inverter sizing ...... 75 4.2.3.2 Economic analysis of the proposed system ...... 77 4.3 Summary...... 81
CHAPTER FIVE: GREENHOUSE GAS EMISSION REDUCTION POTENTIAL...... 83 5.1 Global warming, GHGs and the contribution from the electricity sector...... 84 5.1.1 The natural greenhouse effect ...... 84 5.1.2 Anthropogenic greenhouse gas emissions...... 85 5.1.3 The impact of electrical power sector on global warming ...... 87 5.2 Greenhouse gas emission reduction by biomass energy systems...... 90 5.2.1 GHG emission reduction by substituting fossil fuels...... 91 5.2.2 Carbon sequestration in dedicated energy crops ...... 92 5.3 Methods and models ...... 93 5.3.1 Models ...... 96 5.3.1.1 Model for CO2 not released by fossil fuel ...... 96 5.3.1.2 Model for carbon stored in above ground biomass...... 97 5.3.1.3 Model for carbon stored in root biomass...... 100 5.3.1.4 Model for carbon stored in soil...... 101 5.3.1.5 Model for carbon emitted due to fossil fuel usage in plantation activities ...... 101 5.4 Analysis results...... 103 5.4.1 Standard analysis...... 103 5.4.2 Sensitivity analysis ...... 108 5.5 Biomass energy systems and carbon credits...... 112 5.5.1 The Kyoto protocol and CDM...... 112 5.5.2 CERs generated by village scale biomass energy systems...... 114 5.5.3 Trading CERs under CDM...... 115 5.6 Summary...... 117
vii CHAPTER SIX: OVERCOMING THE BARRIERS ...... 118 6.1 Land scarcity barrier ...... 118 6.1.1 Overcoming land scarcity barrier ...... 120 6.2 Economic Barriers ...... 123 6.2.1 Overcoming the economic barriers ...... 123 6.3 Operational barriers ...... 126 6.3.1 Overcoming the operational barriers...... 127 6.4 Summary...... 128
CHAPTER SEVEN: CONCLUSIONS AND FUTURE WORK...... 129 7.1 Future Work...... 131
REFERENCES ...... 133
APPENDIX A: EXPLANATION OF UNITS...... 144
viii List of Tables
Table 1.1 - Number of people without electricity (in millions), 2002 [1]...... 3
Table 2.1 - Reactions occurring in gasification [36]...... 20
Table 2.2 - Producer gas composition and heating value [22]...... 22
Table 4.1 - Costs and other parameters for economic analysis...... 65
Table 4.2 - Load profile I...... 66
Table 4.3 – Economic analysis results for the Load profile I ...... 69
Table 4.4 - Economic analysis results for the Load profile II ...... 72
Table 4.5 - Costs and other parameters of the battery bank and the inverter system...... 77
Table 4.6 - Economic analysis results for biomass generator and battery storage system combination with load profile I...... 79
Table 5.1 – Parameters used for standard analysis ...... 103
Table 5.2 - Results of standard analysis...... 105
ix List of Figures
Figure 2.1 - A Gliricidia (Gliricidia sepium) tree...... 15
Figure 2.2 - Schematic presentation of gasification process [35]...... 19
Figure 2.3 – Fixed bed gasifiers; (a) Updraft gasifier (b) Downdraft gasifier [38]...... 25
Figure 2.4 - Fluidized bed gasifiers; (a) Bubbling bed gasifier. (b) Circulating bed gasifier [38]...... 27
Figure 2.5 - A biomass fired steam turbine system [18]...... 31
Figure 3.1 - Map of the Endagalayaya electricity distribution grid (not to scale)...... 35
Figure 3.2 - The gasifier and generator system at Endagalayaya power system ...... 38
Figure 3.3 - Biomass power station in Endagalayaya...... 38
Figure 3.4 - Gliricidia trees that are grown as a fence...... 40
Figure 3.6 - The gasifier and the generator system at "Kohombe" estate...... 46
Figure 3.7 - "Kohombe" biomass power station...... 46
Figure 3.8 - Gliricidia trees grown in between coconut tree rows...... 49
Figure 4.1 - Wood consumption rate and generation efficiency of a 5kW biomass gasification based power system...... 57
Figure 4.2 - Generator operating capacity calculation procedure for a single hour...... 60
Figure 4.3 - Simplified cash and energy flow over N number of years...... 62
Figure 4.4. - (a) Load profile I. (b) Load profile II...... 67
Figure 4.5 - (a) Hourly power demand; (b) Generator operating capacity and excess power generated for 72 hours for the load profile I...... 68
Figure 4.6 - COE sensitivity analysis against wood and diesel price...... 69
Figure 4.7 - Contribution from various capital and operating expenses to the COE of biomass energy plant (0% incentive case for the load profile I)...... 70
Figure 4.8 - (a) Hourly power demand; (b) Generator operating capacity; for 72 hours for the load profile II...... 72
x Figure 4.9 - Contribution from various capital and operating expenditures to the COE of biomass energy plant (0% incentive case for the load profile II)...... 73
Figure 4.10 - Load, generator operating capacity and the battery bank power flow for the biomass generator and battery storage system combination for a 72 hours period...... 78
Figure 4.11 - COE sensitivity analysis against battery cost and operator salary for the biomass generator and battery storage system combination with 0% incentive on CC...... 80
Figure 4.12 – COE variation with under different operator salary rate at current battery cost ($1.14/Ah) ...... 81
Figure 5.1 - The Earth’s annual and global mean energy balance [60]...... 85
Figure 5.2 - The global carbon cycle, showing the carbon stocks in reservoirs [15]...... 88
Figure 5.3 - Fossil fuel emissions and the rate of increase of CO2 concentration in the atmosphere [15]...... 89
Figure 5.4 - Electricity generation by fuel [4]...... 89
Figure 5.5 - Carbon, energy and fuel flows within the system boundary...... 95
Figure 5.6 - Carbon flow in above ground biomass pools...... 100
Figure 5.7 - Carbon flow in different pools (standard test) ...... 106
Figure 5.8 - Cumulative CO2 offset and annual rate of CO2 offset...... 107
Figure 5.9 - Cumulative CO2 emission of biomass system and diesel system...... 107
Figure 5.10 - Carbon offset after 15 years for Gbr: 0-30 t/ha/y and ηgen: 0-30% in surface plot...... 109
Figure 5.11 - Carbon offset after 15 years for Gbr: 0-30 t/ha/y and ηgen: 0-30% in a colour map...... 110
Figure 5.12 - (a) Percentage variation of C offset with varying Gbr. (b) Percentage change of C offset with varying ηgen...... 111
Figure 5.13 - Affect on cost of electricity by different CER prices...... 115
Figure 6.1 - Power densities of various forms of biomass production [84] ...... 119
xi List of Equations
Equation 4.1 – Producer gas generation rate….………………………………...……….54 Equation 4.2 – Engine fuel consumption rate..………………………………….……….55 Equation 4.3 – Wood consumption rate..…………………………………………..…….56 Equation 4.4 – Biomass system operating efficiency...………………………………….56 Equation 4.5 – Yearly load………………………………………………...…………….58 Equation 4.6 – Hourly power demand of the power system.…………………………….58 Equation 4.7 – Annual wood requirement…...….……………………………………….59 Equation 4.8 – Total energy generated……..……………………………………………61 Equation 4.9 – Total energy available to the end user.…………………………..………61 Equation 4.10 – Present value of the lifecycle cost...……………………………………61 Equation 4.11 – Annualized cost……………….………………………………...... ……63 Equation 4.12 – Cost of energy……………....……………………………………….….63 Equation 4.13 – Battery bank capacity…………………………………..………………76 Equation 5.1 – Photosynthesis reaction……………………………….....………………92 Equation 5.2 – Total electricity generated………………………………………...…..…96 Equation 5.3 – Amount of fossil energy replaced by biomass…….………………….....96 Equation 5.4 – Amount of carbon not released due to fossil fuel substitution…………..97 Equation 5.5 – Amount of carbon not released due to fossil fuel substitution ………….97 Equation 5.6 – Carbon stock in above ground iomass……….………………..…………98 Equation 5.7 – Carbon stored in roots………………………...... ………………..……100 Equation 5.8 – Carbon emitted by tractors used for plantation establishment………....102 Equation 5.9 – Carbon emitted by tractors used for biomass transport.………………..102
xii List of Symbols and Abbreviations
AC Annualized cost Bcap Battery bank capacity C Carbon CC Capital cost CDM Clean development mechanisms CER Certified emission reduction Cesp Carbon emitted by tractor usage in plantation establishment Cetr Carbon emitted by the tractors used to transport biomass Cf Non-released carbon amount CFL Compact fluorescent lamp Ch Carbon stored in harvested biomass CH4 Methane CHP Combine heat and power CI Loan interest Cmax Maximum carbon stock Cn Carbon stock in above ground biomass CO Carbon monoxide CO2 Carbon dioxide COE Cost of energy Cr Carbon stored in roots CRF Capital recovery factor Cs Carbon stored in stumps Csoil Carbon stored in soil Ddiesel Density of diesel DOD Battery depth of discharge E Total energy available to the end user Ebat Energy delivered by the battery bank Eex Excess energy generated Egen Total energy generated EM Electromagnetic F Engine fuel consumption rate F0 Intercept of the engine fuel consumption curve F1 Slope of the engine fuel consumption curve FC Fuel cost G Tree (biomass) growth rate Gch Growth rate of the carbon stock in harvestable biomass Gcn Carbon stock growth rate Gh Harvestable biomass growth rate GHG Greenhouse gas H2 Hydrogen Hf Lower heating value of the base case fuel Hgas Lower heating value of producer gas
xiii Hw Lower heating value of wood IC Internal combustion Ic Carbon content of the base case fossil fuel IPCC Intergovernmental Panel on Climate Change L Hourly power demand of the power system LCC Life cycle costing LCCPV The present value of the lifecycle cost Lday Daily load vector LHV Lower heating value LUTW Light up the world foundation Lyear Yearly load vector MC Maintenance cost mgas Producer gas generation rate mw Wood consumption rate Mw Annual wood requirement N Number of years which the economic analysis is performed. N2 Nitrogen nd Daily noise in power demand nh Hourly noise in power demand OS Operator salary P Generator operating capacity Pe Generator size PV Photovoltaic r Discounting rate RC Replacement cost SRF Short rotation forestry SV Salvage value TAR Third assessment report of the IPCC TPES Total primary energy supply UNFCCC United Nations Framework Convention on Climate Change Vbat Nominal battery voltage δl Power distribution loss ηb Biomass system operating efficiency ηbat Battery cycle efficiency ηc Combustion efficiency of the base case fuel ηf Efficiency of the base case system ηgas Gasifier cold gasification efficiency ηgen Biomass generator efficiency ηinv Inverter efficiency λ Wavelength
xiv 1
Chapter One: Introduction
Electricity is one of the most important energy carriers in the modern society. Day to day human activities are greatly dependent on the electrical energy that is used for lighting, appliances, communications and other energy sources derived through electrical energy such as mechanical and heating energy. However one of the most striking features of the present world electrical energy distribution is the massive disparity between developing countries and industrialized countries. Some 1.6 billion people, about a quarter of the humanity have no access to electrical energy sources [1]. More than 99% of them are living in the developing world. Everyday when the sun sets, this unprivileged and underserved portion of humanity, light up a kerosene wick lamp or a candle to illuminate their households in this era of technological marvels, just like humans in caves started a fire to light up their dwellings a few thousands of years ago. Yet they pay dearly and a very considerable sum from their hard earned income, for the fuel used for that near primitive source of illumination.
1.1 Electricity and human development
Availability of electricity is critical for providing even the basic services such as home lighting, education and health care. The ability to meet, read, and study in an illuminated environment after dark has an enormous impact on the social, economic, physical and spiritual lives of those with limited opportunities for progress. Among the most significant of these benefits are the improved conditions for the education of children and
2 women in areas where poverty and illiteracy walk hand in hand [2]. Availability of home illumination will lengthen the number of hours that can be used for income generating activities. For health care services, in addition to illumination electricity, there is a need for sterilizations, clean water supply, sanitation and refrigeration of essential medicines.
A statistical analysis of 15,000 townships in the Philippines indicates that there is a significant relationship between maternal health and access to electricity [3]. Electricity can also run machines that support livelihood activities such as food processing, irrigation for agriculture, apparel production, and small scale manufacturing. Access to communication and information is becoming essential in this modern society and availability of electricity in rural areas will enable access to those through wireless telephony.
1.2 Status of rural electrification in developing countries
As of 2002 about 1,623 million people were without access to electricity and 1,615 million were from the developing countries (Table 1.1). Of that number more than 80% were living in rural areas [1]. Sub Saharan Africa and South Asia are the regions with lowest electrification levels. About 64% of the world electrical energy is produced using fossil energy sources and most developing nations do not posses them [4]. The electrical energy services in developing countries are also plagued by problems such as escalating fossil energy prices, generation expansion to meet the high electricity demand growth, financing the expansion of distribution grids and environmental pollution associated with
3 fossil energy sources. Hence the prospects of obtaining electricity services in rural areas in the developing countries are low.
Table 1.1 - Number of people without electricity (in millions), 2002 [1].
Region Rural Urban Total Africa 416 118 535 Sub-Saharan Africa 408 117 526 North Africa 8 1 9 Developing Asia 871 148 1019 East Asia and China 192 29 221 South Asia 679 119 798 Middle East 13 1 14 Latin America 39 1 46 Developing Countries 1339 275 1615 OECD and transition economies 7 <1 7 World 1347 275 1623 Note: Organisation for Economic Co-operation and Development (OECD) is an international organization of developed countries. Transition economies are the countries in transition from planed economies to free market.
Rural households in developing countries mainly depend on kerosene or candles for home illumination. The expenditure on kerosene can be high as 20% of the monthly income of the household. Escalating prices increases the economic burden caused by
kerosene based lighting [5][6]. The lighting services provided by kerosene are very poor
in quality. The total light output of a kerosene wick lamp is about 10 lumen (lm) while an
electrical source such as a 5 Watt (W) compact fluorescent lamp (CFL) with an efficacy
of 60 lm/W will provide about 300 lm [7]. The emissions from kerosene lamps cause
indoor air pollution that can lead to respiratory illnesses. Fuel based lighting sources are
accident prone and burn accidents due to over turned kerosene lamps are common in rural
4 areas. Without electricity, obtaining other service that need it such as refrigeration, power for appliances and machines and telecommunications is virtually impossible. Lack of electricity and other modern energy services in rural areas can decrease the willingness of professionals such as doctors, teachers, nurses etc. to reside in those areas, further limiting services and opportunities to local population [8].
1.3 Attempts for rural electrification
Many organisations have worked tirelessly to provide electrical services to the rural sectors in developing countries, using renewable energy sources and other distributed generation schemes. Many of these projects uses solar photovoltaic (PV), wind energy, micro hydro energy and geothermal energy to generate electricity. There are about 1.1 million solar home lighting systems and solar lanterns being used in developing countries
[9]. Many village scale mini grids developed with micro hydro based electricity generation are being used in Asia. China alone has about 60,000 such systems while other leading countries such as Nepal, India, Vietnam and Sri Lanka have about 100-1000 micro hydro systems each [9].
Light Up The World (LUTW) Foundation of the University of Calgary is the world leader in pioneering the provision of lighting services to the rural sectors in developing countries using solid state lighting and PV energy [6][10][11]. Since its inception in 2000
LUTW has provided more than 14,000 lighting systems to rural households in 26 countries.
5
Hydro resources are not available in all regions and seasonal variations of the hydro resources are another problem for a steady electricity supply. Similar problems are associated with wind power. PV usage in general is possible in almost any region of the world. However the present relatively high capital costs, as well as recurring costs such as battery bank replacement, make it affordable only in small scale (<100W) for the rural populations. Therefore usage is limited only for lighting and few low power appliances.
In all of the sources described above, providing power on demand as in case of a utility grid is a great challenge.
1.4 Biomass energy for rural electrification
Biomass energy, the energy derived from wood and other plant matter is an important element in the global total primary energy supply (TPES) and accounts for about 15% of it [12]. In the case of developing countries the contribution from biomass to the TPES could be high as much as 40%, but today most of the biomass energy is utilized inefficiently, mainly for cooking and heating in rural households [12][13].
Modernised biomass energy is an ideal option for rural electrification. With short rotation forestry techniques and energy conversion technologies such as modern gasification and pyrolysis techniques, biomass energy is a sustainable electrical power source as opposed to conventional fossil fuels. Operation of a biomass energy system similar to a fossil fuel based power system with on demand power generation is quite possible, unlike other intermittent sources of alternative energy. In addition to providing electricity services
6 which will contribute to human development, many other social, economic and environmental benefits can be obtained by using biomass energy.
Extensive use of biomass energy will create employment thus contributing to rural economic development, and the use of biomass energy for electrical power generation instead of traditional fossil energy will save the foreign exchange that was spent on importing fossil fuel [14].
One of the main advantages of a biomass energy system is its environmental friendliness and particularly its contribution to the mitigation of global warming. The electricity generation sector is one of the main producers of greenhouse gases (GHG) that causes global warming. A sustainably implemented biomass power system is a GHG free power system and moreover it may provide GHG sinks in the form of the biomass energy crop plantations, thus reducing the GHG levels in the atmosphere. This feature has created an increased global interest on biomass energy systems. Future global energy supply scenarios proposed by various studies including those made by the Intergovernmental
Panel on Climate Change (IPCC) have included biomass as a key energy source for future demands [15-20].
1.5 Contribution in this thesis
The contributions in this thesis are designed to support the planning and implementation of biomass energy systems for rural electrification by providing a multidisciplinary
7 analysis of small scale implementations. The work that has been published on biomass electricity generation have mainly focused on large scale system implementations that are used for industrial or utility based power systems [17][21]. The work that has been published on rural small scale applications are limited to a few areas such as the assessment of conversion technologies [18][22] or a presentation of a project experience
[23].
