Off-Grid Renewable Energy Options for Rural Sustainable Development: a Case Study of Guizhou Province, China

Home , Danzhai County, Kaili City, Kaiyang County, Qingzhen, Wudang District, Xiuwen County

OFF-GRID RENEWABLE ENERGY OPTIONS FOR RURAL SUSTAINABLE DEVELOPMENT: A CASE STUDY OF GUIZHOU PROVINCE, CHINA

Chun Zhu

A dissertation submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Energy and Environmental Policy

Fall 2017

OFF-GRID RENEWABLE ENERGY OPTIONS FOR RURAL SUSTAINABLE DEVELOPMENT: A CASE STUDY OF GUIZHOU PROVINCE, CHINA

Chun Zhu

Approved: ______John Byrne, Ph.D. Professor in charge of the dissertation on behalf of the Advisory Committee

Approved: ______Syed Ismat Shah, Ph.D. Interim Director of the Energy and Environmental Policy Program

Approved: ______Babatunde A. Ogunnaike, Ph.D. Dean of the College of Engineering

Approved: ______Ann L. Ardis, Ph.D. Senior Vice Provost for Graduate and Professional Education

I certify that I have read this dissertation and that in my opinion it meets the academic and professional standard required by the University as a dissertation for the degree of Doctor of Philosophy.

Signed: ______John Byrne, Ph.D. Professor in charge of dissertation

Signed: ______Young-Doo Wang, Ph.D. Member of dissertation committee

Signed: ______Jiahua Pan, Ph.D. Member of dissertation committee

Signed: ______Bo Shen, Ph.D. Member of dissertation committee

ACKNOWLEDGMENTS

First and foremost, I would like to thank my advisor Dr. John Byrne, for supporting me during these past six years. It has been a great honor for me to be his Ph.D. student. As a distinguished professor of energy and environmental policy, Dr. Byrne provided me with every bit of guidance, assistance, and expertise that I needed during my Ph.D. study. He has taught me, both consciously and unconsciously, how good research is done. He gave me the freedom to choose the research topic that I want to take, at the same time continuing to contribute valuable feedback, advice and encouragement. I appreciate all his contribution of time, ideas, and funding to make my Ph.D. experience productive and stimulating. Especially during the last two years of my Ph.D. study, I was away from the campus, Dr. Byrne sacrificed his weekend and we had phone call meeting every three weeks for my dissertation consultation. His flexibility in scheduling, gentle encouragement and relaxed demeanor made for a good working relationship and the impetus for me to finish. In addition to our academic collaboration, I greatly value the close personal rapport that Dr. Byrne and I have forged over the years. Not only an advisor, but Dr. Byrne is also a close friend of mine. He was always aware of the unique issues facing by me such as I20 extension and CPT application, and offered helps as soon as he can. For me, he is the best professor and I quite simply cannot imagine a better adviser! I would also like to give a heartfelt, special thanks to Dr. Young-Doo Wang. He was not only my co-advisor until his retirement, but my mentor and friend. His patience, flexibility and caring and concern, and faith in me during my Ph.D. study

iv enabled me to earn my Ph.D. He has been motivating, encouraging and enlightening. He has been so kind to me – never judged or pushed me when he knew I needed more time on my research. Even after his retirement, he remained a supporter and provided insight and direction for me to the end. For this, I cannot thank him enough. And I am forever grateful. Also, I am very grateful to the remaining members of my dissertation committee, Dr. Jiahua Pan, and Dr. Bo Shen. I have known Dr. Pan for many years. Although he is a very famous expert in sustainable development in China, he is very humble and modest, and patient to me and to his students. He has been helpful in providing advice many times during my Ph.D. study. Particularly, without his support on collecting Chinese data, this dissertation could never be finished on time. For Dr. Shen, I am thankful to him for his time and valuable feedback on my preliminary version of this dissertation. He is very busy person, but still he spent quite amount of time on advising me on my research. The members of the Center for Energy and Environmental Policy (CEEP) have contributed immensely to my personal and professional time at University of Delaware (UD). CEEP has been a source of friendship as well as good advice and collaboration. I am especially thankful for the professors at the CEEP, who helped me with my course study and my research projects: Dr. Lawrence Agbemabiese and Dr. Lado Kurdgelashvilli. Also I would like to thank past and present CEEP members that I have had the pleasure to work with. I particularly want like to thank Ms. Joohee Lee for her help in assisting me submitting the required documents for graduation. I thank Ms. Mayuri Meera and Dr. Lemir Teron for assisting me with teaching the

v undergraduate students. And I thank Dr. Fei Guo for his efforts in proofreading my dissertation and providing valuable advices. My time at UD was very enjoyable largely due to UD is a great community and I felt lucky that I am being part of this great community. I am grateful for time spent with my friends at UD, for the AG day, for the International Student Essay Contest, for the New Student Orientation, and for many other people and memories. My time at UD was also enriched by the Office of International Student, the Energy and Environmental Policy Student Association, and the UD Chinese Student Association. I would also like to extend my thanks to my two best friends, Chi Hu and Dr. Yingjun Su for their supports and friendships. We have known each other since we were in high school in China, now more then 10 years past we are still best friends. I would like to thank them for being supportive throughout my dissertation writing and for chatting with my online when I felt my progress was too slow. Their love and caring made me strong, even during tough times in my Ph.D. pursuit. Last but not the least, I am deeply thankful to my parents. Through their unconditional love, patience, support and unwavering belief in me, I’ve been able to complete his long dissertation journey. My parents have greatly influenced me more ways than one. My father is always a role model for me. He is caring, passionate and strong. He was born in a very poor family in rural China, but because he studied so hard, he became the first batch of university students after the Great Cultural Revolution. Being a university student in China at the time was rare, and what’s more, he was the youngest among all his classmates. After school, he worked so hard and was dedicated to our family. One of the most important lessons my father taught me

vi was to work hard for the things that I aspire to achieve. The dedication and persistence he has for his life was contagious and motivational for me, even during the toughest time of my Ph.D. study. My mother is very caring and encouraging. She always gives good advices and is also a good listener. She has been great supporter and has unconditionally loved me during my good and bad times. She has faith in me even I failed. These past six years have not been an easy ride, for her and me. I truly thank her for being on my side, even when I was depressed and irritable. This last word of acknowledgement I have saved for my dear husband Dr. Zhixiang Tong, who has been with me all these years and has made them the best years of my life. He is my biggest fan and supporter. He has taken care of everything I needed without complaints, so I could just focus on my writing. He has been patiently waited many hours while I worked on my dissertation. At the same time, he has also given me so many beautiful memories throughout this journey. I could not have finished this journey without him by my side. Thank you.

vii TABLE OF CONTENTS

LIST OF TABLES ...... xiv LIST OF FIGURES ...... xviii ABSTRACT ...... xxi

Chapter

1 INTRODUCTION ...... 1

1.1 Modern Energy Access ...... 1

1.1.1 Definition and Importance of Modern Energy Access ...... 1 1.1.2 Status of Global Modern Energy Access ...... 4 1.1.3 Status of Modern Energy Access in China ...... 9

1.2 Providing Modern Energy Access with Renewable Energy ...... 15

1.2.1 Synergy between Renewable Energy and Energy Access ...... 15 1.2.2 Renewable Energy for Modern Energy Access in China ...... 16 1.2.3 Problems of Renewable Energy Development in China ...... 18

1.3 Research Objectives ...... 20 1.4 Research Questions ...... 22 1.5 Dissertation Outline ...... 23

2 LITERATURE REVIEW AND SIGNIFICANCE OF THIS STUDY ...... 26

2.1 Key Observations from the Existing Literature on Renewable Energy for Rural Development ...... 26

2.1.1 Renewable Energy for Sustainable Rural Development: An Overview ...... 27 2.1.2 Economic Perspective ...... 30 2.1.3 Social Perspective ...... 38 2.1.4 Environmental Perspective ...... 43

2.2 Conclusion of Literature Review and Significance of this Study ...... 45

viii 3 CONCEPTUAL FRAMEWORK AND RESEARCH METHDOLOGY ...... 49

3.1 Conceptual Framework ...... 49 3.2 Research Methodology ...... 52

3.2.1 Selection of Case Study Region and Renewable Energy Options 54 3.2.2 Phase 1 – Resource Potential Analysis ...... 55 3.2.3 Phase 2 – Energy Analysis ...... 56 3.2.4 Phase 3 – Sustainability Analysis ...... 60

4 PROFILE OF GUIZHOU PROVINCE ...... 64

4.1 Background of Guizhou Province ...... 64

4.1.1 Geography ...... 64 4.1.2 Population ...... 65 4.1.3 Economy ...... 66

4.2 Access to Electricity in Guizhou Province ...... 70

4.2.1 Individual Households in Areas without Electrical Services ...... 70 4.2.2 Individual Households in Areas without Adequate Electrical Services 70

4.3 Access to Clean Cooking Fuels in Guizhou Province ...... 73

5 CASE STUDY OF SOLAR HOME SYSTEMS IN GUIZHOU PROVINCE 77

5.1 Overview of Solar Home Systems ...... 77 5.2 Solar Resource Potential in Guizhou Province ...... 80

5.2.1 Overview of Solar Resource in China ...... 80 5.2.2 Overview of Solar Resource in Guizhou Province ...... 82 5.2.3 Potential Solar Home System Markets in Guizhou Province ...... 83

5.3 Energy Analysis of Solar Home Systems in Guizhou Province ...... 87

5.3.1 An Overview of RREAD for Energy Analysis ...... 88 5.3.2 Sizing of Solar Home Systems ...... 89 5.3.3 Energy Output of Solar Home Systems ...... 96 5.3.4 Reliability of Solar Home Systems ...... 99

5.4 Economic Analysis of Solar Home Systems in Guizhou Province ...... 102

ix 5.4.1 Overview of RREAD for Economic Analysis ...... 102 5.4.2 Preparation of Cost Stream ...... 104 5.4.3 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) ...... 106 5.4.4 Comparison with Competing Diesel Engine Generator Systems111

5.4.4.1 Sizing of Diesel Engine Generators ...... 112 5.4.4.2 Energy Analysis of Diesel Engine Generators ...... 115 5.4.4.3 Economic Analysis of Diesel Engine Generators ...... 117 5.4.4.4 Comparison of Cost-effectiveness between Solar Home Systems and Diesel Engine Generators ...... 122