The objective of this thesis is to perform a comprehensive analysis of small scale biomass electrical energy systems that can be employed for rural electrification considering their unique characteristics. Since village level electrification is being considered for this research work, the size of the energy systems analysed was limited to few kilowatts. An assessment of biomass resources and conversion technologies, a comprehensive analysis of the system economics and GHG benefits and an analysis of the barriers are included in the thesis. Two case studies are also included to demonstrate the feasibility of this technology for rural electrification. A secondary objective of this work is to develop system simulation and analysis modules that are to be included in an integrated biomass system planning and analysis tool.
1.5.1 Methodology used
Literature surveys and field surveys were used to study the state of the art technologies, operational characteristics, biomass resource characteristics and barriers. A number of interviews with experts, and also biomass energy users, were also conducted to get
8 further information. The field survey was made in January 2006 in Sri Lanka and two biomass energy systems that are in operation there were studied in detail.
Simulation and analysis modules were developed for economic and GHG benefits analysis. Biomass power system components as well as the associated energy crop plantation were modeled using simple mathematical models to develop those modules.
These were implemented using Matlab® m-files.
1.5.2 Layout of this thesis
Chapter 1 of the thesis presents an introduction about the status of rural electrification in the developing countries and the research objectives. An assessment of biomass resources and conversion technologies are presented in Chapter 2. Two case studies are presented in Chapter 3. Chapter 4 consists of a comprehensive economic analysis of village scale biomass power systems. System economics with different power demands are analysed.
The methodologies and models used are presented in detail. An analysis of GHG benefits of small scale biomass energy systems is presented in Chapter 5. An introduction on the global warming issue and global attempts to mitigate it is included. GHG benefits are quantified using the simulation and analysis modules developed, and the details of the models and results are presented. Assessment of the barriers to implement biomass energy systems is presented in Chapter 6 and suggestions as to how to overcome those barriers are included. The conclusions of this research work and anticipated future work
9 are presented in Chapter 7. A description of the units that are used in this thesis but are not standard metric (SI) units is presented in Appendix A.
10
Chapter Two: Assessment of Biomass Resources and Technology for Electricity Generation
An assessment of biomass resources and technology options for electrical energy generation is presented in this chapter. The information for the assessment was obtained mainly through literature and a field survey. Alternative forms of biomass resources are assessed. Various technology options that can be used for electricity generation are discussed with more emphasis given to those that are preferred for small scale implementations.
2.1 Biomass resources
In the perspective of energy, biomass refers to all forms of plant or animal derived materials that can be utilized as a form of energy that includes wood, herbaceous plant matter, crop and forest residues, dung etc. [12]. The annual global biomass production by photosynthesis is 220 billion dry tonnes. This is equivalent to 10 times global energy use
[18]. The role of a particular biomass resource as a fuel for energy is largely depends on its physical and chemical properties such as the heating value, moisture content, mass density, ash content etc. The share of biomass in global primary energy supply can be as much as 15%. However mostly it is used as a non commercial source of fuel and thus not included in official energy statistics [12]. In many cases biomass is used for cooking and heating. Three sources that have the largest potential are the residues, biomass from existing forestry and biomass from dedicated energy plantations.
11
2.1.1 Residues
Residues are the byproducts of food, fiber and forestry products. Hall et al have estimated the global total energy potential of residues to be 111 EJ/year [12]. Agricultural residues such as rice husk, straw, bagasse, animal dung etc. and forestry residues such as saw dust, mill residues, waste wood etc. are used for domestic and industrial energy requirements throughout the world.
However not all the residues can be used for energy. The cost of collecting, processing and transporting residues may be too high so it may not be cost effective to utilize them for energy. In other cases some of the residues are needed to be left on the originating site itself for nutritional recycling. Furthermore there may be competing uses for residues that are more cost effective [12][18].
One notably important biomass residue is bagasse, the fibers remaining from sugarcane after the juice extraction. The bagasse generation rate is about 250 kg for a tonne of sugarcane processed (25% in mass) [21]. The heating value of bagasse is about 10MJ/kg.
The world sugarcane production is about 1billion tonnes per year and ideally that will produce about 250 million tonnes of bagasse per year [21][24]. Sugar factories usually utilize the bagasse for thermal and electrical generation for on site usage. However, since there is such a large amount, this resource is under utilized. One main problem associated with bagasse use for energy particularly for electricity generation is that its availability is limited to the sugarcane harvesting and crushing season [21] which is only about 6 to 7
12 months long. Therefore unless it is used with a mix of other fuels, year round generation of electricity is a challenge. To generate electricity using bagasse normally a boiler/steam turbine method is the most suitable.
Some other forms of agricultural residues with large potential are rice husk, cereal straws from maize, corn and wheat and also coconut shells. Wood residues from forestry products too have a larger potential due to the worldwide availability. Conversion processes that can be used to harness energy from the residues depend on their chemical and physical characteristics. In general biochemical conversion processes are suitable for residues with higher moisture contents while thermochemical processes are preferred for those with lower moisture contents [18][21].
Residue biomass is an important biomass energy source and good management practices are needed to utilize the full potential of it. The biomass intensive energy scenarios developed by the IPCC includes a share of 55 EJ/y from residues to total global commercial energy supply by 2050 [25]. A comprehensive analysis of worldwide residue biomass energy potential is presented by Hall et al in [12]. A more recent analysis on their potential, covering a comprehensive range of residues in five Asian countries, has been done by Bhattacharya et al in [26]. A country or region specific estimation of the residue biomass resources with emphasis on their temporal availability, energy densities and harnessing costs is needed to plan and implement biomass energy systems that utilize them.
13
2.1.2 Biomass from existing forests
Forests that are managed for lumber and the forestry industry can provide biomass for energy in many ways. The unharvested overgrowth that is too low quality for forestry products can be harvested for energy. Also, removing of such overgrowth will increase the yield of remaining high quality wood [12][18][27]. Furthermore biomass from the activities thinnings, prunings and selective removals that are done as part of management of the commercial forests can be effectively utilized for energy applications[12][21].
However exploiting of old-growth or the natural forest for biomass energy is not recommended. This will adversely affect the biodiversity and the ecology which would result in ripple effects in the long run. In the areas where energy is generated using biomass, firm policies and management practices must be adopted in order to prevent exploitation of natural forest.
2.1.3 Dedicated energy plantations
Dedicated energy plantations make the biomass energy a more significant source of energy in many parts of the world. Dedicated energy crops are sustainably grown and managed in plantations in order to obtain wood biomass for energy generation purposes.
Usually fast growing trees with shorter harvesting cycles are used in these plantations.
This plantation practice is also referred to as short rotation forestry (SRF) or simply SRF plantations [12][14][21].
14
In SRF plantations, the energy crop species are grown and managed like any other agricultural crop. The tree species used for the energy plantations depends on soil and climate conditions of the region that the plantation is grown. Some common species that are used in the tropical regions are Gliricidia (Gliricidia sepium), Acacia (Acacia auriculiformis), Cassia (Casuarinas equicetifolia), Giant ipil-ipil (Leucaena leucocephala) and Eucalyptus species. In the temperate regions the common SRF species are poplars (Populus) and willow species (mainly Salix viminalis and Salix desyclados).
SRF plantations can be harvested as clear cutting, followed by replanting or periodic coppicing. Coppicing is the process in which the side branches of the trees sprout after older branches are periodically harvested leaving the stump intact and growing. Many hardwood species are suitable for coppice regimes [14][21]. Harvesting frequency in both cases depends on the tree specie as well as the climate and soil conditions. Furthermore, the season of the year also affects the coppice regrowth. The nutritional removal from the soil at harvest is minimal as only the carbon (C), hydrogen (H) and oxygen (O) are consumed at combustion. A large portion of the nutrient uptake is recycled back to the soil by returning the foliage and softwood parts back to the site and allowing it to decay.
By selecting nitrogen fixing trees for the SRF plantation, the soil quality can be increased and also the nitrogen (N) loss at combustion as NOx can be mitigated.
The specie that was studied in detail in this study is Gliricidia sepium in Sri Lanka. It is a fast growing and nitrogen fixing tree specie that is widely grown in tropical regions in
South America, Africa, Asia and the Pacific islands. Though not a native specie to Sri
15
Lanka as it was introduced as a shade growth tree for the tea plantations in the colonial era, it has become widely distributed in almost all parts of the country. Despite being an introduced specie, it has fortunately not become an invasive plant threatening the native species, and it has been widely used for fencing, ally cropping, fuel woods and shading for vegetables and other commercial crops. This is a medium size semi deciduous tree that typically grows to about 8-10m in height with a broad canopy [14][28].
Figure 2.1 - A Gliricidia (Gliricidia sepium) tree.
Large cuttings of Gliricidia are mainly used for plantation setup. At harvest usually all
the branches of a tree are pruned and utilized for energy. The first harvesting can be made
approximately 8-12 months after planting, after which harvesting can be made in 6-8
16 months cycles. The yield depends on the climate and soil conditions as well as the management practice used. From a Gliricidia only plantation a yield of 20-25 t/ha/y under favorable conditions and 10-15 t/ha/y under less favorable conditions can be obtained
[14][29]. The foliage can be used as a natural nitrogen fertilizer. Gliricidia can be easily intercropped with commercial crops and hence the land can be effectively shared. Due to large potential of Gliricidia as energy crop specie, the government of Sri Lanka recently declared it as the county’s fourth commercial plantation crop [30].
Properly managed energy crop plantations foster other advantages such as prevention of soil erosion and restoration of degraded lands. A few factors are vital for the feasibility of energy crop plantations and the most important are the cost of the plantation and the total energy required for planting, harvesting and processing biomass for energy. These two factors depends on the type of the land used, agroforestry practices used, use of machinery for plantation activities and their fuel consumptions, labour inputs, harvesting and hauling distances, fertilizer usage for plantations and the yield of the plantation. In general the energy used for biomass production should be considerably lower than energy produced using them. By limiting the use of machinery and the distance that the biomass is transported before being utilized the cost and energy requirements can be reduced.
Furthermore, by selecting species that require minimal or no fertilizer, the cost and energy input can be further reduced. An investigation on the limiting cases of these parameters for various plantation species and for different sizes of power generation plants merits some research attention.
17
Another challenge for dedicated energy plantations is that the land resource available in a particular country or a region is limited, and if dedicated energy plantations are to be implemented they must compete for the land with other human and societal needs. A major concern with dedicated energy plantations is that they may be in competition with food production. Since the land is needed to grow food, but energy can be provided in a variety of ways, food production usually has priority [12]. This is a key issue for the large scale exploitation of biomass for energy and comprehensive region specific assessments are needed with insight into the future demands and needs. One such assessment for the
African region done by Marrison and Larson [31] and a similar study on Sri Lanka has been done by Perera et al in [32]. Degraded lands due to previous improper land use practices can be effectively utilized for energy plantations by proper species selection
[12][14][25][33][34]. The amount of such degraded lands in developing countries is about 2 billion hectares and about 621 million hectares of that can be replanted [25].
Many plantation trials made in developing countries have demonstrated the feasibility of this agroforestry practice [12][14]. Another alternative is sharing the same land with food and commercial agriculture by intercropping [34]. Long term studies with different species are needed for planning such plantations and biomass energy systems.
Dedicated energy crops can be considered as the most important biomass resource that will play a key role in biomass intensive energy generation. The IPCC biomass energy scenarios includes 385 million hectares of dedicated energy plantations globally by 2050 producing some 120 EJ/y of energy [25].
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2.2 Technology for electricity production from biomass
Power generation technology adopted to harness the energy in the biomass depends on the type of biomass used. The technologies that are available to generate electricity include thermochemical conversions such as gasification and combustion and biochemical conversions such as anaerobic digestion. The latter is more suitable for biomass with high moisture content such as animal dung and urban or agricultural waste.
Energy in woody biomass is mainly harnessed through thermochemical conversions.
Gasification of woody biomass is mainly studied in this research as a technology for rural electrification using biomass resources. Therefore only the thermochemical conversion technologies and the prime movers that can be used in order to generate electricity are described here. Reviews of various biochemical conversion processes that can be utilized to convert biomass into energy and case examples are presented in [16][18].
2.2.1 Biomass gasification
Gasification is the process of converting solid fuels into a combustible gaseous fuel by partial oxidation. This combustible gaseous mixture is usually called the producer gas.
This low calorific value gas can be combusted in internal combustion (IC) engines or gas turbines to generate electricity. The process by which this conversion takes place is quite complex from a chemical point of view and the reactor in which the conversion process occurs is called as gasifier.
19
2.2.1.1 Gasification process
Gasification of solid biomass includes number of steps [35] that are
drying of biomass;
thermal decomposition to gas, condensable vapors and char (pyrolysis);
subsequent thermal cracking of vapors to gas and char;
gasification of char by steam or carbon dioxide;
partial oxidation of combustible gas, vapors and char.
These different steps are illustrated in Figure 2.2.
Figure 2.2 - Schematic presentation of gasification process [35]. In a gasifier the process steps mentioned above occur in different zones and the gas
produced consists of carbon monoxide (CO), hydrogen (H2), carbon dioxide (CO2), methane (CH4) and nitrogen (N2) (if air is used as the gasification agent) [35][36]. The
20 reactions that take place in the gasification process, the enthalpy of the reaction and the zone in the reactor in which they take place are listed in Table 2.1.
As can be seen from Table 2.1 some reactions are endothermic (reactions 4-5) and the energy necessary for those reactions is provided by the combustion and partial combustion reactions within the gasifier [36][37]. The temperature inside the reactor for wood gasification is about 800°-1000°C. The gas produced contains impurities such as small char particles, ash, tars and oil.
Table 2.1 - Reactions occurring in gasification [36]. Enthalpy of the Reaction reaction, ΔQ (kJ/mol) Combustion zone C + O2 = CO2 -405.9 (1) C + ½O2 = CO -123.1 (2) Pyrolysis zone 4CnHm = mCH4 + (4n-m)C exothermic (3) Reduction zone C + CO2 = 2CO 159.7 (4) C + H2O = CO + H2 118.7 (5) C + 2H2 = CH4 -87.4 (6) CO + H2O = CO2 + H2 -40.9 (7) CO + 3H2 = CH4 + H2O -206.3 (8) Sign convention of enthalpies: Endothermic (energy absorbed): ΔQ>0 Exothermic (energy released): ΔQ<0
Solid residue left after the gasification consists mainly of ash that is composed of oxides
of Ca, K, Na, Mg and Si and possibly carbon or char [36]. Gasifiers can operate under
low (near atmosphere -1atm) or high (several atmospheres) pressure.
21
The quality and the heating value of the gas depend on the factors such as the characteristics of biomass feedstock, type of reactor, reactor operating conditions and the gasification agent used. Feedstock properties that can affect the gas quality are the moisture content, ash content and composition, heating value, bulk density and the volatile matter content [35][36]. High moisture content in the feed stock has an adverse effect on the thermal balance. Low ash content improves the thermal balance, reduces the loss of carbon in the residues and reduces the operating problems such as slagging.
Slagging also depends on the operating temperature and in the case of biomass, the presence of SiO2 in ash. SiO2 has the lowest melting point among the ash components
and can melt due to the higher temperature inside the gasifier causing slagging.
The amount of N2 in the producer gas is a key parameter that determines the heating
value of the producer gas. It is an incombustible gas and a high N2 content reduces the
heating value of the producer gas. N2 free producer gas can be obtained by using oxygen or hydrogen as the gasification agent. Typical composition and the characteristics of the producer gas obtained by gasifying biomass with an air blown gasifier are listed in Table
2.1.
The producer gas obtained through gasification is then cleaned and cooled before use in an IC engine or turbine. The temperature of the gas leaving the gasifier is about 300°-
500° C and this has to be cooled to raise the energy density. Most coolers that are used are gas to air heat exchanger where the cooling is done by free convection of air outside the heat exchanger. The impurities such as organic compounds, ash, char alkali and tar
22 adversely affect the prime movers. To clean the gas, filters such as dry cyclone filters, wet scrubbers and dry cloth filters are used [36].
Table 2.2 - Producer gas composition and heating value [22]. Gas composition (dry basis) CO 17-22% CO2 9-15% N2 50-54% H2 12-20% CH4 2-3% Gas heating value 4-6 MJ/Nm3 (MJ per normal m3)
Tars in the producer gas are the main problem encountered with gasification based power
systems. These are the high molecular weight compounds in the gas downstream of the
gasifier and begin to condense at temperatures less than 450°C. They deposit on the walls
of the pipings and also cause problems in the subsequent prime movers that are used to
generate energy. Low or no tar producer gas is obtained by using improved gasifiers or
by employing tar removal processes. Tar can be cracked down into lower molecular
weight compounds using either catalytic or thermal processes [36], but these processes
increase the cost and complexity of the gasification system.
2.2.1.2 Gasifier types
Different kinds of gasifier designs are being employed in various applications. These can
be categorized according to the design of the reactor (fixed bed, fluidized bed), according
to the gasification agent (air blown, oxygen gasifiers) and according to the pressure in the
23 gasifier (atmospheric, pressurized). Oxygen gasifiers and pressurized gasifiers are usually used in large scale systems particularly in industrial applications and large scale power generation. An important parameter of a gasifier is the gasification efficiency. This can be expressed on a hot or cold gas basis. The hot gasification efficiency is the ratio between the chemical and thermal energy content of the producer gas and the energy content of the feedstock. The cold gasification efficiency is the ratio between the chemical energy content of the producer gas and the energy content of the feedstock [35].
In case of electricity generation through combusting producer gas, the cold gasification efficiency is considered for analysis as only the chemical energy of the fuel is the parameter of interest.
Four kinds of gasifiers suitable for wood biomass gasification are described in this section. These are distinguished according to the design of the reactor, fixed bed gasifiers and fluidized bed gasifiers. In fixed bed gasifiers the feed stock is packed in a fixed bed and the different zones of gasification can be clearly identified. According to the direction of gas flow two kinds of fixed bed gasifiers can be identified, namely the updraft gasifiers and downdraft gasifiers. These two fixed bed gasifier types are more suited for small scale gasification applications [18]. In fluidized bed gasifiers solids behave as fluids through contact with a gas. Air, oxygen and/or steam are injected from below to keep the bed in suspension (fluidized). Gasification process occurs throughout the bed and different process zones can not be distinguished [18][35]. Turbulence causes excellent heat and mass transfer, producing uniform temperatures everywhere in the bed.