5.4.5 Sensitivity Analysis of Solar Home Systems in Guizhou Province 125 5.4.6 Comparison with Previous CEEP Work ...... 130

5.5 Social Analysis of Solar Home Systems in Guizhou Province ...... 132 5.6 Environmental Analysis of Solar Home Systems in Guizhou Province 135 5.7 Potential Challenges Facing Solar Home System Development in Guizhou Province ...... 137

5.7.1 Energy Challenge ...... 137 5.7.2 Cost Challenge ...... 138 5.7.3 Financing Challenge ...... 139 5.7.4 Awareness Challenge ...... 141 5.7.5 Policy Challenge ...... 142

5.8 Conclusion of Solar Home Systems in Guizhou Province ...... 143

6 CASE STUDY OF HOUSEHOLD BIOGAS DIGESTER SYSTEMS IN GUIZHOU PROVINCE ...... 144

6.1 Overview of Household Biogas Digesters ...... 144 6.2 Optimum Conditions for Biogas Production in Guizhou Province ...... 148

6.2.1 Temperature ...... 148 6.2.2 Carbon/Nitrogen (C/N) Ratio ...... 153

6.3 Feedstock for Biogas Production in Guizhou Province ...... 155

6.3.1 Crop Residues ...... 155 6.3.2 Animal Manures ...... 160

6.4 Energy Analysis of Household Biogas Digesters in Guizhou Province 164

x 6.4.1 Overview of ABEPE Model for Energy Analysis ...... 164 6.4.2 Energy Output and Potential Household Biogas Digester Markets in Guizhou Province ...... 166

6.5 Economic Analysis of Household Biogas Digesters in Guizhou Province ...... 174

6.5.1 Overview of RREAD for Economic Analysis ...... 174 6.5.2 Preparation of Cost Stream ...... 174 6.5.3 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) ...... 179 6.5.4 Comparison with Alternative Cooking Methods ...... 183

6.5.4.1 Comparison with LPG-based Cooking ...... 183 6.5.4.2 Comparison with Coal and Biomass-based Cooking . 186

6.5.5 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province ...... 191 6.5.6 Study Comparison with Previous CEEP Work ...... 196

6.6 Social Analysis of Household Biogas Digesters in Guizhou Province . 198

6.6.1 Reduces Expenditure on Fuels ...... 198 6.6.2 Reduces Time Spent on Collecting Fuels for Cooking ...... 199 6.6.3 Improves Gender Equity ...... 201 6.6.4 Provides Valuable Byproducts (Fertilizer) ...... 202

6.7 Environmental Analysis of Household Biogas Digesters in Guizhou Province ...... 204

6.7.1 Reduces Indoor Air Pollution ...... 204 6.7.2 Improves Health Conditions ...... 206 6.7.3 Improves Sanitation ...... 208 6.7.4 Reduces Greenhouse Gas Emissions and Deforestation ...... 209

6.8 Potential Challenges Facing Household Biogas Digester Development in Guizhou Province ...... 212

6.8.1 Lagged Development ...... 212 6.8.2 Energy Challenge ...... 214 6.8.3 Financing Challenge ...... 215 6.8.4 Maintenance Challenge ...... 216 6.8.5 Awareness Challenge ...... 218 6.8.6 Policy Challenge ...... 218

xi 6.9 Conclusion of Household Biogas Digesters in Guizhou Province ...... 219

7 BUILDING AN INTEGRATED RENEWABLE ENERGY SYSTEM IN GUIZHOU PROVINCE ...... 221

7.1 Overview of Integrated Renewable Energy Systems ...... 222 7.2 Solar-Biogas Integrated System Architecture in Guizhou Province ..... 223 7.3 Technical Specification of Solar-Biogas Integrated Systems in Guizhou Province ...... 226

7.3.1 Solar Home System ...... 226 7.3.2 Biogas Digester Gas Engine System ...... 227

7.4 Market Potential and Energy Performance of Solar-Biogas Integrated Systems in Guizhou Province ...... 228

7.4.1 Market Potential of Solar-Biogas Integrated Systems in Guizhou Province ...... 228 7.4.2 Energy Performance of Solar-Biogas Integrated Systems in Guizhou Province ...... 231

7.5 Economic Analysis of Solar-Biogas Integrated Energy Systems in Guizhou Province ...... 234

7.5.1 Preparation of Cost Stream ...... 234 7.5.2 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) ...... 236

7.6 Non-economic Benefits of Solar-Biogas Integrated Energy Systems in Guizhou Province ...... 238 7.7 Conclusion of Solar-Biogas integrated Energy Systems in Guizhou Province ...... 240

8 CONCLUSIONS, RECOMMENDATIONS, AND SUGGESTIONS FOR FUTURE WORKS ...... 242

8.1 Conclusions ...... 242 8.2 Policy Recommendations for Off-grid Renewable Energy Systems Development ...... 245

8.2.1 Building An Institutional Framework ...... 246 8.2.2 Increasing Support for Renewable Energy R&D ...... 248 8.2.3 Investing in Renewable Energy ...... 249 8.2.4 Accessing to Financial Options ...... 249

xii 8.2.5 Improving Renewable Energy Services ...... 251 8.2.6 Strengthening Cooperation ...... 252

8.3 Suggestions for Future Works ...... 253

8.3.1 Update Data ...... 253 8.3.2 Conduct Field Trip in Guizhou ...... 254 8.3.3 Extend Current Research ...... 255 8.3.4 Expand New Dimensions ...... 256

REFERENCES ...... 257

xiii LIST OF TABLES

Table 1.1 Population without Electricity and Electrification Rates by Regions, 2014 ...... 5

Table 1.2 People Relying on Traditional Use of Biomass for Cooking by Regions, 2014...... 7

Table 1.3 People Relying on Biomass Resources as Their Primary Fuels for Cooking in China, 2013 ...... 14

Table 4.1 Main Indicators on Guizhou’s Population...... 66

Table 4.2 Poverty Population and Poverty Rate in Guizhou, 2011 – 2015...... 67

Table 4.3 Assess to Electricity in Guizhou Province...... 71

Table 4.4 Changes of Rural Households Cooking Fuels Structure in Guizhou Province, 2000 – 2010...... 76

Table 5.1 Solar Zones in China...... 80

Table 5.2 Potential Markets for Solar Home Systems in Guizhou Province...... 86

Table 5.3 Rural Household Electricity Consumption in Guizhou Province (kWh/day)...... 92

Table 5.4 Sizing Solar home Systems for Rural Household in Guizhou Province. 95

Table 5.5 Annual Net Energy Output for the 42 Potential Counties in Guizhou Province...... 97

Table 5.6 Cost Streams of Solar Home Systems in Guizhou Province...... 106

Table 5.7 Levelized Energy Costs for Solar Home Systems in the 42 Potential Counties in Guizhou Province...... 108

Table 5.8 Sizing of Diesel Engine Generators...... 114

xiv Table 5.9 Comparison of Solar Home System and Diesel Generator in Terms of Sizes...... 115

Table 5.10 Cost Comparison between Solar Home Systems and Diesel Gen-set in terms of System Cost and BOS Components Cost...... 118

Table 5.11 Factors Affecting Diesel Fuel Costs...... 119

Table 5.12 Factors Affecting Lube Oil Costs...... 121

Table 5.13 Cost Comparison between Solar Home Systems and Diesel Gen-set in terms of O&M...... 122

Table 5.14 Cost-effectiveness Comparison between Solar Home Systems and Diesel Engine Generators...... 123

Table 5.15 Sensitivity Analysis of Solar Home System in Guizhou Province...... 129

Table 5.16 Study Comparison between CEEP Previous Work and this Dissertation...... 131

Table 6.1 Distribution of Average Ground Temperature at a Depth of 1.6 m in China...... 150

Table 6.2 Average Ground Temperature at the Depth of 1.6 m for Each of the 88 Counties in Guizhou Province...... 151

Table 6.3 C/N Ratios from Different Feedstock Materials...... 154

Table 6.4 Average Residue-to-Crop Ratios for Major Crop Types in China and in Guizhou Province...... 156

Table 6.5 Residue Production of Rice, Wheat and Corn per Household for each of the 88 Counties in Guizhou Province, 2016...... 157

Table 6.6 Daily/Annual Manure Production per Animal, kg/head...... 160

Table 6.7 Manure Productions of Pig, Cattle, Sheep and Chicken per Household for each of the 88 Counties in Guizhou Province, 2016...... 162

Table 6.8 Dry Matter Content Factors for Crop Residues and Animal Manures. . 166

Table 6.9 Biogas Yield Factors for Crops Residues and Animal Manures (Dry Matter Contents)...... 167

xv Table 6.10 List of Potential Markets in Guizhou Province for Household Biogas Digester (Counties with Daily/Annual Modified Gas Production > 0.8m3/292m3 per Household)...... 170

Table 6.11 Cost Parameters for a Typical Fixed Dome 8m3 Biogas Digester in China. 178

Table 6.12 Levelized Energy Costs (LCOE) for Household Biogas Digester in the 56 Potential Counties in Guizhou Province...... 181

Table 6.13 Cost Parameters for LPG Based Cooking...... 184

Table 6.14 Cost Comparison between Household Biogas Digester and LPG- Based Cooking...... 185

Table 6.15 Factors Considered when Calculating the Annual Fuel Cost of Coal. .. 187

Table 6.16 Cost Parameters for Coal-based Cooking...... 188

Table 6.17 Cost Comparison between Household Biogas Digester and Coal- Based Cooking...... 189

Table 6.18 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province...... 195

Table 6.19 Study Comparison between Previous CEEP Work and this Dissertation...... 197

Table 6.20 Pollutants for Various Types of Fuels Burned at Households in Guizhou Province...... 205

Table 6.21 GHG Emission Factors by Fuels...... 210

Table 6.22 GHG Emission Reduction by Energy Substitution of Biogas in Rural China, 1991 – 2005 (Gg CO2-eq)...... 211

Table 7.1 Technical Specifications of Solar Home System in the Solar-Biogas Integrated System in Guizhou Province...... 226