Higher throughputs are possible with fluidized bed gasifiers. These are more expensive
24 than fixed bed gasifiers and mainly used in large scale applications. The higher capital cost and more complex operation makes them less suited for small scale applications.
Two fluidized bed gasifier kinds are described below.
2.2.1.2.1 Fixed bed updraft gasifiers
This is the simplest type of gasifier. Feed is introduced from the top and air from the bottom of the reactor via a grate (Figure 2.3 (a)). Biomass fed from the top moves downwards in the opposite direction of the gas flow through the drying, pyrolysis reduction and oxidizing zones as a result of the conversion process and ash removal. The temperature of the gas exiting the reactor is low (200°-300° C) and higher gasification efficiency can be obtained because of that. The other advantages of this design are the simplicity and the tolerance to biomass with higher moisture content.
A major disadvantage of this design is the high amount of tar and pyrolysis products in the exit gas because the pyrolysis gas is not combusted. Therefore the updraft gasifier is more suited for direct thermal energy applications such as to generate gas as a boiler fuel.
In case of power generation applications, extensive gas cleaning is required [35][37].
2.2.1.2.2 Fixed bed downdraft gasifiers
In a downdraft gasifier the feed is also inserted from the top, but the producer gas leaves the reactor from the bottom (Figure 2.3 (b)). Hence, both the fuel and the gas flow in the same direction. The same zone formation can be observed as in the case of updraft
25 gasifier but the order is somewhat different since air is introduced directly to the oxidation zone.
(a) (b)
Figure 2.3 – Fixed bed gasifiers; (a) Updraft gasifier (b) Downdraft gasifier [38].
Because the gas passes through the high temperature oxidation zone, tars from the pyrolysis are cracked into lower molecular weight substances. Thus low tar content producer gas that is suitable for IC engine applications can be obtained. The main drawback of this reactor is the high ash and dust particle concentration because the gas flows through the oxidizing zone where small ash particles are entrained. Also scaling up of this type of gasifier is limited and furthermore the quality of the gas depends on the
26 level of loading. At low load levels more tar is produced because tar cracking becomes less efficient at low temperatures. At high load levels the tar cracking capability is higher but the particulate content of the exit gas also becomes higher [35]. Due to the lower cost and inherent capability of producing low tar producer gas, downdraft gasifiers are widely used for small scale power generation applications using IC engines.
2.2.1.2.3 Bubbling fluidized bed gasifiers
In the bubbling fluidized bed gasifier the air is introduced into the vessel through a grate in the bottom. Above the grate is a moving bed of fine grained material such as sand, into which the prepared feedstock (biomass) is introduced (Figure 2.4(a)). The temperature inside is maintained at 700°-900° C by controlling air/feed stock ratio. The fluidized bed gives rapid heating of reactant gases in addition to excellent mixing of biomass solids and inert media. Feed material is pyrolysed in the hot bed to form char with gaseous compounds, high molecular weight compounds being cracked by contact with the hot bed material. Tar production is moderately high at 1% to 2%, but less than a fixed bed updraft gasifier [37].
2.2.1.2.4 Circulating fluidized bed gasifier
In circulating fluidized bed gasifiers the bed material is circulated between the reaction vessel and a cyclone separator (Figure 2.4 (b)). In this reactor there is no distinct interface between the dense phase of fluidized sand and the freeboard. In fact the higher velocity
27 fluidization regime means that there is a particle density gradient from the bottom of the gasifier to the top. Entrained media and char fines are recycled back to the gasifier via a retention cyclone. The higher velocity regime gives an alternative approach to increasing char residence time to promote higher efficiency gasification [35].
(a) (b)
Figure 2.4 - Fluidized bed gasifiers; (a) Bubbling bed gasifier. (b) Circulating bed gasifier [38].
Both fluidized bed gasifiers are used in large scale applications. Pressurized air or oxygen may be injected in order to get high throughputs and high quality producer gas.
Due to the recent increased interest in biomass based power generation, a great deal of research and development is being done on developing improved gasifiers. A
28 comprehensive assessment of modern gasifier technologies with surveys of their applications for heat and power generation are presented in [17].
2.2.1.3 Prime movers to generate electricity using producer gas
Internal combustion engines are used by almost all the small scale biomass gasification based electrical power systems. Therefore IC engines are discussed in detail below.
Other possible prime movers are the Stirling cycle engines and the gas turbines.
Gas turbines are relatively expensive thus increasing the capital investment needed to implement the power system. Also gas turbines demand stringent gas quality requirements and extensive gas cleaning mechanisms are needed and this will increase the cost and complexity even more. Therefore for small scale implementations in rural areas, gas turbines are not cost effective. However for systems with generation capacities of a few megawatts (1-100 MW) the gas turbine is the preferred choice as the cost of the equipment is less sensitive to the scale [18].
Modest gas quality requirements in terms of particulate content, are demanded by Stirling engines thus making them a good choice for producer gas operation [22]. However the operating efficiency of Stirling cycle engine with a gas as the working fluid is low and the gas must be pressurised in order to get a compact powerful engine. It is concluded that the cost of them is too high to foster a cost effective power system.
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2.2.1.3.1 Internal combustion engines for electricity generation with biomass energy
IC engines operated with producer gas are an ideal choice for small scale electricity generation systems in rural areas of the developing world. The capital cost required for a gasifier/IC engine power system is less than US$1000/kW even for smaller systems
[14][18].The technology is well understood and the maintenance requirements and the operator skills needed for running are modest. Millions of IC engines, excluding the ones in vehicles, are being used in developing countries for applications such as power generation, mechanical shaft power, irrigation etc. It has been estimated that in India, about 8 million small diesel engines are used to drive irrigation pumps [18].
Small scale engines (a few kilo Watts) that are designed to operate on gaseous fuels are not common commercially. However IC engines that are usually operated with gasoline or diesel can be converted to run with producer gas, either in 100% gas mode or in a mixture with conventional fuel. Converting the gasoline engines, which are spark ignition engines, is easier than converting compression ignition diesel engines. For the gasoline engines only the changes to the fuel injection and control system are needed. If a diesel engine is to be converted to run in 100% producer gas mode a spark ignition system must be installed and the compression ratio has to be reduced. Contrarily a diesel engine can be operated with 90% producer gas and 10% diesel mode [18][23]. However the availability of fossil fuels will limit the suitability of such a system for remote location applications.
Diesel engines have been favoured because of their higher efficiency, greater reliability and durability.
30
Power and efficiency loss are unavoidable when an IC engine operates with producer gas and the main reason is the lower heating value of the producer gas. For example the lower heating value of the stoichiometric producer gas/air mixture is only about 2.5
MJ/Nm3 compared to 3.5 MJ/Nm3 for gasoline/air mixture and 3.3 MJ/Nm3 for diesel/air
mixture [22]. In case of diesel engines running with producer gas there is an efficiency
drop due to the reduction of compression ratio as well. Efficiencies up to 25-30% are possible to obtain with engines combusting producer gas though typical operating efficiencies for small scale systems are 17-20%. The overall system efficiency is the product of the cold gasification efficiency (70-75%) of the gasifier, the efficiency of the
IC engine and the electrical conversion efficiency of the generator that is coupled to the engine (90%). Determining the correct gas/air mixture is difficult as the composition changes over a run and it could be drastic too. To mitigate this possibility, different kinds of valves are used and these range from simple hand operated valves to fully automatic
ones to control the gas-air mixture. The former is common for rural power applications
and skilled operators are needed as a result.
Experience and results of rural power systems operated with gasifier/IC engine
combination are presented in [17][18][22][23] and the systems that were studied in the
field surveys also used this combination (Chapter 3).
31
Figure 2.5 - A biomass fired steam turbine system [18].
2.2.2 Electricity generation through combustion and steam turbines
Thermochemical conversion through combustion and steam turbines can also be used for electricity generation. In these systems the biomass is directly combusted in boilers producing pressurised stem, which is expanded in a turbine that runs a generator [18].
Steam-Rankine cycle is used in the modern biomass power plants based on boilers/steam turbines. These systems that are being used may operate in either power generation only mode or combine power and heat (CHP) mode. In case of CHP mode some steam is extracted from the turbine for heating use before it is eventually returned to the boiler
[18]. These systems become more cost effective when operated in CHP mode. The capital cost requirements make this a choice for biomass power or CHP systems with capacities of a few hundred kilowatts to a few megawatts.
32
2.3 Summary
There are many varieties of biomass resources that can be converted into useful energy and the feasibility of using them depends on their chemical and physical features as well as the costs of procuring them. A comprehensive assessment of these resources is important to plan effective and sustainable biomass power usage in a particular country or region.
The technologies that are used to covert biomass energy must be chosen considering the properties of the potential biomass resource and the capacity of the system. Biomass gasification based systems with IC engines were found to be an ideal choice for low power rural electrification due to economics and technological considerations.
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Chapter Three: Case Studies
Two field studies on small scale biomass energy systems in Sri Lanka are presented in this chapter. One system is a rural village power system in a village in Uva province and the other is a biomass energy plant in a coconut plantation in North-Western province.
These sites were visited in January 2006 and the observations made during that visit were used to develop these case studies. The author was also involved in the planning stage of the village power system in 2004.
The planners, owners and the energy end users of the two biomass energy systems were interviewed in the field survey. Information regarding the system implementation and adaptation were obtained through these interviews. Energy usage patterns and daily operational process were observed. Data on biomass production and supply as well as land use and sharing patterns were obtained in the field survey. Details of the systems, operations and problems encountered are presented in this chapter.
3.1 Case study I - Endagalayaya village biomass power system
Endagalayaya is an isolated village in the Uva province of Sri Lanka, about 300km away from the commercial capital city, Colombo and about 100km from the southern coast.
The total area of the village is about 800 ha. The total population is about 200, residing in about 50 households. Some of them permanently live in the village while others just have their crop lands in the area. The inhabitants are mainly paddy, vegetable and dairy
34 farmers. The village is about 10km away from the nearest main road and is in the buffer zone of the Udawalawa National Park, a major wildlife protected area. Extending the utility grid is not realistic due to the prohibitive cost as well as the capacity shortage in the national grid. Therefore an independent power generation plant was the only way of providing electricity to the village at least in the short term.
The villagers had relied on kerosene lamps for home lighting until a solid-state lighting system was provided by the “Light Up The World Foundation (LUTW)” in June 2002. A survey done by LUTW found that the villagers were spending a significant amount of their monthly earnings on poor quality kerosene lighting [39]. A lighting cooperative society was formed in the village in order to maintain and operate the solid-state lighting system by the name of “Endagalayaya United Solar Energy Preservation Society”. With the financial and technical assistance from a group of concerned group of engineers led by Mr. Lalith Seneviratne of the Flowing Currents Pvt. Ltd., the village acquired a 3.5kW biomass power system in the fall of 2004 and the system was commissioned in October
2004. In addition to providing energy for the villagers in Endagalayaya, one of the prime objectives of this project was the proof of the technical feasibility of using this technology for rural electrification.
3.1.1 The power system
The system consists of a downdraft fixed bed gasifier (Model WBG-10) manufactured by
Ankur Scientific Energy Technologies Pvt. Ltd in India. The prime mover is a single
35 cylinder gasoline engine modified to operate in 100% producer gas mode and it powers a synchronous generator (Figure 3.2). The gas cleaning and cooling are done through a
Venturi scrubber with water re-circulation and a series of filters. The system installation was done by Lanka Transformers Pvt. Ltd., which is one of the pioneers of promoting biomass energy in Sri Lanka. Biomass feeding is done manually and there are two operators, each working a 6.5 hour shift, with the system operating from 6pm to 7am.
The rated capacity of the system is 3.5kW and typical operating capacity is about 2-3 kW.
C3.2 Bc12. Legend C2.3
PS – Biomass Power Station C3.3 4 mm2. cable Bc11 Bc9
2.5 mm2 cable C2 Bc10 C3 1.5 mm2 cable C1 BJ3 1.0 mm2 cable Bcw.1 Bc12. C2.2 BJ2 House Bcw Bc8 Street Lamp Bc7 C2.1 C1a Gray sections and houses are the B2. Bc6 planned future expansions. Bw B1 BJ1 D2 Bc3. PS B2 D1 Bc3 Bc3.2 D4. Bc4 D3 A1 A2. A2. A2 A2.3 D3.1 Bc3.3 D4 A3 A2. Bc5 A4 A2. A1a A5 AJ1 D5 A2. A2a2 A4. AJ2
A2. D6. A2.8 D6 A2.4 A2.7 Revision: R8 A2a A2a. D6. Date: 02 February 2006 A2. Total No. of Houses (incl. planned): 60
No. of Houses up to which grid laid: 48
No. of Houses connected and served: 31
Figure 3.1 - Map of the Endagalayaya electricity distribution grid (not to scale). By courtesy of Mr. Lalth Seneviratne
36
The power plant is located in a central location in the village and the land for the generator station was donated by Mr. S. Dharmasena, who is a founding member of the lighting cooperative society. The energy is distributed through underground cables to the households and there are four main cable sections each of about 1km long. Junction boxes are placed along the main cable lines, each serving a cluster of houses (Figure 3.1).
An underground cable system was used due to the presence of elephants in the area as the village borders a wildlife protected area. Presently there are 28 houses that are connected to the system and in addition there is a network of street lights that illuminate most of the pathways of the village.
The main fuel wood used is Gliricidia sepium and the system consumes about 80kg of wood per day. Each household pays a monthly tariff of Rs100 (US$1) and supplies 80kg of dried and pelleted fuel wood. At present consumption levels, this wood supply meets the fuel requirement to operate the plant.
3.1.2 Biomass supply
As mentioned above, the power system uses only Gliricidia wood pellets as its fuel. The villagers grow Gliricidia trees in home gardens and crops and are used mainly as fences
(Figure 3.4). The tree is fast growing and also used as a support and shade for crops such as pepper, beans, chilli, gourds etc. which are grown as commercial agricultural crops.
The leaves are usually used as a cattle food. At the time of the site visit one of the farmers was putting up a dedicated Gliricidia crop of about 0.5ha and sharing the same land with
37 pepper vines. The mature branches of the trees are harvested in 5-8 month cycles and the main stump is kept intact for re-growth. The branches are then chopped to make wood pellets of about 1.5-2.5 inches long Figure 3.5 (a). They are then sun dried for about 2-3 days Figure 3.5(b).
The leaves and soft woody parts are left in the ground beneath the trees, thus providing fertility for the trees. Each household provides its monthly wood quota (80kg) according to a schedule that was agreed at the general meeting of the cooperative society. A representative of the cooperative collects the wood at the power station. Only manual labour is used in harvesting, wood preparation and transporting stages. At Endagalayaya, it was observed that villagers usually harvest about 3-4 trees to produce 80kg of wood and an average person can prepare about 25kg of wood pellets per hour.
Because the 80kg of wood is an obligation for the households in return for the electricity, the households do not get any additional income through fuel wood supply. However there are some farmers who supply wood for the other households. If a particular family could not prepare its monthly wood requirement due to the wood shortage or lack of time they can buy wood pellets from these suppliers and the current rate is about LKRs 3/kg
(US$ 0.03/kg).
38
Figure 3.2 - The gasifier and generator system at Endagalayaya power system
Figure 3.3 - Biomass power station in Endagalayaya
39
The initial capital cost for putting up the power generation system and the distribution grid was about US$8000 [40]. A substantial portion of this, including the full cost of equipment and installation cost was provided by an independent donor group. The villages were charged a connecting fee of US$5 per household and this was done mainly to create the sense of ownership. The labour that was needed for power house construction and grid installation was provided by the villagers as part of their contribution.
3.1.3 Capital and operating costs of the system
The two operators are paid LKRs 4,500 (US$45) each per month. Presently the operator salary is paid by the Flowing Currents Pvt. Ltd. which is a not for profit company that focuses on promoting biomass based electricity generation in rural villages in Sri Lanka.
The other monthly and annual maintenance includes servicing of equipments, lubricants, kerosene (about 5 l/month) and gasoline (2 l/month) purchase. Including all of these the monthly maintenance and operating costs excluding the operator salary is about US$25.
This is sourced by the LKRs100 monthly fee paid by the households. Major maintenance expenses are jointly borne by the cooperative society and Flowing Currents Pvt. Ltd.
40
Figure 3.4 - Gliricidia trees that are grown as a fence
(a) (b)
Figure 3.5 - Wood preparation process; (a) chopping the branches in to pellets; (b) sun drying the pellets.
41
3.1.4 System ownership and management
The system is formally owned and managed by the Endagalayaya United Solar Energy
Preservation Society. The society has elected officials and a general committee who are appointed annually by the members. The society activities are governed by its constitution and a set of by-laws. The general committee manages the energy system with the support of the Flowing Currents Pvt. Ltd and a few other local experts. The activities of the society include; collection of fuel wood and tariffs, maintenance and repair of the equipment, maintaining the transaction records, maintaining the street light network and planning any future expansions. In addition to managing and operating the power system, the cooperative also focuses on village infrastructure developments that are collectively important. The regular meetings of the cooperative society are held at the community hall. These meetings have become a forum for the community to meet and discuss the things that are important to the community as a whole and also a place to resolve any disputes that are related to the power system operation.
3.1.5 Observations made at Endagalayaya
Since the commissioning of the system the energy supply has been reliable and steady.
Of the 40 or so households only 28 have been connected to the energy system. The rest of the households did not connect either because they could not afford the connection fee and the monthly tariff or because they do not permanently live in the village. The
42 governance by the cooperative society is very successful and community participation for managing and maintaining the system is widely observed.
In the households the electricity is used primarily for lighting. The other most common usage is for entertainment purposes such as TVs and radios. In addition to those, some use electricity for cellular phone charging and clothes ironing. The safety and convenience of the electrical lighting is a boost for the education of the village children as it allows them to study at night. The women find more flexible working hours for their day to day routine activities such as cooking and cleaning. Some women found that the electrical power system made their extra income generating activities, such as making palm mats and dress making, much more productive. Though direct commercial usage of electricity was not observed, availability of electric lighting has increased the time that can be spent on those activities. The street light network was found to be helpful in detering crop raiding wild elephants and also for the safety of night time walking. The wood fuel supply and tariff payment has been steady and reliable.
3.1.6 Problems and challenges faced by the power system
The main challenge faced by the power system is that it is still not self sustaining and it relies on the support of outside organizations. The reason for this is the income earned through the tariff is not sufficient to cover the maintenance and operating costs of the system due to the small number of electricity subscribers. With current energy demand
43 and also with some demand side management, the plant can easily serve another 15 or so households.
The cooperative is not buying any fuel wood from the villagers as the mandatory 80kg fuel wood amount from each house hold is sufficient to provide the demand so far.
Therefore in the villagers’ point of view there is no direct financial gain from the power system to an individual household though the availability of electrical energy has escalated their quality of life. If there are businesses or services that purchase power from the system, then households can get an extra income by providing the additional required fuel wood to the power system.
Because the villagers have relied only on the home gardens and fences around crop lands as the wood source, some are facing fuel wood shortages, particularly in the dry season.
As a result some farmers, as well as the cooperative are now planning to grow dedicated
Gliricidia plantations. Wood pellets that did not meet the specified size and moisture content have also been a problem for the power system, thus the cooperative has appointed formal wood collectors who examine the pellets before accepting them.
3.1.7 Present status of biomass energy usage in Endagalayaya and nearby area
Despite the minor challenges, the Endagalayaya power system has been running steadily and the success of this system has proven the feasibility of the technology, and also the
44 management practice adopted. Motivated by the success of this system, Mahakiula, an adjacent village to Endagalayaya recently acquired a 10kW biomass plant.
The Flowing Currents Pvt. Ltd. has started gasifier manufacturing in the same area and therefore it will create more local employments. Furthermore, it will reduce the capital investment needed to establish village biomass power systems.
After the government of Sri Lanka declared Gliricidia as a commercial plantation crop, some of the Endagalayaya farmers are now planning to grow it in large scale in order to tap in to the growing fuel wood market. This can become a major additional income source for them as more biomass plants emerge in the region.
3.2 Case study II – Biomass power plant in “Kohombe” coconut plantation
The Kohombe coconut plantation is in an area called Kakkapalliya, a small rural area in the North-Western province of Sri Lanka. The nearest commercial centers are the busy coastal towns of Negambo and Chillaw. Despite being only few kilometres away from a major coastal highway, the area is not connected to the utility grid. The plantation is owned by Dr. Ray Wijewardene, who is one of the most widely acclaimed advocates of biomass energy usage in Sri Lanka. A 3.5kW biomass electrical energy system was installed in Kohombe in May 2003. This system is a classic example of land sharing with commercial agricultural crops for bioenergy crops and also the use of byproducts that are generated by biomass energy systems.
45
3.2.1 The power system and the energy usage
This system also uses a downdraft gasifier manufactured by Ankur Scientific Energy
Technologies Pvt. Ltd. in India to convert solid Gliricidia pellets into producer gas. The gaseous fuel is then combusted in a single cylinder, internal combustion engine to produce electricity (Error! Reference source not found.).
The system operates only 4 hours per day and daily wood consumption is about 20kg.
The fuel wood is supplied by the Gliricidia energy crops that are grown in the plantation itself. Details about the energy crop are discussed in section 3.3.2. The electricity produced is mainly used to pump water into an overhead tank that provides drip irrigation to the coconut trees in the section 1B of the plantation, thus preventing the premature fall of young nuts and increasing the yield. In addition to that the system provides electricity to 8 plantation employee families living in the plantation area. The energy is also used for an electric wood cutter which is used for preparing wood pellets. The system has run for more than 4000 hours since its commissioning in 2003.
The capital cost of the equipments was about US$5000. In addition to that the initial cost of energy crop plantation establishment was about US$150 which was mainly the labour cost involved in preparation and planting of Gliricidia trees. The total fuel cost is about
US$0.04/kWh.
46
Figure 3.6 - The gasifier and the generator system at "Kohombe" estate
Figure 3.7 - "Kohombe" biomass power station
47
3.2.2 Biomass energy crops in Kohombe estate
Gliricidia trees are grown in an area of about 10 acres in rows between the coconut tree rows (Figure 3.8). The plantation mix is such that there are about 40-50 coconut palms per acre and about 8-10 Gliricidia trees per palm. Therefore the land is effectively utilized by sharing it with the energy crop and the coconut, which is one of the main export agricultural products in Sri Lanka.
Other commercial crops such as pepper are also grown in the same space. Hence, the nutritional balance of the soil is also maintained by avoiding crop monocultures. Because
Gliricidia is a nitrogen fixing tree species, it increases the nutritional content of the soil, thus reducing the fertilizer requirement of the coconut plantation and therefore the production cost. Harvesting is done using manual labour and that is one of the assigned duties of the plantation workers. As mentioned above an electrical wood cutter is used for wood preparation and the labour cost for wood preparation is about US$0.02/kg.
3.2.3 Byproducts from the Gliricidia energy crop
An important observation made at Kohombe was the use of Gliricidia foliage as an alternative fertilizer for coconut plantation. Coconut in general is crop which has high fertilizer requirements mainly due to the nutrient removal from the soil due to the harvesting of nuts [41]. Moreover young coconut palms need a substantial amount of nitrogen fertilizer as it is important for leaf development and early flowering. Therefore
48 fertilizer cost is a substantial portion (20-40% depending on the age of the plantation) of plantation management expenditures [30]. One of the main fertilizers that need to be applied to the trees year round is urea, which provides the nitrogen requirements for the palms to ensure high yields and healthy coconut palms [30][34][41]. Urea requirement of the coconut palms is about 0.7-1 kg/palm/year depending on the age of the tree and also the annual yield [30][41]. Research done by the Coconut Research Institute of Sri Lanka has revealed that 35kg of Gliricidia foliage (50-60% moisture) contains the nitrogen equivalent to about 0.8kg of urea [14]. At Kohombe, the urea fertilizer has been completely replaced by Gliricidia foliage and each coconut palm is supplied with about
50kg of Gliricidia leaves per year instead of urea (Figure 3.9). This has saved about
US$10/acre/year of fertilizer cost which is a significant percentage of annual plantation cost.
Many other crops also use urea extensively and as it is mainly imported to Sri Lanka then large sums of foreign currency are spent on urea annually. The potential of Gliricidia leaves as a nitrogen fertilizer thus has been welcomed by the agricultural authorities of the country. The Coconut Cultivation Board of Sri Lanka currently provides an incentive of about US$30/acre to establish coconut and Gliricidia intercropping plantations considering the fertility value of the leaves and the energy value of the wood yield [42].
This incentive has been welcomed by many farmers including those who are at
Endagalayaya, described in section 3.1.
49
Figure 3.8 - Gliricidia trees grown in between coconut tree rows.
Figure 3.9 - Application of Gliricidia leaves as a nitrogen fertilizer to the coconut trees.
50
3.3 Summary and discussion
The two systems that were studied in the field survey demonstrated the feasibility of small scale biomass power systems to provide electrical energy for rural households as well as for rural industries. Adaptation of this technology by the rural village communities was observed. The management and governing practices adopted in the
Endagalayaya system is exemplary for similar kinds of implementations using any form of renewable energy technology. Furthermore, for biomass based power generation systems, mandatory requirement of such an organizational structure was observed at
Endagalayaya.
Sharing of land with other agricultural and societal activities was observed in both cases.
The feasibility of replicating such a land use practice must be investigated for biomass energy is a land intensive form of energy compared to other alternative sources. Effective use of byproducts from the biomass energy system was observed in the second case study and this shows the importance of proper selection of energy crop species.
One main challenge that was observed at Endagalayaya was the systems lack of self sustainability due to the low energy demand. A comprehensive study of the system economics under typical rural energy demands is needed for planning and implementing such biomass power systems that would be sustainable. Such an analysis has been made in this research work and the results are presented in Chapter 4.
51
Chapter Four: Economic Analysis of Village Scale Biomass Energy Systems
Starting from the 1970s many renewable energy projects have been implemented in the rural areas of developing countries with the financial and technical support from the international and local development assistance agencies. Many of these projects, though demonstrating the feasibility of appropriate technologies as a means of providing electricity for rural areas, did not achieve sustainability due to a lack of mechanisms for maintenance and on going operation [9][43]. In most of the cases the donor based approach provided the fixed capital assets but little attention was given for ensuring the availability of recurrent costs such as operating and maintenance costs [9][43].
Furthermore organizational structures were not developed in order to manage the power systems. Learning from that experience, recent attempts to provide energy services to the rural areas in the developing world took a market based approach with sustainable business models. These energy services may be operated by either local enterprises or community cooperatives [43][44]. A comprehensive understanding of the system economics over the life cycle is of paramount importance in order to plan and implement such a sustainable energy service.
Biomass energy systems compared to other renewable energy sources such as photovoltaic or wind, are more complex in operation and the operating costs are significantly higher. They are more analogous to conventional fuel based power systems in that regard [45]. Therefore a detailed economic analysis, giving attention to dependencies and sensitivities to the variations of the relevant parameters is needed when
52 planning and designing a village power system. Such an analysis will provide a clear overview about the timely manner of the finance requirements, revenues that should be generated by the system in order to achieve sustainable operation, and the overall financial feasibility. Comprehensive economic analysis of a village scale biomass power system under various operating conditions is performed in this chapter. Details of the models used and the results obtained are presented. An overview and recommendations for a sustainable biomass energy system are presented in chapter 6.
4.1 Methods and models
Life cycle costing (LCC) method was used to analyse the economic feasibility of an off- grid village scale power system based on woody biomass gasification and internal combustion engine conversion. LCC was performed under different power demands to investigate the system economics. Levelized cost of energy (COE) was calculated under the assumed conditions to compare the different options and a diesel powered generator was used as the baseline to compare the biomass power system with. This was chosen as the baseline, because it is the most likely conventional fuel based option to provide electrical energy to an off grid village. The diesel internal combustion (IC) engine/generator option is a proven technology and there are many such systems being used throughout the world as an electrical power generation source for remote locations
[46][47]. Grid extension was not considered because in many developing countries that is not a viable option in the foreseeable future due to the prohibitive cost. Furthermore, kerosene lighting, the source that is being used by many rural households is not
53 considered as the baseline for the primary analysis because the quality of service provided is not comparable with the full range energy service given by biomass power systems.
An accurate estimation of the factors associated with the operation of the power system such as the total energy that is available for the users, annual fuel requirement and operating hours are very important in order to obtain good results from the economic analysis. This is mainly because the operational cost of a biomass power system is substantial. Therefore a time series simulation over a one year period was used with a
1hour time step to calculate those parameters. The power system was modelled using simplified mathematical models in order to perform the simulation. Details of the models are presented in section 4.1.1. Three load demand profiles were mainly used for the simulation and these were chosen in a way that they would represent the typical power demands of a village community. Using these load profiles, hourly power demand was estimated and then the generator operating capacity, hourly fuel requirement and system efficiency were calculated for a period of one year. Operating costs were then calculated using these results for the LCC. Details of the economic analysis methodology used are presented in section 4.1.5. The chapter starts with a description of the models that were used to simulate the physical system in order to estimate the resource requirements and operating performance.
54
4.1.1 Component models
4.1.1.1 Wood gasifier
The gasifier is considered as a black box that converts the solid biomass into producer gas at a particular efficiency and rate. The efficiency at which the conversion takes place can be expressed on cold or hot basis [35]. The cold basis efficiency or simply the cold gasification efficiency is the ratio between the chemical energy content in the producer gas and the energy content in biomass. The hot gasification efficiency is the ratio between the chemical and heat energy content of producer gas and the energy content of the biomass. The former is used for the calculations because the energy form that is of interest for the IC engine conversion is only the chemical energy of the producer gas. The producer gas generation rate can be calculated using the basic gasification equation 4.1 which was derived using fundamental definitions.
η gas H wmw mgas = (4.1) H gas
Where mgas and mw are producer gas generation rate and wood consumption rate (in kg/h)
respectively. ηgas is the cold gasification efficiency of the gasifier, it depends on the
gasifier technology used and is usually in the range of 70-80%. Hw and Hgas are the lower
heating values (in MJ/kg) of wood and producer gas respectively. The lower heating
value (LHV) is the net energy released by oxidization of the fuel excluding the heat
55 required for vaporization of the water in the fuel and the water produced from hydrogen combustion during the conversion process [35]. Typical values for Hw and Hgas are
13.5MJ/kg and 5.7MJ/kg respectively [14][48]. LHV of the producer gas is largely depends on the composition of the producer gas. For example high nitrogen or water vapour content will reduce the LHV of the gas mixture.
4.1.1.2 Internal combustion engine and generator system
IC engines are used in both the biomass power system and the diesel baseline case. To calculate the fuel requirement and operating efficiency under different load conditions a model proposed in [45] is used. In this model the fuel consumption rate is taken as a linier function of the operating power. Using that relationship equation 4.2 was used to calculate the fuel consumption rate, F (measured in kg/h). The IC engine and the electrical generator are considered as a single module for this simulation.
F = F0 Pe + F1P (4.2)
Where Pe and P are the generator size and operating power (in kW) respectively. F0 is the interception of the fuel (in kg/h/kW) curve which represents the no load fuel consumption of the generator. F1 is the slope of the fuel curve (in kg/h/kW) [45][49]. Values of F0 and
F1 can be calculated using manufacturer’s data or obtained from direct measurement. By
combining equations 4.1 and 4.2 the hourly wood consumption rate can be calculated as
expressed in equation 4.3. Furthermore the biomass system efficiency, ηb can be
56 calculated using equation 4.4. The efficiency is not directly needed for the economic analysis but is useful in assessing the overall system performance.
1 ⎛ H ⎞ ⎜ gas ⎟ mw = ⎜ ⎟()Fb0 Pe + Fb1P (4.3) η gas ⎝ H w ⎠
3.6P ηb = (4.4) mw H w
By examining the equations 4.3 and 4.4 it can be seen that low power operation yields low system efficiencies. The fuel consumption curve and the efficiency curve for a 5kW biomass power system are shown in Figure 4.1.
The fuel consumption rate of the diesel power system can be calculated directly using equation 4.2. It may be divided by the density of diesel, 0.82 kg/l to get the fuel consumption rate in l/h, as the amount of diesel used is usually measured in litres.
4.1.2 Load profiles
The hourly load profile for a period of one year was synthesized statistically using the average daily load demand and the derivation steps are detailed in this section. The load vector Lday (1 × 24) was created from the average hourly loads. Lday was then replicated
57
365 times to create the yearly load profile vector Lyear (1×8760) and this process is expressed in equation 4.5.
12 15%
Efficiency
8 10%
No load Efficiency, % fuel consumption Wood
Wood consumption, kg/h consumption, Wood consumption 4 5%
0 0 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Power, kW
Figure 4.1 - Wood consumption rate and generation efficiency of a 5kW biomass gasification based power system
To account for the random variations of the hourly and daily loads, random noise was added to Lyear and also corrected for the power losses due to power distribution. The hourly load demand profile of the power system for one year, L was then calculated using equation 4.6.
58
Lyear = [Lday Lday ……… Lday]1×8760 (4.5)
L = Lyear (1+nh+nd )(1+δl) (4.6)
Where nh and nd are random noise vectors with zero mean. The standard deviation of nh and nd are σh and σd respectively and they represent the hourly and daily random variation of the loads. δl is the percentage power distribution loss.
A similar approach is used to create load profiles by using the micro power optimization and simulation software tool Homer® [49]. Changes can be made to this process to include the seasonal or weekly variations of the loads. In that case the equation 4.5 should be modified to accommodate those seasonal or weekly data. This statistical method was used to create the load profiles because usually the measured load demands are not available in the planning stage of village power systems. However if measured data is available those data can be directly used to create L. Such an approach can be adopted to perform a post assessment of the power system.
4.1.3 Generator operating capacity calculation
In order to calculate the hourly generator operating capacity, P (kW) two factors have to be considered, which are the power demand and the minimum operating capacity of the
IC engine. Most constant speed IC engines typically do not operate bellow a specified capacity for prolonged periods in order to avoid the carbon build up in the pistons and the
59 piston rings due to the improper fuel air mixture at lower loads [45][47]. The minimum capacity is typically about 25-30% of the rated capacity of the engine. Keeping this in mind the engine operating capacity is calculated as follows.
When the demand is lower than the engine minimum capacity, the generator operates at its minimum capacity and any excess power should be routed to a secondary load which could be a useful or dumped load. When the load is higher than the generator maximum capacity, then the system is operating at its maximum capacity. There will be unmet energy demand in that case and this should be avoided by proper planning and design of the power system. In all other cases the generator operates at the same level as the load.
When the power demand is zero the engine shuts down. The fuel requirement for each hour is then calculated using equations 4.2 through 4.4. Our calculation procedure for one particular hour of the biomass energy system is shown in Figure 4.2 and the same procedure is repeated for all 8760 hours. A similar process can be used for the diesel system.
4.1.4 Total energy and fuel calculation
Total wood requirement, Mw (kg/y) was calculated by summing the hourly wood consumption, mw over the period (1 year) as expressed in equation 4.7.
8760 M w = ∑ mwi (4.7) i=1
60
Figure 4.2 - Generator operating capacity calculation procedure for a single hour.
Similarly the total electrical energy generated by the generator, Egen (kWh/y) can be calculated by summing the hourly generator operating capacity, P(kW) over the period.
However from Egen only the energy available to the user, E (kWh/y) will generate revenues to the power system. Therefore to calculate E, the transmission loss and the excess energy generated, Eex due to operating the generator at the minimum capacity in
61 the hours with low power demand, must be subtracted from Egen. Equations 4.8 and 4.9 were derived to calculate Egen and E respectively.
8760 Egen = ∑ Pi Δt (4.8) i=1
th Where Pi is the generator operating capacity in i hour and Δt = 1h.