Table 7.2 Technical Specifications of Biogas Digester Gas Engine System in the Solar-Biogas Integrated System in Guizhou Province...... 228

Table 7:3 Renewable Energy Production from the Candidate Solar-Biogas Integrated System Counties in Guizhou Province...... 232

xvi Table 7.4 Adjusted Renewable Energy Production from the Candidate Solar- Biogas Integrated System Counties in Guizhou Province...... 234

Table 7.5 Cost Parameters for Solar-Biogas Integrated Systems...... 235

Table 7.6 Levelized Energy Costs (LCOE) Comparison...... 236

Table 7.7 Non-Economic Benefits of Solar-Biogas Integrated Energy Systems and Individual Renewable Energy Systems...... 239

xvii LIST OF FIGURES

Figure 1.1 Access to Electricity Around the World. Source: World Bank, 2017...... 6

Figure 1.2 Access to Clean Cooking Facilities Around the World. Source: World Bank, 2017...... 8

Figure 1.3 Precedent of Household Electrification in Selected Countries. Source: He & Victor, 2017...... 10

Figure 1.4 Distribution of Rural Households Using Biomass as Primary Cooking Energy in China. Source: World Bank, 2013...... 13

Figure 1.5 Dissertation Outline...... 25

Figure 2.1 Impacts of Renewable Energy on Rural Sustainable Development...... 29

Figure 3.1 Theoretical Framework of this Study...... 51

Figure 3.2 Methodology Flow Chart...... 53

Figure 3.3 Overview Structure of RREAD to Calculate the Energy Performance of Solar Home System...... 58

Figure 3.4 Overall Structure of ABEPE to Calculate the Energy Performance of Household Biogas Digester...... 60

Figure 3.5 Overall Structure of RREAD to Calculate the Economic Performance of Renewable Energy Systems...... 61

Figure 4.1 Map Showing the Location of Guizhou Province in China...... 65

Figure 4.2 Per Capita Disposable Income of National Average and Guizhou, 2015 (unit: CNY). Source: National Bureau of Statistics, 2016; Guizhou Bureau of Statistics, 2016...... 68

Figure 4.3 Per Capita Disposable Income of National Average and Guizhou, 2011 – 2015 (unit: CNY). Source: National Bureau of Statistics, 2016; Guizhou Bureau of Statistics, 2016...... 69

xviii Figure 4.4 The Distribution of Rural Households Mainly Using Solid Fuels for Cooking in China. Source: Tang & Liao, 2014...... 75

Figure 5.1 Major Components of a Solar Home System...... 78

Figure 5.2 PV Cell, Module and Array. Source: Department of Energy, 2016...... 79

Figure 5.3 Average Annual Total Sunshine Hours across China. Source: CMA Wind and Solar Energy Resource Center, 2011...... 82

Figure 5.4 Annual Solar Hours of Guizhou Counties...... 85

Figure 5.5 An Overview of RREAD Energy Analysis for Solar Home System...... 89

Figure 5.6 An Example of Weining County in terms of its Monthly Net Energy Output...... 100

Figure 5.7 An Example of Weining County in terms of its Monthly Energy Shortfall Days...... 101

Figure 5.8 Overview Structure of RREAD to Calculate the Economic Performance of Renewable Energy System...... 103

Figure 5.9 LCOE Comparison between Solar Home Systems and Diesel Engine Generators (unit: $/kWh)...... 124

Figure 5.10 Sensitivity Analysis of Solar Home Systems in Guizhou Province...... 129

Figure 6.1 Typical Fixed-dome Biogas Digesters in China. Source: FAO, 2017. . 145

Figure 6.2 Typical Floating Drum Biogas Digesters in India. Source: FAO, 2017.147

Figure 6.3 Typical Plug Flow Biogas Digesters. Source: FAO, 2017...... 148

Figure 6.4 Distribution of Average Ground Temperature at a Depth of 1.6 m in China. Source: Chen et al., 2010; Chen et al., 2013...... 150

Figure 6.5 Flow Diagram Describes the Steps of “ABEPE” Model in this Study. 166

Figure 6.6 Potential Markets in Guizhou Province for Household Biogas Digester (Counties with Daily/Annual Modified Gas Production > 0.8m3/292m3 per Household)...... 173

Figure 6.7 LCOE Comparison between Household Biogas Digester and LPG for Cooking (unit: $/m3)...... 186

xix Figure 6.8 LCOE Comparison between Household Biogas Digesters and Coal for Cooking (Unit: $/m3)...... 190

Figure 6.9 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province...... 195

Figure 7.1 Schematic Diagram of Solar-Biogas Integrated Systems...... 226

Figure 7.2 Steps for Identifying the Candidate Counties for Integrated Solar- Biogas Systems in Guizhou Province...... 230