E = (Egen − Eex )(1− δ l ) (4.9)
4.1.5 Economic analysis
In the economic analysis the present value of the lifecycle cost, LCCPV and the levelized cost of energy, COE were calculated. LCCPV is the aggregate of the present values of the cash flow of the power system over the period of interest. A simplified cash and energy flow of a power system is shown in Figure 4.3. LCCPV can be calculated using equation
4.10 [50][51].
⎡ N ⎤ LCC PV = CC + ⎢∑()FCi + OSi + MCi + CI i + RCi di ⎥ − SV ⋅ d N ⎣ i=1 ⎦ (4.10) 1 di = ()1+ r i
62
Figure 4.3 - Simplified cash and energy flow over N number of years
Where CC is the capital cost and FC, OS, MC, CI, and RC are the fuel cost, operator salary, maintenance cost, interest paid on loans, and replacement cost respectively for the ith year. N is the number of years that the economic analysis is performed and r is the discounting rate used. SV is the salvage or the residue value of the power system at the end of period of interest.
To compute the COE it is necessary to calculate the annualized cost, AC ($/y) of the power system as the LCCPV calculation was performed using an annual interval [51]. AC is calculated by multiplying LCCPV by the capital recovery factor, CRF(r,N) for the period of interest and the discounting rate used (Equation 4.11) [50][51].
63
AC = LCC PV ⋅CRF(r, N) (4.11) r()1+ r N where; CRF(r, N) = ()1+ r N −1
The COE is then calculated using equation 4.12 [51]. COE is measured in US¢/kWh throughout this analysis.
AC COE = (4.12) E
Where E (kWh) is the total energy available to the end user.
4.2 Analysis and results
The models and methods described in section 4.1 were used to develop Matlab® m-file codes. The codes were then used to perform economic analysis of a biomass power system, providing electrical energy to a 50 house off-grid village. Three load profiles were considered for the analysis. The load profiles were estimated considering the typical rural household electricity consumption data and practices obtained from published literature, field surveys (Chapter 3) and also from the author’s experience with rural electrification projects [44]. The cost data were obtained from manufacturers data and literature [14][33] [52] and the initial capital was assumed to be obtained from a line of credit and incentives. Three cases were considered for the incentives, namely no
64 incentives, 50% incentive on capital cost and 100% incentive on capital cost. The incentives are assumed to be provided by the government or development assistance agencies. The third case is analogous to a case where the whole system is donated to a village. Furthermore, the interest rate on loans was assumed to be 6% for all the cases considered. It was considered that the system is owned by a community cooperative or a local enterprise and the prime motive is to provide energy services to the village rather than profit maximization. An annual discounting rate of 10% was used for LCC and COE calculation and the analysis was performed for a 15 year period. Unless otherwise specified the costs and parameters listed in Table 4.1 are used for all the calculations.
Detailed calculations with sensitivity analysis were made with the Load profile I. Load profile II was analysed to investigate the effect of power demand on the COE.
Contribution from various expenses on COE was analysed for both profiles.
4.2.1 Analysis for load profile I
Load profile I represents a case where the electricity is used generally for lighting and entertainment purposes such as TV and radio. This is the most common form of renewable energy usage in the rural areas of the developing countries [9]. In addition to the household loads a street light network was included as it was found to be a need in rural village settings. For lighting, both in houses and streets it was assumed that compact fluorescent lamps (CFL) are used due to their high efficiency. Mean household load profile was assumed to be the same for all the houses. This however is not the case in actual power systems, particularly with appliances such as TVs and radios. Hourly and
65 daily noise with standard deviations of 15% and 10% respectively were added because of that. Load profile generation steps are presented in Table 4.2.
Table 4.1 - Costs and other parameters for economic analysis
Item Notation Biomass system Diesel system Capital cost CC $9500 $7500 Gasifier $2000 - IC engine/generator $3000 $3000 Distribution grid $2500 $2500 Civil works $1500 $1500 Miscellaneous $500 $500
Fuel cost - wood FC $0.02/kg - Fuel cost - diesel FC - $0.65/l Operator salary OS $0.3/h $0.3/h Maintenance cost (2% of CC) MC $190/y $150/y Salvage value SV $2000 $1500 Engine operating lifea - 20000 h 20000 h Replacement cost RC $1500 $1000 Interest on loans - 6% 6% Annual discounting rate r 10% 10% Fuel curve intercept F0 0.8 kg/h/kW 0.08 kg/h/kW Fuel curve slope F1 2.4 kg/h/kW 0.21 kg/h/kW Cold gasification efficiency ηgas 70% - Fuel LHVs Hw, Hdiesel 13.5 MJ/kg 43.33 MJ/kg Hgas 5.7 MJ/kg Transmission loss δl 2% 2% Analysis period N 15 years 15 years a It was assumed that a modified diesel engine is used for power generation in the biomass power system and the engine life was assumed to be 20,000 hrs [53]. Regular maintenance including minor over hauls were also assumed to be included in the maintenance cost.
66
Table 4.2 - Load profile I Per Total Street Hour Domestic lighting loads TV Radio house household Total lights demand demand (kW) (kW) 15W 10W 10W 5W 50W 10W (W) (kW) 1 9 5.0 0.25 0.90 1.15 2 9 5.0 0.25 0.90 1.15 3 9 5.0 0.25 0.90 1.15 4 9 5.0 0.25 0.90 1.15 5 9 5.0 0.25 0.90 1.15 6 9 9 91/2 9 9 45.0 2.25 0.90 3.15 7 9 9 91/2 91/2 9 42.5 2.13 0.45 2.58 8 0.0 0.00 0.00 0.00 9 0.0 0.00 0.00 0.00 10 0.0 0.00 0.00 0.00 11 0.0 0.00 0.00 0.00 12 0.0 0.00 0.00 0.00 13 0.0 0.00 0.00 0.00 14 0.0 0.00 0.00 0.00 15 0.0 0.00 0.00 0.00 16 0.0 0.00 0.00 0.00 17 0.0 0.00 0.00 0.00 18 9 0.0 0.00 0.00 0.00 19 91/2 91/2 22.5 1.13 0.45 1.58 20 9 9 91/2 9 80.0 4.00 0.90 4.90 21 9 9 91/2 9 80.0 4.00 0.90 4.90 22 9 9 9 75.0 3.75 0.90 4.65 23 91/2 91/2 91/2 91/2 40.0 2.00 0.90 2.90 24 9 5.0 0.25 0.90 1.15
This average power demand profile (Load profile I) is shown in Figure 4.4 (a). LCCPV and COE were calculated for both biomass and diesel system providing energy services for this demand profile for three cases with different incentive levels (0%, 50%, and
100%).
67
As described in section 4.1.2 the stochastic nature of the power demand due to the hourly and daily variations is statistically handled and the power demand for 72 hour period (3 days) generated by the analysis model is shown in Figure 4.5(a). Generator operating capacity and the excess power generated for the same period is shown in Figure 4.5(b).
6
5
4
3
Load, kW 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
(a)
6
5
4
3
Load, kW 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 (b)
Figure 4.4. - (a) Load profile I. (b) Load profile II.
68
6 Hourly power demand
5
4
3 kW
2
1
0 10 20 30 40 50 60 70 Hour
(a)
6 Excess power Generator operating 5 capacity
4
3 kW
2
1
0 10 20 30 40 50 60 70 Hour
(b)
Figure 4.5 - (a) Hourly power demand; (b) Generator operating capacity and excess power generated for 72 hours for the load profile I.
Results obtained from this analysis are listed in Table 4.3. It can be seen that the COE of the biomass system is much less than that of the diesel system under the assumed conditions. A sensitivity analysis was performed to investigate the COE under different wood and diesel price and the results are shown in Figure 4.6. From this analysis it can be seen that the at a diesel price of US$0.65/l the COE of the diesel system is less than the biomass system only when the wood price is more than US$0.1/kg.
69
Table 4.3 – Economic analysis results for the Load profile I Case 1 Case 2 Case 3 0% incentive 50% incentive 100% incentive on CC on CC on CC Biomass Diesel Biomass Diesel Biomass Diesel
LCCPV, US$ 30,441 46,579 24,277 41,666 18,124 36,819 AC, US$/y 4,002 6,124 3,192 5,478 2,383 4,841 Total Energy, kWh/y 11,218 11,218 11,218 11,218 11,218 11,218 COE US¢/kWh 35.7 54.6 28.4 48.8 21.2 43.2
1.5
Biomass system isBiomass prefered system is preferred
1
0.65 Diesel price, US$/l
0.5 Diesel system is Dieselpreferred system is prefered
0 0 0.02 0.05 0.1 0.15 Wood price, US$/kg
Figure 4.6 - COE sensitivity analysis against wood and diesel price.
70
Figure 4.7 shows the composition of the COE for the 0% incentive case. It can be seen that the operating costs account for a substantial part of the COE, while the operator salary is the highest contributor. Therefore it is not economical to run the plant at lower loads for longer periods as the operator salary is a fixed amount per hour irrespective of the generator running capacity. Furthermore the contribution from the fixed costs such as capital investment on COE will be higher when the electricity demand is low.
Replacement cost, 7.23%
Maintenance (Capital cost - cost, 4.75% salvage value), 29.64%
Operator salary, 35.57% Loan interest, 9.23%
Fuel cost, 13.58%
Figure 4.7 - Contribution from various capital and operating expenses to the COE of biomass energy plant (0% incentive case for the load profile I).
Though the COE of the biomass system is significantly lower than the baseline case, it is still higher than the COE of the utility grids. The household electricity price offered by the utilities is usually in the range of US¢ 9-25 per kWh [54]. For the system considered the COE falls within this range only in the 100% incentive case. The main reason for that
71 is the relatively lower energy demand of the village scale isolated power plants. However it should be noted that the utility grids also get government incentives for both capital and fuel costs. Furthermore the expenditure on wood fuel (US¢5/kWh – 13.6% of COE) stays in the local or regional economy unlike in the case of fossil energy based electricity generation where the fuel is usually imported. Therefore if the wood fuel is supplied by the energy users of the village, the effective price they would pay for electricity is
US¢5/kWh less than the calculated COE in all the cases.
4.2.2 Analysis for load profile II
Load profile II represents a typical utility like power demand where the electrical energy is used throughout the day for domestic as well as for commercial purposes. This profile is shown in Figure 4.4 (b). In this case it was assumed that in the day time electricity is used for income generating activities such as grinding mills, irrigation, sewing machines, refrigeration etc. The power demand and the generator operating capacity for a 72 hours period are shown in Figure 4.8 (a) and (b). Economic analysis results for this load profile are listed in Table 4.4.
With this power demand profile, in all three cases with different incentive levels, the
COE is less than that of the respective cases with the load profile I, where the generator is used only in the night. Furthermore the COE is within the range of the commercial utility electricity price in all the cases.
72
7
6
5
4
3 Load, kW 2
1
0 10 20 30 40 50 60 70 (a)
6
5
4
3
2
1 Operating capacity, kW
0 10 20 30 40 50 60 70 Hour
(b)
Figure 4.8 - (a) Hourly power demand; (b) Generator operating capacity; for 72 hours for the load profile II.
Table 4.4 - Economic analysis results for the Load profile II Case 1 Case 2 Case 3 0% incentive 50% incentive 100% incentive on CC on CC on CC Biomass Diesel Biomass Diesel Biomass Diesel
LCCPV, US$ 47,098 83,200 38,536 75,826 32,439 71,302 AC, US$/y 6,192 10,939 5,067 9,969 4,265 9,74 Total Energy, kWh/y 25,100 25,100 25,100 25,100 25,100 25,100 COE US¢/kWh 24.7 43.6 20.2 39.7 17.0 37.3
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(Capital - Replacement, salvage 11.17% value), Maintenance, 19.15% 3.07%
Loan interest, 5.97%
Operator Fuel, 18.20% salary, 42.44%
Figure 4.9 - Contribution from various capital and operating expenditures to the COE of biomass energy plant (0% incentive case for the load profile II).
Figure 4.9 shows the contribution from different expenditures to the COE and it can be seen that as in the case of the load profile I, the main contribution is from the operator salary. However due to the higher energy production the contribution from the fixed capital and operating costs are lower. For example for the load profile I, about 51% of the
COE is due to the fixed costs while for the load profile II only 39% is contributed by them. The COE for the 0% incentive case is 31% lower compared to the same case with the load profile I.
It can be concluded that from this analysis that higher power demand yields lower COE and therefore it is more affordable to the users. Hence, for the sustainable operation of the system, it is important to create a wide market for electricity within the area served.
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Contrarily it can be assumed that commercial applications that were not possible in the rural area due to the lack of electricity will emerge after the introduction of the energy system, thus creating a market for electricity. If the power system is operated by a village cooperative, it can initiate village enterprises such as grinding mills or electrical water pumping services and purchase of electricity from the system, while charging for the services it supplies. For example in rural agricultural communities, the farmers use diesel or gasoline powered water pumps for irrigation. With escalating fuel prices this would be a substantial expenditure in the cropping season. The cooperative can start an electrical water pump renting scheme with power outlets near the crop fields or build water tanks and use electricity to pump water. The revenue generated from these can be used for operating and maintaining the power plant. Moreover when there are commercial power purchasers, the villagers can earn extra income too by selling more fuel wood to the energy plant. A win-win situation is thus created by linking a village biomass project with other rural development initiatives.
4.2.3 Biomass energy system with battery storage system
In the analysis in sections 4.2.1 and 4.2.2 it was seen that the operator salary is the most significant expenditure as far as the COE is concerned. For the time periods where the power demand is low, which is a common situation in rural village scale power systems, the contribution from that is even higher thus increasing the overall COE. Furthermore, if the cost of skilled labour that is needed for the system operation is higher then it will significantly increase the COE. For example for the analysis in sections 4.2.1 and 4.2.2
75 the cost of labour was taken as US$0.30/h and that is a typical amount for rural regions in developing countries. However with socioeconomic changes the expected wages could also rise. This will be compensated if there is a high energy demand. However for systems where the power demand is mainly coming from domestic usage, this could be a challenge. One possible solution is to integrate a battery bank and an inverter system to the biomass power plant. In that case the low power demands could be served by the stored energy through the inverter where unmanned operation is possible. The battery bank can be charged by running the generator at full capacity in the operating hours.
In this section a battery bank and an inverter were integrated into the biomass power system and the economic analysis was performed with the load profile I. Here it was assumed that the generator runs only when the power demand is more than 1.5kW and it is operated at full power (5kW) during those periods. The excess energy generated is stored in the battery bank. The battery bank/inverter system serves the power demands when the generator is not running. The battery bank was sized in a way that it is capable of storing energy for one full day while limiting the cell depth of discharge (DOD) to a maximum of 50%.
4.2.3.1 Battery bank and inverter sizing
With the load profile I the power demand is limited to only 13 hours per day from 6pm to
7am. From 11pm to 5am the mean power demand is less than 1.5kW. Therefore the generator would be operated from 6pm to 11pm and from 5am to 7am (7hours in total) at
76 full capacity (5kW). The energy requirement for the period where the generator is not operating is 7.1kWh with a peak power demand of 1.17kW. Equation 4.13 was derived to calculate the battery bank size, Bcap.
1000Ebat Bcap = (4.13) Vbat ⋅ DOD ⋅ηbat ⋅ηinv
Where Ebat, Vbat, DOD, ηbat, and ηinv are the energy to be delivered by the battery bank (in kWh), nominal voltage of the battery (V), allowed cell depth of discharge (%), the battery charging/discharging efficiency (%), and the inverter efficiency (%) respectively. Bcap is the battery bank capacity in Amp-hours (Ah). A 12V battery bank was considered and the typical value for ηbat and ηinv are 85% and 95% respectively. The battery bank capacity needed was found to be 1406Ah. The exact battery bank capacity size can vary according to the practical sizes of the batteries available in the local market. For this analysis it was assumed that the storage system was implemented using Trojan® L16, 6V 360Ah deep discharge batteries [52]. The battery bank can be implemented using 8 of those batteries by connecting four strings in parallel were each string consists of 2 batteries in series.
Then the voltage and capacity of the battery bank was 12V (6V × 2), 1440Ah (360Ah ×
4).
A 2kW inverter was chosen considering the possible surges in the power demand. It was assumed that the battery charge controlling is also done by the inverter. An example inverter system is Xantrex® DR2412, 12V, 2.4kW inverter [52]. An additional feature of
77 this system is that if there is a power demand which exceeds the capacity of the biomass generator, the battery bank can provide the capacity shortage. Hence it increases the overall quality of service.
4.2.3.2 Economic analysis of the proposed system
The costs and other parameters of the battery bank and inverter system assumed for the economic analysis are listed in Table 4.5. All other parameters used are identical to the ones listed in Table 4.1.
Table 4.5 - Costs and other parameters of the battery bank and the inverter system.
Item Notation Value Battery bank cost $1600 Inverter cost $1500 (Added to the capital cost) Salvage value of the inverter $500 and battery bank Maintenance cost of batteries $62/y and inverter (2% of initial cost) Battery life - 4 years Inverter lifea - 15 years Battery efficiency ηbat 85% Inverter efficiency ηinv 95% Battery replacement cost $1500 (engine) $1600 (battery) Generator operating period - 7h/day Battery bank capacity Bcap 1440 Ah Inverter capacity Pinv 2.4kW a The inverter life was assumed to be 10 years for continuous operation (24 hours) [55]. It was assumed that the inverter is operated only for 13 hours per day for this analysis.
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An hourly simulation for a period of 1year was made in order to perform the economic analysis. The load served, generator operating capacity and battery bank power flow are shown in Figure 4.10. The economic analysis results are listed in Table 4.6 in comparison with the “generator only” system.
6 Load Generator power Battery bank power flow 5
4
3
2 Power, kW
1
0
-1
-2 10 20 30 40 50 60 70 Hour
Figure 4.10 - Load, generator operating capacity and the battery bank power flow for the biomass generator and battery storage system combination for a 72 hours period.
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From the economic analysis results it can be seen that under the assumed conditions for the 0% incentive on CC case the COE of the generator and battery bank combination is marginally lower than that of the generator only case. However when there are incentives on CC the COE of battery bank option becomes much lower.