Figure 8.1 Key Policy Options for Off-grid Renewable Energy Development in Guizhou Province...... 246

xx ABSTRACT

Access to reliable electricity and clean cooking facilities is crucial to human well-being and to a country’s economic development (IEA, 2016). These two forms of modern energy services are essential for providing basic human needs such as clean water, sanitation and healthcare, and for reducing poverty (IEA, 2016). Over the past two decades, China has provided hundreds of millions of rural people with access to these two forms of modern energy services. Despite the accomplishments, still many people in China have no access to electricity, and more than 1/3 of China’s population relies on biomass for cooking (NEA, 2016; IEA, 2016). Finding appropriate ways to provide modern energy services to these populations has been a key issue for Chinese government. To serve this aim, this dissertation examines off-grid renewable energy options for rural electrification and clean cooking services in rural China. A lot of work has been done in the area of providing modern energy services by using off-grid renewable energy technologies such as solar homes systems and household biogas digester systems. For example, many studies that have focused on rural electrification indicated that solar home systems can meet the lighting and other basic electricity needs for users in rural areas (Byrne et al., 2001; Kumar & Zubair, 2012; Kamalapur & Yaragatti, 2011; Stojanovski et al., 2017; Feron, 2016; World Bank, 2016). And studies of rural cooking have revealed that a typical small-scale digester system is an essential technology for many rural households, providing a reliable source of cooking fuel (Usack et al, 2014; Rajendran et al., 2012; Tucho & Nonhebel, 2015; Amare, 2015; Raha et al., 2014; Xia, 2013). However, none of the

xxi above-mentioned research examines off-grid renewable options for rural energy needs in an integrated manner. In addition, studies of today have seldom mentioned of ability of off-grid renewable systems to deliver services that will provide rural households with non-economic benefits. For example, Byrne et al. (2001) calculated the levelized costs of stand-alone PV systems for rural off-grid users in Xinjiang and Qinghai provinces. And a more recent study by IRENA (2016) studied the economic impacts of solar homes systems on rural households in Africa. In addition, studies of biogas digester systems have concluded that biogas digesters are economically more efficient than traditional cooking fuels like coal, wood and LPG and they could cause annual savings for rural communities (Yasar et al., 2017; Perez et al., 2014; Ding & Li, 2013; Usack et al., 2014; Xia, 2013). But none of these authors have mentioned about the non-economic benefits that off-grid renewable systems bring to rural households. Certainly there are non-economic benefits from lighting, TV, and clean cooking powered by solar home systems and household biogas digester systems. They may improve rural households’ social activities, reducing time spent for cooking, as well as mitigating greenhouse gas emissions. However, the existing literature is far more concerned with economic than non-economic benefits, and it does not offer a strong case that large non-economic benefits could be obtained from renewable energy. To fill the identified research gaps, this dissertation develops an integrated approach to off-grid renewable energy systems for modern energy access in the context of rural China. This integrated approach is to utilize solar and biogas technologies to meet the electricity and cooking fuel demands of rural households in China. In addition, both economic and non-economic benefits of solar and biogas off- grid technologies are assessed. This integrated approach is carried out in three phases.

xxii The first phase is an evaluation of solar and biomass resources. Given the resource assessment, the second phase is an analysis of the energy performances of off-grid renewable energy systems (a solar home system of array capacity of 520W, a household biogas digester system of 8m3 and an integrated system that combines those two resources) to be operated in rural China. And the last phase involves conducing a comprehensive assessment of sustainability performance of renewable energy options from three aspects, namely economic, social and environmental. To carry out the resource evaluation and energy value analysis, a CEEP- developed simulation tool model, Rural Renewable Energy Analysis and Design Tool (RREAD), and an Animals Database for Energy Potential Estimation (ABEPE) model created by Batzias et al. (2005) are used to evaluate the energy performances of solar home systems and household biogas digesters in an integrated manner. To conduct the economic assessment of renewable energy utilization in rural China, this dissertation further expands the methodology developed at CEEP, employing RREAD to examine the levelized cost of energy (LCOEs) of off-grid renewable systems in comparison with their competing conventional energy systems. In addition, sensitivity analyses are performed on a number of variables (such as discount rate, module cost, energy output, etc.) to discover the extent to which they affect the renewable energy systems’ economics. Finally, qualitative analyses are applied to examine the non-economic benefits that off-grid renewable energy systems bring to rural households. As an integrated approach to off-grid renewable energies, this dissertation provides better policymaking guidance than existing non-integrated approaches when addressing rural energy needs.

xxiii Chapter 1

INTRODUCTION

1.1 Modern Energy Access

1.1.1 Definition and Importance of Modern Energy Access Energy is fundamental to generating prosperity. It is the golden thread that connects economic growth, social equity, and environmental sustainability (World Bank, 2000; United Nations, 2000; United Nations, 2004; UNDP, 2003). Enabling access to modern, affordable and clean energy for people around the world is often referred as an over-riding challenge faced by every country on its road to a sustainable future (IEA, 2016). For developing countries, the access to modern energy services has fundamental benefits in terms of reducing poverty, promoting economic development, improving health and increasing productivity (IEA, 2016). So according to IEA, “if the vicious circle of energy poverty and human under-development is to be broken, governments must act to improve the availability and affordability of modern energy services” (IEA, 2004; UN, 2012). Although there is no internationally agreed definition about modern energy access, usually modern energy includes three forms of energy, and each of them provides significant benefits to economic and social development (IEA, 2016):

 Minimum level of electricity for powering lights and appliances in the households and public facilities such as hospitals, schools and government offices;