Table 4.6 - Economic analysis results for biomass generator and battery storage system combination with load profile I. Case 1 Case 2 Case 3 0% incentive 50% incentive 100% incentive on CC on CC on CC Generator Generator Generator Generator Generator Generator + battery only + battery only + battery only
LCCPV, US$ 30,175 30,441 22,011 24,277 13,848 18,124 AC, US$/y 3,967 4,002 2,894 3,192 1,821 2,383 Total Energy, kWh/y 11,400 11,400 11,400 11,400 11,400 11,400 COE US¢/kWh 34.8 35.1 25.4 28.0 16.0 20.9
Another observation made from the simulation was the reduction in the fuel wood requirement. The wood requirement for the generator only system is 27t/y while for the generator battery combined system, to serve the same power demand, the wood requirement is 24t/y. The reason for the difference is that the generator is running more efficiently in the latter case because it operates at full capacity.
A sensitivity analysis was performed to investigate the COE of the two options under different operator salary and battery cost and the results are shown in Figure 4.11. Figure
4.12 shows the COE variation in the operator salary range of US$ 0-1/h under current
80 battery price (US$ 1.14/Ah). From the results it can be seen that when the operator salary increases the biomass system with battery storage becomes the more favourable option.
For example as shown in Figure 4.12 for a particular battery cost ($1.14/Ah in this case) the COE of the generator only system is more sensitive to the increasing operator salary under the load demand considered. However if the battery cost is high the generator only system may be the favourable choice (Figure 4.11). One disadvantage of a battery bank is the lifetime of that is quite sensitive to the operating conditions such as temperature and battery maintenance. Therefore it should be properly installed and maintained in order to obtain the desired benefits.
1
0.9
0.8
Biomass generator + Biomassbattery bank generator + 0.7 battery bank
0.6
0.5
Operator salary US$/h salary Operator 0.4
0.3
Biomass 0.2 Biomassgenerator generator onlyonly
0.1
0 0.5 1 1.5 2 2.5 3 Battery price US$/Ah
Figure 4.11 - COE sensitivity analysis against battery cost and operator salary for the biomass generator and battery storage system combination with 0% incentive on CC.
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0.65 Biomass generator only 0.6 Biomass generator + battery bank 0.55
0.5
0.45
0.4
0.35 Cost of energy, US¢/kWh energy, of Cost 0.3
0.25
0.2 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Operator salary, US$/h
Figure 4.12 – COE variation with under different operator salary rate at current battery cost ($1.14/Ah)
4.3 Summary
A comprehensive economic analysis of small scale biomass power systems was performed in this chapter. A time series analysis method was used for the analysis.
Levelized cost of energy was used to compare different system options and two load profiles were used to investigate the effect of power demand on the cost of energy. A system with a battery storage system was analysed and a diesel powered electrical energy system used as the baseline system for comparison.
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From the analysis it was seen that the cost of energy is principally dependent upon the total energy demand. It was seen that with the load profile where the demand is higher the cost of energy is lower than the one with low power demand. Therefore it is important to create a market for electricity in addition to the typical domestic usage for the sustainable operation of the power system. In all cases the energy cost of the biomass power system was significantly lower than the diesel baseline system.
A system with battery storage and an inverter was considered as one possible solution for smaller systems with lower power demands. From the analysis it was seen that the feasibility of this system largely depends on the operator salary rate and the battery cost.
In all the systems considered, the availability of incentives makes the electricity more affordable for the rural users. This should be taken in to account by policy makers and rural development agencies that focuses on rural infrastructure development.
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Chapter Five: Greenhouse Gas Emission Reduction Potential
The potential global climate change caused by the greenhouse gas (GHG) emissions is becoming one of the major problems faced by the world in the third millennium. The increasing number of scientific evidences about the rising GHG concentration in the atmosphere due to human activities and its correlation with the climate changes, particularly with the rising trend of the global mean annual temperature, has created a global alert. Because the emissions from fossil fuel burning is the most significant source of GHGs, the climate change issue is strongly linked with the world energy usage and policies [56]. Therefore the mitigation attempts have created a rethinking of the world energy usage and renewable energy sources are receiving increased attention.
Biomass energy is widely accepted as a GHG free source of energy source[57-59]. The role of biomass energy systems with dedicated energy crops in GHG emission mitigation is two fold. It reduces GHG emission by avoiding fossil energy usage and also provides
GHG sinks through the dedicated energy plantation. This chapter analyses the GHG emission reduction potential of small scale biomass energy systems through energy and carbon budgeting. Results of that analysis are then used to assess the potential of using the GHG emission reductions generated as a means of financing biomass energy projects through the Clean Development Mechanisms (CDM), one of the three flexible mechanisms of the Kyoto protocol.
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5.1 Global warming, GHGs and the contribution from the electricity sector
Greenhouse effect and its impact on global mean temperature have been discussed in scientific literature for almost 100 years [56]. The natural green house effect in fact is what sets the earth’s mean temperature at a liveable level.
5.1.1 The natural greenhouse effect
The primary energy source of the earth is the sun. The inbound solar radiation is in the ultra violet and visible portion (wave length, λ: 0.2 – 0.4 μm) of the electromagnetic
(EM) spectrum. The earth’s atmosphere is relatively transparent to these shorter EM waves and converted to thermal energy when hits on the earth’s surface. This energy is reflected back to space at longer wavelengths (λ : 4 μm – 100 μm) which are typically in the visible portion and the infrared portion of the EM spectrum. The atmosphere is more opaque at these wavelengths mainly due to the GHGs that include water vapour (H2O), carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and ozone (O3). These GHGs absorb the outbound infrared radiation and then re-emit both down towards earth and outer space. Hence a significant portion of the outbound infrared radiation is trapped in the earth’s atmosphere warming its surface. This creates a temperature gradient ranging from an average mean surface temperature of 14°C to an average temperature of -19°C at a height of 5km, to -58°C at the top of the atmosphere (top of the troposphere, 16km at the equator and about 8km at the poles) [15][56][60]. This is the natural greenhouse effect and it is part of the energy balance of the earth which is illustrated in Figure 5.1.
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In an equilibrium state the net radiation at the top of the atmosphere is zero. A change in any of the major factors that create this equilibrium will create an imbalance which is called as “radiative forcing”. A radiative forcing will set the physical forces in motion and restore the equilibrium.
Figure 5.1 - The Earth’s annual and global mean energy balance [60].
5.1.2 Anthropogenic greenhouse gas emissions
Human activities have influenced the environment, to some degree, from the beginning time, but since the industrial revolution, the impact has grown to a much larger extent.
Human activities, particularly fossil energy burning for energy, have significantly
86 increased the GHG concentration in the atmosphere. High concentration of GHGs creates a positive radiative forcing as described in section 5.1.1. The response of the climate to this radiative forcing is complicated and non linear and analysis of that is beyond the scope of this thesis. Qualitatively, increased GHG levels in the atmosphere will trap more infrared radiation and reflect them towards the earth, leading to a rise of the global mean temperature [15]. This is what widely referred as the global warming. The major anthropogenic GHGs are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6) [61].
Of these CO2 is the one with the largest contribution to the global warming. Therefore the analysis in this thesis is more focused on CO2.
There are a number of evidences in scientific literature on the rising CO2 concentration
[15][62-64] and the strong correlation between the CO2 level in the atmosphere and the mean global temperature [15][65]. Of these the most detailed and comprehensive contributions are the assessment reports and special reports by the Intergovernmental
Panel on Climate Change (IPCC), a multi-national scientific group established to investigate the science of climate change under the auspice of United Nations
Environment Program and the World Meteorological Organization. According to the
Third Assessment Report (TAR) of the IPCC [15], since the industrial revolution the amount of carbon dioxide in the atmosphere has increased by 30% and continue to increase at an unprecedented rate of 0.4% per year mainly due to the fossil fuel combustion and deforestation. The TAR also reports an increase of global average surface temperature by 0.6 ±0.2 ° C.
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The global carbon cycle is shown in Figure 5.2. As shown the CO2 is generally kept at a steady state level by absorption by carbon sinks such as forests and soil carbon pools in the terrestrial biosphere and also by the oceans. However the present rate of fossil energy combustion emits CO2 and other GHGs at a rate faster than the absorption rate of the natural sinks. Furthermore the deforestation, agriculture and other land use changes have shrunk the sinks, thus creating the current increase of CO2 levels. Figure 5.3 shows the emissions by fossil fuel usage and the rate of increase of CO2 in the atmosphere and clearly indicates a correlation between them. The average fossil fuel carbon emissions in
1980s & 1990s are 5.44 ± 0.3 Pg/year and 6.3 ± 0.4 Pg/year respectively (1Pg = 1015g –
Petagrams).
5.1.3 The impact of electrical power sector on global warming
Fossil fuels are the dominating source of the world total primary energy supply (TPES).
For example the world TPES of 2003 is 10,579 Mtoe (million tonnes of oil equivalent
1Mtoe = 44.76 GJ) and about 80% of that is supplied by fossil fuels (34.4 % oil, 24.4% coal and 21.2% natural gas) [4] and a substantial portion of this fossil energy is used for electrical power generation. Figure 5.4 shows the fuel mix for electricity generation from
1971 to 2003. It can be seen that electricity is predominantly generated using fossil fuel resources. In fact electricity and heating energy are the largest CO2 emitting sectors and the fastest growing ones [66]. In 2003 the total fossil fuel related CO2 emission was
25.5GtCO2 and 40% of that was contributed by the electricity and heat sector.
Furthermore the total emission from the electricity and heat sectors in 1971 was
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3.7GtCO2 and that had increased to 10GtCO2 in 2003. The increase is mainly due to the growth in electricity demand [4].
Figure 5.2 - The global carbon cycle, showing the carbon stocks in reservoirs [15]. The global carbon cycle, showing the carbon stocks in reservoirs (in Gt C = 1015 g C) and carbon flows (in Gt C yr-1) relevant to the anthropogenic perturbation as annual averages over the decade from 1989 to 1998. Net ocean uptake of the anthropogenic perturbation equals the net air-sea input plus runoff minus sedimentation.
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Figure 5.3 - Fossil fuel emissions and the rate of increase of CO2 concentration in the atmosphere [15].
Figure 5.4 - Electricity generation by fuel [4].
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Because of this large contribution by the electricity sector, the mitigation attempts to reduce the GHG emission in the electricity sector are getting increased attention.
Furthermore, as electricity will be an important energy carrier in a clean energy future, emission free electricity generation is a global need. The other important factor that should be considered is the growing electricity demand of the developing countries. As discussed in Chapter 1, presently the electricity consumption in developing countries is at modest levels. However with the socio economic development the demand for electricity will also grow. Meeting such a demand growth with traditional fossil fuel based generations will add another large influx of GHGs in to the earth’s atmosphere. Therefore the use of cleaner sources for electricity generation is of the utmost importance.
5.2 Greenhouse gas emission reduction by biomass energy systems
Electrical power systems powered with sustainably obtained biomass can generate significant GHG emission reductions. In general GHG emission reduction attempts either to reduce GHG emissions by substituting fossil fuels with zero or low emission sources or develop sinks to sequester the GHGs which would otherwise be added to the atmosphere. Biomass energy projects with dedicated energy plantations fall under both these categories. The mechanism by which the biomass energy systems reduce the GHG, particularly CO2, is described in the following sections.
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5.2.1 GHG emission reduction by substituting fossil fuels
As described in sections 5.1.2 and 5.1.3 the main fuel sources for electricity generation are fossil fuels and they produce net positive CO2 emissions to the atmosphere. This is because carbon in fossil fuels is the atmospheric carbon that was absorbed by photosynthesis and deposited in reserves many thousands of years ago and any CO2 emitted to the atmosphere due to burning them results in a net increase in the present atmospheric CO2 level.
Biomass energy systems generate electricity using the energy obtained through thermo- chemical conversion (gasification/combustion) of harvested biomass from energy plantations. This process too will emit CO2. However this CO2 was originally absorbed from the atmosphere by the trees in energy plantation and will be reabsorbed in the next growing cycle as described in the section 5.2.2. Therefore in this case CO2 is recycled in a closed loop and the net emission to the atmosphere is zero. Thus if biomass is used to generate a unit of electricity instead of fossil fuels, it will avoid the net CO2 emission by the fossil fuel usage. The amount of CO2 that can be avoided, and also the factors which affect this amount, will be quantitatively analysed in the following sections of this chapter. It is important to note that as long as the biomass used is not from destroying natural forests then the net emission of CO2 to the atmosphere will be zero. For example instead of dedicated energy crops, the biomass in industrial or agricultural waste (saw dust, commercial forestry plantation residues, rice husk, coconut husk, urban waste etc.) is used, the net CO2 emission would be still zero. This is because the CO2 emitted in
92 those cases is the atmospheric CO2 absorbed in the previous biomass growing cycle which was few months or years ago, instead of many thousands of years as in case of fossil fuels.
5.2.2 Carbon sequestration in dedicated energy crops
The energy crops are managed plantations of trees with faster growth rates and shorter harvesting cycles. Depending on the tree species used, and the management practice, either the whole tree or the mature parts of it will be harvested at regular intervals. In either case the growing vegetation absorbs atmospheric CO2 through “photosynthesis” and converts it into plant carbohydrate (C6H12O6) with oxygen (O2) as a by product. This is a complex photo-chemical process and the simplified general equation is given in equation 5.1 [12].
6CO2 + 6H 2O ⎯Lightenerg⎯⎯⎯y→C6 H12O6 + 6O2 (5.1)
The energy for the process is obtained from the sunlight and the carbohydrate produced is stored in the branches, stumps, roots and foliage of the tree. Some CO2 is emitted back to the atmosphere through respiration, decaying of the dead woody parts and fallen leaves.
Another important process in the energy plantation is the carbon storage in the soil. The roots, decaying wood matter and foliage increase the soil carbon content [67][68]. With the growth of the vegetation, these carbon pools will also increases and when the trees become mature their growth as well as the growth of the carbon pools will cease. Carbon
93 stored in aforementioned different pools will be quantitatively analysed in section 5.3 and section 5.4.
Because the trees are regularly harvested to supply biomass for energy generation, the energy crop will act as an active carbon sink. Furthermore when degraded land, in which the soil carbon pool is severely oxidized, is used for energy plantations it will restore the land by increasing the soil organic content.
The main objective of this chapter to model and quantitatively analyse the GHG emission mitigation potential of an isolated small sized, village scale biomass based electrical power system with a dedicated energy plantation. A simple mathematical model was used to quantify the CO2 amounts that was either sequestrated or avoided. A sensitivity analysis was then performed to investigate the effect of different factors that determine the total amount of CO2 reduced.
5.3 Methods and models
A hypothetical village scale biomass energy system, similar to the ones described in the case studies in chapter 3 is used for this analysis. Since the amount of CO2 reduced depends on the biomass sources, plantation management practices and local geographic and climate factors, conditions for Sri Lanka were used for the analysis. The following assumptions were made for the calculations.
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Gliricidia sepium is grown as an energy crop in managed plantations degraded lands with a density of 5000 trees per hectare and all the branches of the trees are harvested at an interval of 12 months and the stumps are left in field for re-growth. Artificial fertilizer is not used for the plantation. The harvested and prepared biomass is then transported to power station using tractors where they will be used for power generation using gasifier/IC-engine combination. Tractors are also used for site preparation in the first year when planting Gliricidia. The average transport distance is assumed to be 2km. Apart from the diesel for the tractors it was assumed that all other operations such as harvesting and fuel preparation are done using manual labour.
The annual biomass yield of Gliricidia was taken as 20t/ha/year in dry weight basis. This is the typical yield that has been obtained by the plantation trials made in Sri Lanka
[14][29][34][69] and also agrees with the observations made in the field studies. The flow of fuels, carbon and energy within the biomass energy system boundary are shown in
Figure 5.5.
An electrical power station with a diesel generator is used as the base line to calculate the
CO2 emission avoided through fossil energy substitution [61][70]. This was chosen because it is the most likely option for power generation for a rural off-grid village if the biomass system is not implemented as mentioned in chapter 4. The amount of carbon in standing and harvested biomass was assumed to be 50% in dry weight basis [70-73].
Tonne of carbon (tC) is used as the primary measurement of carbon. To convert this in to tonne of CO2 (tCO2) the IPCC standard measurement of GHG emission reductions [61],
95 tC amount should be multiplied by 44/12. Analysis was done for a period of 15 years
(economic life of the biomass power system) with a time step of one year.
Figure 5.5 - Carbon, energy and fuel flows within the system boundary.
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5.3.1 Models
5.3.1.1 Model for CO2 not released by fossil fuel
The amount of fossil fuel that can be displaced by a certain amount of wood depends on the net heating value of the fossil fuel, net heating value of the wood, and the conversion efficiencies. Equations to calculate the amount of CO2 offset through fossil energy substitution were derived using the guidelines proposed in the IPCC guidelines
[61][70].The amount of wood available per year to displace fossil energy is the annual yield of the energy plantation. If Mw (tonnes) is the annual wood yield then the total electrical energy, Egen (GJ) that can be generated can be calculated using equation 5.2.
Egen = η gasη gen H w M w (5.2)
Where ηgas and ηgen are the cold gasification efficiency of the gasifier and net electrical conversion efficiency of the engine/generator respectively. Hw (GJ/t) is the net heating value of the wood. Then the amount of fossil fuel that can be displaced or saved, Mf
(tonnes), is the amount needed to generate the same amount of electrical energy. This can be calculated using equation 5.3.
Egen M f = (5.3) η f H f
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Where ηf and Hf (GJ/t) are the conversion efficiency of the fossil fuel system and the net heating value of the fuel displaced respectively. The non-released carbon amount (in tC) due to fossil fuel substitution can be obtained using equation 5.4.
C f = ηc I c M f (5.4)
Where Ic is the carbon content in fossil fuel expressed in tC per tonne of fuel (tC/t).
Factor ηc is the combustion efficiency and that is to account for the small fraction of carbon that will not oxidise during the fossil fuel combustion. That depends on the fuel used, combustion technology used and equipment age. Typically for diesel engines ec is about 99% [70]. Typical values for Hf and Ic for diesel are 43.33 GJ/t and 0.875 tC/t respectively [61]. For the biomass system Hw is 13.5 GJ/t (20% moisture basis) [14][29].