1  Safer, less polluting and more sustainable cooking and heating fuels and stoves;

 And mechanical power from either electricity or other forms of energy sources that enables productive economic activity such as agriculture, textile and other industries. Due to situation in China and data constraints, this dissertation focuses only on two types of them: the access to electricity and to a relatively safe, clean and sustainable means of cooking in rural China. Access to modern energy is vital to a country’s economic development and prosperity. In a country, especially in a developing country, access to reliable and affordable electricity and clean cooking fuels are fundamental to improving health and reducing poverty, enhancing productivity and promoting economic growth. This is because access to modern energy will provide people with, better sanitation, cleaner water and improved healthcare condition, and greater development opportunities through means of clean and efficient lighting and cooking services. Modern energy provides the poor great benefits in various ways. Access to electricity, according to IEA, involves specific minimum electricity consumption of a household, the amount varies from rural to urban households (IEA, 2016). Usually in the rural setting, the household consumption level is set at 250 kWh per year, which could provide for the use of a floor fan, a mobile telephone and two compact fluorescent light bulbs for about five hours per day (IEA, 2016). Electricity provides lighting, thus it can extend the day and hours for people to work and study. Electricity also provides lighting for household appliances that opens up new ways of communication, entertainment, and information exchanging. In addition to these

2 benefits, increased access to electricity can also increase a country or a households’ productivity and the quality of its products. For example, electricity enables water pumps for crops, thus resulting in less manual labors for watering. Also refrigerator enables food and medicine to be stored in cooler conditions thus enhances food and medicine security. The definition of access to clean and sustainable cooking facilities includes the facilities that emit fewer pollutants, and that are more environmental friendly and energy efficient than the traditional cook facilities that are currently used in developing countries. In this sense, these facilities mainly refer to biogas digesters, liquefied petroleum gas (LPG) stoves and improved biomass cook stoves (IEA, 2016). The most direct benefits from using modern cooking facilities are avoided exposure of indoor air pollution and reduced time of women and children collecting fuel wood and cooking. Currently, cooking devices in the poorest households are biomass stoves with not chimneys or hoods. The adverse consequences of using these facilities are the pollution levels inside the households are many times higher than the outside. Each year, 4.3 million premature deaths are caused by household air pollution due to inefficient biomass combustion (IEA, 2016). Modern cooking facilities have the potential to reduce the exposure of people to cooking pollutants released from the traditional biomass significantly, thus help to avoid premature deaths. In addition, for households that rely heavily on traditional biomass for cooking, women and children are usually responsible for fuel wood collecting. This is a time and labor-consuming task. Use of modern cooking facilities can also reduce their burdens of spending time and traveling long distances to gather fuel wood.

3 There is a growing consensus now that a close correlation existing between level of household income and level of access to modern energy. In general, a country with a large population living on an income of less than $2 per day tends to have low electrification rates and high rates of people relying on traditional biomass for cooking (IEA, 2004). Poor people are trapped in an “energy-poverty” nexus, where the lack of modern forms of energy affects their economic productivity, income earning opportunity, job creation, and living conditions. This will then leave these people in poverty, and in turn prevents them from buying modern energies that could help alleviate their poverty. By contrast, improved access to electricity and clean cooking facilities enables development of economic activities, education access, gender equality and health conditions. For example, household biogas digesters reduce the amount of traditional fuel used which is a direct cash saving, and they also alleviate the burden placed on women and children in fuel collection. Also, access to electricity enhances food supply and food security through irrigation, water pumping and refrigeration. In addition, when poor households gain access to modern energy services, they are able to conduct more advanced value-added activities that enable them to escape poverty. Today millions of people in the world will continue to be without these services, thus special attention should be paid to achieving universal access to electricity and clean cooking facilities for those communities.

1.1.2 Status of Global Modern Energy Access Assess to Electricity Today, an estimated 1.2 billion people – 16% of the world’s population – still did not have the access to electricity in 2014 and 1.5 billion more people have unreliable services (IEA, 2016). Among all five continentals, Africa has the least rate

4 of electrification, at 45% and highest number of people without access to electricity, at 634 million which more than 50% of world’s population that don’t have the electricity. Among those people in Africa, 99.6% are from Sub-Saharan African countries. Most of the rest people who don’t have the access to electricity are from developing Asia, including 244 million in India and 60 million in Bangladesh (IEA, 2016). Nearly 80% of those without access to electricity live in rural areas. Efforts of expanding access to electricity in developing countries over the past two decades have been strong. Between 1990 and 2008, almost 2 billon people gained access to electricity (Pachauri et al., 2012). In the central scenario of the World Energy Outlook 2016 (the New Policies Scenario), the number of people lacking access to electricity will drop to 784 million in 2030 and further drop to 541 million in 2040 (IEA, 2016).

Table 1.1 Population without Electricity and Electrification Rates by Regions, 2014

Population without Electrification Urban Rural electricity rate electrification electrifica Region rate tion rate millions % % %

Developing countries 1,185 79% 92% 67%

Africa 634 45% 71% 28% North Africa 1 99% 100% 99% Sub-Saharan Africa 632 35% 63% 19% Developing Asia 512 86% 96% 79% China 0 100% 100% 100% India 244 81% 96% 74% Latin America 22 95% 98% 85%

Middle East 18 92% 98% 78% Transition economies & 1 100% 100% 100% OECD

5 WORLD 1,186 84% 95% 71% Source: IEA, 2016.

Figure 1.1 Access to Electricity Around the World. Source: World Bank, 2017.