Substituting these values in equations 5.2 through 5.4 and combining them an expression for the total annual carbon not released by fossil fuel substitution is obtained (equation
5.5).
⎛η η ⎞ C = 0.27⎜ gas gen ⎟M (5.5) f ⎜ ⎟ w ⎝ η f ⎠
5.3.1.2 Model for carbon stored in above ground biomass
In above ground plant matter, carbon is stored in branches, stumps and foliage. For the carbon stored in woody parts of the trees a simple growth function proposed by Marland
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& Marland in [71] was used. In this model the carbon stored in the total above ground biomass at any time, Cn+1 (tC/ha), was taken as a function of the previous stock Cn and the growth rate Gc (tC/ha/y) with a limiting value of Cmax. The carbon growth is modeled by equation 5.6 [71].
Cn+1 = Cn + Gcn (5.6)
where Gcn = Gc when Cn ≤ Cmax/2
and Gcn = (Gc/Cmax/2) (Cmax-Cn) when Cn>Cmax/2
According to this function the carbon stock grows linearly at a rate Gc until it reaches half of the maximum value. Thereafter the growth rate is proportional to the difference between the standing carbon stock and the maximum carbon stock that can be supported by the specific tree species and the particular site. This is due to the ceasing of carbon stock growth as the trees mature. Amount of carbon in trees is assumed to be 50% of the weight of the woody biomass (dry weight basis) [72][74]. Therefore Gc (tC/ha/y) was assumed to be half of the tree growth rate G (t/ha/y). Gliricidia growth data obtained from literature and field observations were used with growth function in equation 5.6, in order to calculate the carbon stored in above ground biomass. Considering the plantation management practice, the carbon stored in harvested biomass (Ch) and un-harvested stumps (Cs) were considered as two different carbon pools.
For the standard analysis a growth rate (Gh) of 20 t/ha/y was assumed for the harvested or the branch biomass [14][29][69][75]. For the Sri Lankan conditions, the range for this
99 value is about 15 – 30 t/ha/y and that range was used for sensitivity analysis. The literature cited are the published results of the biomass energy system trials done in Sri
Lanka and they also agree with the observations made in field studies (see chapter 3).
Because all the branches are pruned when harvesting, the harvested biomass amount per year was assumed to be same as the annual growth rate. The maximum amount of the branch biomass that can be achieved is about 150 t/ha. However, since all the branches are harvested every year, this limiting value would never be reached. The carbon growth rate for the harvested biomass, Gch was taken as Gh/2 (10 tC/ha/y).
There is limited available literature on the growth rates and carbon pools of un-harvested stumps for a management regime used for the system that is being analyzed. The data published in [76] and [77] was used to estimate the parameters for stump carbon pools as the methodology used in those are very similar to plantation management practice used for this analysis. Using those data, a growth rate of 15 t/ha/y (carbon growth: 7.5 tC/ha/y) and maximum stump biomass value of 30 t/ha (maximum carbon: 15 tC/ha) was used for the standard analysis. For the sensitivity analysis, the growth of stump carbon pool was assumed to be 75% of the branch carbon pool growth rate. Maximum carbon pool value was assumed to be the same value as the standard analysis (ie 15 tC/ha). A long term study with Gliricidia plantation under same conditions is needed to obtain the exact results. However the above values agree with the field observations and are sufficient for a simplified analysis. The carbon flows in the two above ground pools for 10 years are shown in Figure 5.6.
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Figure 5.6 - Carbon flow in above ground biomass pools
5.3.1.3 Model for carbon stored in root biomass
Biomass content in roots depends on the type of the tree, soil characteristics and climate conditions. A method proposed by IPCC was used to estimate the root biomass content
[73]. In this method, the root biomass to the above ground biomass ratio is taken as 0.26.
Using this relationship, the carbon stored root biomass, Cr , can be calculated using equation 5.7.
Cr = 0.26(< Ch > +Cs ) (5.7)
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Where
5.3.1.4 Model for carbon stored in soil
The amount of carbon stored in soil depends on the local climate conditions, soil type and the condition of the soil before the energy plantation was implemented. The soil carbon gain data published in [68] is used to quantify the soil carbon pool. According to that when a degraded land in Sri Lanka is converted to an agro-forestry plantation the soil carbon sequestration rate is 0.3 – 0.5 tC/ha/y. An average rate of 0.4 was used for the calculations. Therefore the soil carbon content, Csoil, was assumed to linearly grow at the above rate. Though there is a maximum limit for the carbon content that can be sequestrated in soil pool, it was assumed that the peak value will not be reached during the time period that is of interest for this analysis.
5.3.1.5 Model for carbon emitted due to fossil fuel usage in plantation activities
Diesel is used in tractors that used for site preparation and wood transport. Therefore the carbon emitted due to those activities must be subtracted in order to calculate the net carbon offset. Tractor fuel consumption for these activities was found from the field study. Thereby, the tractors diesel consumption for site preparation is 40 l/ha and that for wood fuel transportation is 0.25 l/ t km (litres per tonne kilometre). Therefore the carbon
102 emitted in preparing 1ha of land can be calculated using equation 5.8. This is a one time emission for a given plantation.
40η D I C = c diesel c (5.8) esp 1000
Where Ddiesel is the density of diesel, 0.82 kg/l. The carbon emitted in transporting the annual wood biomass amount can be calculated using equation 5.9.
0.25η D M dI C = c diesel w c (5.9) etr 1000
Where d is the average distance that the wood is transported. It should be noted that in the calculation in equation 5.9 it is assumed that the total annual yield is transported in a single trip from the plantation to the power station. However the actual case is different from that and the harvesting and transporting is done throughout the year. However this will not affect the analysis results by a considerable amount. This is because the value of
Cetr is small compared to the other carbon pools. Furthermore, in actual village scale biomass power systems, the wood is normally transported using non fossil consuming means such as, manual labour, bicycles and bullock carts.
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5.4 Analysis results
The models described in sections 5.3.1.1 through 5.3.1.5 were coded in Matlab® m-file programs to perform the standard and sensitivity analysis. Carbon pools in un-harvested stumps and roots are considered as a single pool for the analysis. This is denoted as carbon stored in total un-harvested biomass, Cuh. The analysis was done for a unit area
(1ha) of energy plantation for clarity.
5.4.1 Standard analysis
In the standard analysis carbon stored or avoided in different pools were calculated for a period of 15 years and presented in time series plots. The parameter values used for this analysis are listed in Table 5.1.
Table 5.1 – Parameters used for standard analysis Parameter Notation Value
Branch biomass growth rate Gbr 20 t/ha/y
Stump biomass growth rate Gst 15 t/ha/y
Maximum stump biomass Smax 30 t/ha
Soil carbon growth rate Gcs 0.4 tC/ha/y
Net heating value of wood (20% moisture) Hw 13.5 GJ/t
Cold gasification efficiency ηgas 70%
Producer gas engine/genset efficiency ηgen 20%
Net heating value of diesel Hdiesel 43.33 GJ/t
Carbon content in diesel Ic 0.875 tC/t
Diesel engine/genset efficiency ηf 25% Average wood transport distance d 2km
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Results of the standard analysis are listed in Table 5.2. Figure 5.7 shows the flow of carbon in different pools that were obtained from standard analysis. Figure 5.8 shows the cumulative CO2 offset and the annual rate CO2 offset. As described in section 5.3.1.5 carbon pool in stumps and roots saturates at 20.2 tC/ha as the plantation matures.
Therefore the rate at which CO2 is sequestered, drops and stabilizes. Net carbon offset through fossil fuel substitution was obtained by subtracting the amount of carbon emitted by tractor usage from the avoided carbon emission. Total carbon offset during this 15 year period is about 71.4tC/ha corresponding to 261.8t of CO2 offset (71.4 tC/ha x 44/12
= 261.8 tCO2/ha) from the atmosphere. The total electricity generated using the wood supplied by 1ha of energy plantation (300t) is 157.5MWh. This corresponds to operating a 1.7kW electrical energy plant with an annual plant factor of 70%. The CO2 offset rate of the power plant is 1.66kgCO2/kWh. If a diesel system is used to generate the same electricity amount that will emit about 166t of CO2, corresponding to an emission rate of
1.06kgCO2/kWh. The difference between the two CO2 levels is the amount sequestrated in standing biomass. The net contribution from the carbon storage in branch biomass is zero as they are regularly harvested. However they provide the wood to substitute diesel, thereby avoiding a potential CO2 emission to the atmosphere. The saw-tooth shaped variation represents the CO2 recycling from the atmosphere, the mechanism which makes the biomass energy system a CO2 free source of electrical energy. These two CO2 flows are shown in Figure 5.9.
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Table 5.2 - Results of standard analysis. Year Cumulative C Cumulative C Cumulative C offset C emission by Total storage storage due to diesel tractors Ctot in un-harvested in soil substitution Cem , (tC/ha) (tC/ha) biomass, Cuh Cs, (tC/ha) Cf, (tC/ha) (tC/ha) 0 0.0 0.00 0.00 -0.03 -0.03 1 18.7 0.40 3.02 -0.04 22.08 2 20.2 0.80 6.05 -0.05 27.00 3 20.2 1.20 9.07 -0.06 30.41 4 20.2 1.60 12.09 -0.07 33.82 5 20.2 2.00 15.12 -0.08 37.24 6 20.2 2.40 18.14 -0.09 40.65 7 20.2 2.80 21.17 -0.10 44.07 8 20.2 3.20 24.19 -0.11 47.48 9 20.2 3.60 27.21 -0.12 50.89 10 20.2 4.00 30.24 -0.13 54.31 11 20.2 4.40 33.26 -0.14 57.72 12 20.2 4.80 36.28 -0.15 61.13 13 20.2 5.20 39.31 -0.16 64.55 14 20.2 5.60 42.33 -0.17 67.96 15 20.2 6.00 45.36 -0.18 71.38
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80 C stored in soil C stored in unharvested biomass 70 C stored in harvested biomass Net C offset by fossil 60 fuel substitution
50
40
30 Cumulative carbon offset tC/ha
20
10
0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Time, years
Figure 5.7 - Carbon flow in different pools (standard test)
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300.00 Annual rate of CO2 offset Cumulative CO2 offset 250.00
200.00
150.00
100.00 CO2 offset,CO2 tCO2/ha 50.00
0.00 012345678910111213141516
-50.00 Time, years
Figure 5.8 - Cumulative CO2 offset and annual rate of CO2 offset
180 CO2 emission of biomass energy system
160 CO2 emission of diesel system
140
120
100
80
60 Cumulative CO2 emission, tCO2
40
20
0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Time, years
Figure 5.9 - Cumulative CO2 emission of biomass system and diesel system.
CO2 released from the biomass energy system recycles through the energy plantation while that for the diesel energy system grows with time.
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5.4.2 Sensitivity analysis
The amount of carbon that can be offset depends on the various parameters. A sensitivity analysis was performed to assess the dependency of the total carbon benefit of the energy system on the energy plantation growth rate and the efficiency of the producer gas/generator electrical conversion efficiency. Biomass growth rate is selected as one variable parameter because it is more prone to variations due to seasonal and geographic conditions. Plant conversion efficiency was chosen to assess the importance of operating the plant at a higher efficiency.
Branch biomass growth rate, Gbr , was varied in the range 0 – 30 t/ha/y. Stump biomass was linked to it by taking its growth rate as 75% of the branch biomass. Root growth will be automatically linked as explained in section 5.3.1.3. The electrical conversion efficiency of the producer gas engine/generator setup, ηgen was varied in the range 0 –
30%. All the other parameters are kept at the same values shown in Table 5.1. Total carbon offset after 15 years is calculated for these two parameter ranges. Resulting carbon offset is presented in Figure 5.10 as a 3D surface plot and in Figure 5.11 as a 2D colour map.
It can be seen from the results of the sensitivity analysis that high growth rates and high efficiencies yield high carbon offsets. This further shows that operating the power system in an environmental perspective is also important as it will offset more carbon. For example if ηgen is increased from 20% to 21% at 20t/ha/y growth rate, the carbon offset
109 will increase by 3.2%. This could be economically advantageous as well in the presence of carbon credits as discussed in section 5.5.
tC/ha
120
140 100
120
100 80
80
60 60
40 40 Cumulative carbon offset tC/ha/y 20
30 0 25 20 -10 20 0 15 0.05 0.1 10 0.15 0.2 5 Generator efficiency, % 0.25 Growth rate, t/ha/y 0 0.3 0
Figure 5.10 - Carbon offset after 15 years for Gbr: 0-30 t/ha/y and ηgen: 0-30% in surface plot.
110
tC/ha 30
120
25
100
20
80
15 60 Growth rate, t/ha/y rate, Growth
10 40
5 20
0 0 0 0.05 0.1 0.15 0.2 0.25 0.3 Generator efficiency
Figure 5.11 - Carbon offset after 15 years for Gbr: 0-30 t/ha/y and ηgen: 0-30% in a colour map.
It was found that the net carbon offset is slightly more sensitive to the growth rate under assumed conditions for the standard test. This is shown in Figure 5.12. As shown there the slope of the carbon offset variation against Gbr is slightly higher that that of carbon offset variation against ηgen. The reason for that is in the longer run carbon offset is
111 mainly governed by the fossil fuel substitution, and higher growth rates provide more wood enabling higher fuel substitutions.
15.00%
10.00%
y = 0.6519x 5.00%
0.00% -25.00 -20.00 -15.00 -10.00 -5.00% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% % % % % -5.00% % variation of C offset C of % variation
-10.00%
-15.00% % variation of growth rate from 20t/ha/y
(a)
15.00%
10.00%
y = 0.6349x 5.00%
0.00% -25.00 -20.00 -15.00 -10.00 -5.00% 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% % % % % -5.00% % variation ofoffset C
-10.00%
-15.00% % variation of generator efficiency from 20%
(b)
Figure 5.12 - (a) Percentage variation of C offset with varying Gbr. (b) Percentage
change of C offset with varying ηgen.
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A sensitivity analysis can be performed to find out the effect on carbon offset by the other parameters too, which were kept constant in this sensitivity analysis.
5.5 Biomass energy systems and carbon credits
The CO2 offset by biomass energy systems can be used as a means of financing them by trading them under the Clean Development Mechanisms (CDM). This potential is assessed in this section.
5.5.1 The Kyoto protocol and CDM
Worldwide concern over the global warming led the nations to sign the United Nations
Framework Convention on Climate Change (UNFCCC) in 1992 at the Earth Summit held in Rio de Janerio. The objective of that is to achieve stabilization of greenhouse gas concentrations in the atmosphere at a low enough level to prevent dangerous anthropogenic interference with the climate system. Subsequently at the third conference of parties (COP3) held in Kyoto in 1997, the members adopted the Kyoto Protocol to the
UNFCCC. Under this the countries listed in the annex I of the protocol are obliged to reduce their GHG emission level 5% below the 1990 levels. The Kyoto protocol came into force in February 2005. The annex – I countries are industrialized nations which are either developed or with transition economies. The developing countries who ratified the
Kyoto protocol are called the non-annex I countries and they are not obligated to achieve any emission reductions [56][78]. The Clean Development Mechanism is one of the three
113 flexible mechanisms implemented under the Kyoto Protocol to reduce the GHG emissions. The other two mechanisms are Emission Trading (ET) and Joint
Implementations (JI).
The CDM provides a framework for the annex I countries to invest in GHG emission reduction projects in non-annex I countries and use the credits earned from those to meet their emission reduction targets. These projects must contribute to sustainable development in host countries as well in addition to reducing overall GHG. Carbon credits under CDM are measured in “Certified Emission Reductions (CERs)”. One CER is equivalent to one tonne of CO2 (1tCO2) offset. Annex I countries can buy CERs from developing countries and use them to achieve their national reduction levels. Before trading the CERs must be properly validated and verified. CDM is administered by the
CDM Executive Board under the UNFCCC secretariat [78][79].
In a CDM project the amount of CERs generated is measured against a baseline. The baseline is usually the next most likely option in the absence of the project. This is similar to the baseline described in section 5.3. The market value of CERs is rapidly changing. The average prices in 2004 and 2005 were US$5.15/tCO2 and US$7.23/tCO2 respectively. In the first quarter of 2006 this had gone up as high as US$11.45/tCO2 [80].
The developing countries are actively participating in CDM projects and in 2005 the total value of CERs transacted was US$ 2.7 billion. The main sellers of CERs are India &
China while the main buyers are Japan and the European Union [80]. Approved CDM projects to date include renewable energy projects for power generation, energy
114 efficiency improvement projects, fuel switching projects, afforestation and reforestation projects, methane capture from land fills etc.
It must be noted that CDM is a project based GHG reduction mechanism and all CER accounting must be done within the project boundary. The rules and regulations that are to be followed by CDM projects are set up by the CDM executive body and those includes the reporting, validating and verification steps that must be followed in order to trade CERs [81].
5.5.2 CERs generated by village scale biomass energy systems.
The amount of CERs generated by a 5kW biomass energy system operating at an annual plant factor of 70% is calculated in this section. The operating parameters and the baseline use are the same as the standard GHG analysis performed in section 5.4.1. Under the present approved methodologies by the CDM executive board, CERs generation by providing CO2 sinks can only be done through afforestation and reforestation projects
[80][82]. Therefore only the CO2 offset by fossil fuel substitution was considered in order to calculate the emission credits.
Using the calculations described in section 5.4 the land requirement for this energy system is about 3ha (1ha operates 1.7kW plant at 70% plant factor. See section 5.4.1).
Then total CO2 offset is 785.2 tCO2 for 15 years or 52.5tCO2/y. Of this amount, CO2 offset due to fossil fuel substitution is 486.5 tCO2 (32.5 tCO2/y). At a CER price of
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US$10/tCO2 this will earn US$4865 (US$325/y). The total electricity generated in 15 years is 459.9MWh (30.7 MWh/y). Therefore this will reduce the cost of electricity by
US¢ 1/kWh. The effect on cost of electricity under different CER price is presented in
Figure 5.13.
2.500
2.000
1.500
ct/kWh 1.000
0.500
Cost of electricity reduction electricity Cost of Us 0.000 1 6 11 16 21 CER price US$/tCO2
Figure 5.13 - Affect on cost of electricity by different CER prices.
5.5.3 Trading CERs under CDM
As explained in section 5.5.1 to trade the CERs under the CDM they must be validated and certified against a baseline. The validation and verification must be done by an independent agency, which has been accredited by the CDM executive board, and it
116 provides its services for a fee. There is also a substantial amount of administration work and documentation that needs professional services to prepare. Thus there is a significant amount of overhead cost incurred in the process of developing a CDM project [83].
To gain financial benefits from carbon trading the revenue generated by CER trading should be considerably higher than the overhead costs explained above. In some cases the
CER buyer provides the transaction costs that are incurred in the CDM process, but in general the value of the CERs generated by the project must be high in order to obtain the anticipated financial benefits.
The amount of CERs generated by a particular village scale project therefore may not high enough to obtain the benefits of carbon trading. However under the Marrakech
Accord agreed at the seventh conference of parties (COP7) of the UNFCCC, small scale projects can be bundled in order to share these transaction costs [81][83]. Also the level of verification and validation as well as the documentation requirements has been reduced for small scale projects (Under the CDM regulations a renewable energy project with capacity less than 15MW is considered as a small scale project). Therefore a number of small scale biomass energy projects can be bundled up to an aggregate maximum capacity of 15MW in order to form a single CDM project and thereby obtain the potential financial benefits of CER trading.
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5.6 Summary
In this chapter the GHG emission reduction potential of village scale biomass energy systems was quantitatively analysed. The analysis focused on CO2 reduction because it is the most significant GHG gas in the atmosphere. A biomass energy system with a dedicated energy plantation in Sri Lanka with Gliricidia sepium as the main energy crop was used as the reference power system. By performing the analysis on a unit area of energy plantation it was found that the biomass energy system offsets CO2 from the atmosphere at a rate of 1.86 kgCO2/kWh compared to a reference diesel system which emits CO2 at a rate of 1.06 kgCO2/kWh. CO2 negative operation of biomass energy system was also quantitatively analysed. This is a unique feature of biomass energy systems compared to other renewable energy technologies that are capable of creating
CO2 benefits only by substituting fossil fuels.. Biomass projects offset CO2 by also providing sinks due to the associated energy crop.
The carbon credits that can be traded under CDM to finance biomass projects were also quantified. It was found that the degree of contribution from the carbon credits depends on the market price of CERs.
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Chapter Six: Overcoming The Barriers
Technical feasibility of using biomass energy for electrical energy generation has been demonstrated by the rural electrification projects that are implemented in many developing countries [14][17][18][23][25]. However the potential of biomass based electricity generation as a means of rural electrification is yet to be recognized in many countries and regions. Barriers that affect the penetration of biomass based electrical generation in the developing countries are analysed in this section. Three barriers that were identified in the course of this research study are assessed with the proposals to overcome them. They are namely
• land scarcity barrier;
• economic barriers;
• operational barriers.
Case examples that are needed for the assessment and proposed mitigation strategies are taken from the projects in Sri Lanka which were studied in field surveys.
6.1 Land scarcity barrier
Biomass resources, the fuel for biomass energy systems are generated by photosynthesis.
The inherently low efficiency of the photosynthetic process has made biomass energy systems the energy form with lowest power produced per unit land area consumed
(power density) [84]. The photosynthesis efficiency is in the range of 3-6% and largely
119 depends on the climate and geographic conditions of the area in which the biomass is being grown [12]. Estimates of global biomass growth have averaged an annual global biomass yield of about 120 gigatonnes of dry biomass that prorates to a power density of
0.5 -1.1 W/m2 [84]. Power densities of various forms of biomass productions are shown in Figure 6.1. In a biomass power system the overall efficiency of the system will also be affected by the efficiencies of the conversion equipments used. As calculated in
Chapter 5 with the present state of the art technologies 1ha of land with an energy crop plantation that has a yield of 20 t/ha/year can operate a 1.7kW rural energy system based on gasification and IC engine technology with an annual plant factor of 70%. That corresponds to a power density of only 0.1 W/m2. Compared to conventional energy technologies with fossil fuel based power generation where the energy density is around
100-400 W/m2 or to solar photovoltaic with power density of about 15-18 W/m2 the power density of biomass energy systems is very low.
Figure 6.1 - Power densities of various forms of biomass production [84] .
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Because of this low energy density biomass energy is a very land intensive form of energy generation. Total land available in a particular country or a region is essentially a fixed amount and it has to be shared with other human needs such as food production, housing, industry, leisure etc. Furthermore, a considerable land area must be left available for natural forestry that sustains the resource balance of the world. Biomass energy systems therefore have to compete with these for the available land and this is one of the main barriers to popularising biomass energy systems. The effect of this becomes more apparent for the countries with high populations but smaller geographic area, a feature shared by many developing countries. Moreover in many developing countries agriculture is the major livelihood for a substantial portion of the population and priority must be given to that in an event of land competition. Overcoming this barrier becomes a challenge in such cases.
6.1.1 Overcoming land scarcity barrier
Land scarcity must be overcome by implementing effective land use and sound management practices and a comprehensive assessment of the land resources available is of the utmost importance. Along with the assessment of the available land, such an analysis should include the other competitive usages of the land, the priorities that should be assigned in case of a trade off situation, the net productivity of the present land use practices, and population growth, with an insight into a considerable time frame into the future. An analysis of that kind will provide a clear idea about the spatial as well as
121 temporal availability of land that can be utilized to develop biomass energy resources such as dedicated energy crops.
A considerable amount of degraded lands are available in many developing countries that are abandoned after poor land use practices such as slash and burn agriculture and deforestation. With proper selection of tree species, energy crop plantations can be employed on these lands and the soil carbon and nutrient levels can be restored.
Furthermore agricultural lands with very low productivity can be converted into dedicated energy crops. For example in Sri Lanka there are about 1.7 million hectares of sparsely used crop lands and range scrub lands which can be easily converted into productive energy plantations with Gliricidia. The growth rates and yields of Gliricidia on low nutrient level soils are proven to be high and the nitrogen fixation of the crop and the litter decay will restore the soil. Replication of such a system is possible in any other country or region as long as the proper selection of crop species and agroforestry practices, suitable for those places are undertaken. Therefore promoting and building capacities for the programmes that would generate such information are immediate needs.
Sharing the land among energy crop plantations and commercial agricultural crops is another effective solution to overcome the land scarcity barrier. In this case too the proper selection of species is needed. Promoting such land use activities through incentives or/and ensuring a guaranteed market will motivate the farmers to adopt the intercropping practice.
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Increasing the production yields of the food crops as well as the energy crop plantation will reduce competition for the land. For example in Sri Lanka the average yield of rice
(paddy) in last 10 years is about 3.3 t/ha and In case of India it is about 2.8 t/ha [85]. In both countries this is lower than the Asian average of 3.9 t/ha and much less than that of
China which is 6.2 t/ha. Increasing the yield by adopting better agricultural techniques will reduce the land intensity of the crop and the regional data shows that it is possible.
Selecting species with high yields will foster the same result from the energy crop plantations.
From a technology point of view the land requirement needed can be reduced by increasing the conversion efficiencies. For example using a similar calculation used in
Chapter 5 it can be shown that using the biomass from a 1ha of energy crop plantation with a yield of 20 t/ha/y, the capacity of the power plant that can be operated at a plant factor of 70% is 1.3kW if the engine/generator efficiency is 15% and that for a system with a 20% efficient engine/generator is 1.7kW. Thus a 5% increase in the engine/generator efficiency increases the capacity of the plant that can be operated using the same land area by 31%. Furthermore by integrating other renewable resources such as wind or hydro power, the overall land demand can be reduced while providing the same level of energy services.
As suggested above the land scarcity barrier can be overcome by proper planning and management practices.
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6.2 Economic Barriers
Despite the technical feasibility and availability of resources many potential biomass projects do not proceed due to economic barriers. These economic barriers could be in the form of the absence of capital funding, where the project does not proceed at all, or in the form of high operating costs where the cost of energy becomes too high and not affordable as a result. There could be barriers due to the presence of favourable economics from other competing services. For example high subsidies on fossil energy will reduce the price seen by the end users and they will prefer to stick with conventional fossil energy based services such as kerosene wick lamps or diesel generators despite the difficulty of procuring them and the health and environmental hazards associated with them. A collective effort by the government agencies, private enterprises and investors, development assistance agencies and community organizations is needed to overcome the economic barriers.
6.2.1 Overcoming the economic barriers
Considerable capital investment is needed to implement a biomass based electrical power system in a rural village. Systems implemented through donor funding is a straight forward solution but the availability of donor funding will limit the penetration. It is unlikely that the end users of the system will have access to the amount of funds needed by themselves or even through a community cooperative. However there is normally a steady cash flow to purchase conventional energy sources such as kerosene and candles
124 for lighting or battery charging [5][6]. Depending on the income levels and other socio economic factors, the rural populations in the developing world are spending about
US$ 15-100 per year on kerosene purchase, which is mainly used for lighting[6]. Hence there is certainly a market for electricity and which the private investors can tap into. A win-win situation is formed in that case as the rural community get the energy service while the investor is making a fair profit. Moreover the biomass needed for the power system can be obtained from the community itself, creating employment and contributing to the economic development of the community. This is the fastest way of providing electrical energy services to the rural communities using biomass energy.
Incentives from governments and development assistance agencies will have a continuing important role. These incentives should be supplied both as capital cost incentives as well as operating cost incentives. Contrarily, governments in developing countries usually spend considerable amounts on fuel subsidies. For example in Sri Lanka there is SLRs
30/liter (US$0.3/liter) subsidy on kerosene because the rural communities heavily rely on it for home lighting. Compared to the actual cost of kerosene production (LKRs 67/liter at current oil price) this is a 45% subsidy. By providing a similar incentive to biomass energy systems a much better energy service can be provided to the rural communities at an affordable price. Furthermore by implementing distributed power generation to provide electricity, the grid extension costs can be avoided. Depending on the country, the grid extension costs vary from US$2000 to US$22000 per kilometre. In developing countries utility grid expansions are normally supported by infrastructure development projects funded by the governments. Extension of utility grids can be avoided by
125 implementing community based biomass power systems and the avoided cost of grid extension can be invested in implementing such a system. Utility companies can also take this into consideration and implement mini biomass power stations in the communities using the avoided grid extension expenditures.
Another very important fact that has to be considered by the governments is the avoidance of fossil energy usage to meet the rural energy demand. Many developing countries are importing all the fossil energy needed and thus large sums of foreign exchange are being spent needlessly. Because biomass is grown locally money spent on fossil energy purchase can be retained in the local economy itself.
The potential of energy systems implemented and operated by community cooperatives is a potential that is constantly overlooked [46]. Community cooperatives can acquire biomass energy systems if they can secure the initial capital investment needed. If the cooperatives can obtain credit through some financing scheme, they can procure the investment needed. However in many developing countries access to credit is unavailable unless at very high interest rates [46]. Therefore building that credit capacity is another role for government and development agencies.
As calculated in the analysis in Chapter 4, low energy demands in rural areas results in higher energy prices which will make it unaffordable, therefore creating a market for the energy among the community is needed. Private investments again are the fastest way of achieving this.
126
Another potential financing method for biomass energy systems is through the Clean
Development Mechanisms (CDM). The certified emission reductions (CERs) generated
(analysed and quantified in Chapter 5) can be traded in the carbon markets and the revenue generated can be used to help cover the operating expenses. There are some considerable overhead costs that incur in the process of developing a project that is eligible to trade CERs under CDM [81][83]. These costs are borne in the form of administration, certifying and verification of CERs generated. Therefore CERs generated by individual village projects may be too small to cover these administration costs.
However the bundling of small projects is possible under CDM regulations and hence a number of small village scale projects can be bundled to share these overhead costs.
Building of some institutional capacities to lead the bundling process is needed.
6.3 Operational barriers
As explained in the case studies, operating and managing a biomass power system is a fairly complex process. Uninterrupted supply of biomass resources must be ensured and the maintenance requirements demanded by the energy systems are relatively high.
Skilled labour for operating the energy system is a must. As a steady cash flow to offset the operational expenses has to be secured, simply achieving a sustainable operation is a challenge. There are many examples of renewable energy projects, that were developed under rural infrastructure development, which have failed due to the absence of a proper institutional structure to manage and operating them [9]. Biomass projects operated by
127 private investors with professional managers could still fail due the lack of steady supply of biomass resources.
6.3.1 Overcoming the operational barriers
For the systems that are operated by the community an energy cooperative was found to be the most effective method of managing the system. Success of such a mechanism was observed in the field surveys and discussed in the case studies (Chapter 3). However as community cohesiveness is essential for the success of such a system, some guidance and awareness creation is needed in the early stage in the projects. Providing some form of training and education on managerial skills need to the community leaders is necessary, and such capacity building may be initiated by the development assistance agencies or
NGOs.
Securing biomass supply is fundamental to the sustainability of biomass energy projects.
Furthermore the quality of the biomass supply should meet the standards demanded by the technology being used. The motivation of the suppliers should be kept high in order to ensure the steady supply and attractive rates and guaranteed markets are necessary to achieve that. Stocking of biomass as necessary is recommended rather than depending on day to day supply, particularly in periods such as the rainy season when a steady supply could be interrupted. Maintaining biomass energy plantations by the power system itself, in addition to supplies from the community, is recommended.
128
Having a wide market for electricity is also important to motivate the biomass suppliers in rural communities and the extra income that can be earned by selling the biomass to the power system will keep them motivated.
6.4 Summary
Three main barriers to the implementation of biomass energy systems to provide electrical energy to rural communities in the developing countries were described along with proposals to overcome them.
Support from government agencies was seen as one of the most important factors in overcoming the barriers. Therefore a biomass energy policy should be included in the national energy policies by the developing countries. Private sector intervention is a key factor to the faster penetration of biomass energy systems with the result that a win-win situation can be created by such participation.
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Chapter Seven: Conclusions and Future Work
Rural electrification is a pressing need in developing countries and with current fossil fuel prices the achieving of that need with conventional energy sources is not possible, at least for the foreseeable future. The use of biomass energy for rural electrification is not only feasible but and it can contribute to human development in many ways. A biomass gasification and internal combustion engine combination is suitable for village scale biomass energy systems due to the comparatively low initial cost and low operational complexity.
The establishment of a proper institutional structure is needed to operate and manage a biomass power system and this is important in order to achieve system sustainability.
Community cooperatives were found to be a successful mechanism to manage biomass energy systems and the successful operation of such a system was observed in the field surveys conducted.
Biomass resources are available in many forms and the feasibility of using them for electricity generation depends on their physical and chemical characteristics as well as the cost of obtaining them. Dedicated energy plantations are the best source from which to obtain biomass since a steady supply of biomass is a key factor for the sustainable operation of the power system. This will also create employment and additional income sources for the rural communities. Sharing the land with energy crops and other agricultural crops increases the financial benefits that can be obtained from an energy
130 plantation. By selecting proper crop species, byproducts with high economic values can be generated.
The cost of the electricity generated by biomass power systems is significantly lower than the other potential electricity generation systems based on conventional fuels. The cost of energy is largely dependent on the total energy demand and this can be a challenge for village scale biomass systems. Economic analysis with different power demand profiles showed that the cost of electricity is lower for higher power demands. Therefore it is important to create a market for electricity within the rural community in addition to the usual household energy usage. Inclusion of a battery bank and an inverter is one possible alternative solution to bring down the COE for systems with low energy demands and high operational costs. Feasibility of such a system depends on the operational costs and the battery bank cost.
Operational costs such as fuel cost, operator wages and equipment maintenance costs usually dominate the COE of biomass power systems, therefore ensuring a means of financing those is important for successful operation.
Contribution to GHG emission reduction is one of the main benefits of biomass energy systems. The amount of GHG, particularly CO2 emission reductions, caused by a particular biomass energy system depends primarily on the efficiency of the power conversion equipments used, the growth rate and yield of the associated energy
131 plantation, and the carbon stock carrying capacity of the site that is used for the plantation.
Scarcity of land was found to be one of the main barriers to implementing biomass energy systems due to the high land area demanded by such systems. Effective land use and energy forestry practices are needed to overcome this barrier and sharing the land with other crops is an immediate step that can be taken to mitigate this problem. Such land use practice is feasible and successful applications were observed in the field surveys.
Support from governments and development assistances agencies as well as private sector investment are the fastest way of providing electricity to the rural communities, as securing the initial capital investment is a challenge for the rural populations.
Furthermore, due to the high potential of biomass energy for rural electrification and other socio economic benefits associated with it in both community levels as well as in broader national level, biomass energy policies should be included in the national energy policies and rural infrastructure development programs.
7.1 Future Work
Planning, implementing, and operating a biomass energy system is a process involving a large amount of data and resource constraints, and those should be handled with care in order to retain the benefits and make the energy system environmentally and economically sustainable. An integrated biomass system planning and optimization tool
132 with the capability of analysing the biomass resource constraints, system economics, environmental impacts, land use scenarios etc. can support the decision making process.
Developing such a decision support system is an anticipated research goal as a continuation of work in this field.
Because biomass energy systems use considerable natural resources such as land and water, a complete life cycle analysis is needed to analyse the environmental performance.
Such an analysis can be used to identify the weaker areas in environmental performance of biomass energy systems and initiate the necessary improvements. Such a study with village scale biomass systems is a priority research need.
133
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Appendix A: Explanation of Units
Metric (SI) units with their prefixes were used throughout this thesis. The units which are not standard SI units are explained bellow.
atm Atmospheres (1atm = 101.325 ×103 Pa) ha Hectares (1ha = 10,000 m2) kWh Kilowatt hours (1kWh = 3.6×106 J)
Mtoe Million tones of oil equivalent (1Mtoe = 44.76×109 J)
Nm3 Normal cubic meters (volume in m3 at 1atm and 15°C) t Metric tonnes ( 1t = 1000kg) tC Metric tonnes of carbon tCO2 Metric tonnes of carbon dioxide