Access to Clean Cooking Facilities Overall, more than 2.7 billion people worldwide – 38% of the world’s population – have relied on the traditional use of solid biomass for cooking, including wood, charcoal, tree leaves, crop residues and animal dug, used in inefficient cooking stoves or in open fires in poor ventilation conditions (IEA, 2016). Similar to the electrification status, sub-Saharan Africa and developing Asia are again the dominants of the total populations. In most countries, the lack of clean cooking facilities is a problem primarily in rural areas; however, many poor people in urban areas also rely on traditional biomass for cooking, particularly in sub-Saharan Africa. In sub-Saharan Africa, only 19% of people use modern fuels as their primary cooking fuel (IEA, 2016). India also has the highest population relying on the traditional use of biomass.

6 In India, 819 million people – 63% of its total population – rely on solid fuels (IEA, 2016). Unlike electricity access, efforts of expanding access to clean fuels have been slow in the past decades. According to IEA’s New Policies Scenario, more than 2.5 billion people are projected to remain without access to clean cooking fuels or stoves in 2030 and 2.1 billion still remain without it in 2040 (IEA, 2016).

Table 1.2 People Relying on Traditional Use of Biomass for Cooking by Regions, 2014.

Population Percentage of population relying on relying on traditional use of traditional use Region biomass of biomass

% millions Developing countries 2,742 49% Africa 793 69% North Africa 1 0% Sub‐Saharan Africa 792 81% Developing Asia 1,875 50% China 453 33% India 819 63% Latin America 65 14% Brazil 10 5% Middle East 8 4% WORLD 2,742 38% Source: IEA, 2016

Figure 1.2 Access to Clean Cooking Facilities Around the World. Source: World Bank, 2017.

To draw global attention to the energy access problem worldwide, in 2011, UN Secretary-General Ban Ki-moon launched the Sustainable Energy for All initiative for making sustainable energy for all a reality by 2030. The initiative is focused on three objectives to be achieved by 2030 (UN, 2016):

 Ensure universal access to modern energy services;  Double the global rate of improvement in energy efficiency;  Double the share of renewable energy in the global energy mix. These three objectives provide clear directions towards universal energy access. In addition, they support each other in many ways. For example, increasing implementation of renewable energies can provide modern energy services to remote rural households where extending traditional electrical grids are expensive and

8 impractical. Improving efficiency of electrical devices requires less energy and thus reduces the amount of power that needed to support them. In all, achieving these three objectives will help achieving sustainable development in the long run.

1.1.3 Status of Modern Energy Access in China Access to Electricity China represents a very successful story of electrification. For over 50 years, Chinese government has dramatically expanded its power supply, including to rural areas. Although more than 1.2 billion people in the world still have no access to electricity today, China, as the most populous country in the world, shows an impressive record – with almost 100% of its population has been provided with electricity today. The development of rural electrification in China has expanded three phases (Pan, et al., 2006). The first phase was from 1949 to 1977: rural electrification in China was slow due to lack of capital and technology. As a result, only areas around big cities were covered by national grids. The second phase was from 1978 to 1997 and it was a rapid expansion. This phase recognized the importance of rural electrification for sustainable development and a major power management reform was adopted, transferring electricity management from central planning to local governments, giving local authorities more autonomy in development decisions. The third phase was from 1997 to today. During this stage, power systems in China have gone through innovation and reform. National electrical grids have been extended from urban to rural areas. In addition, off-grid options such as solar home systems and wind systems are utilized to provide electricity to remote and dispersed areas that national grids are unable to reach.

9 Remarkable accomplishments have been achieved after those three phases. As shown in the figure below, there is an exponential growth in China’s electrification rates since 1970. By 2010, 90% of China’s population has accessed to electricity, this was increased from only 50% in 1970 (He & Victor, 2017). This rate is just as high as well developed countries such as U.K. and the U.S., and it shows a striking contrast to India – as also one of the most populous countries in the world, its electrification rate now is fewer than 65%. Until of today, China has almost achieves full electricity access with only less than 1 million people still don’t have the access to electricity (He & Victor, 2017).

Figure 1.3 Precedent of Household Electrification in Selected Countries. Source: He & Victor, 2017.

Favorable policies, programs and initiatives are dedicated to the rapid expansion of electricity supply in China. The two most prominent initiatives for rural electrification in China are the China Township Electrification Program that was from

10 2001 to 2005 and the China Village Electrification Program that was from 2005 to 2010. As the largest of its kind in the world, the China Township Electrification Program helped to electrify 1,000 townships in China, while the China Village Electrification Program helped to further electrify 3.5 million households in those 1,000 townships (NREL, 2006; NREL, 2011). Moreover, in 2013, National Energy Administration (NEA) issued the China’s Three-Year Plan (2013-2015) for Solving Electrification Problem in China, aiming to provide electricity to all the remaining 3 million unelectrified population in China by the year 2015 (NEA, 2014). With the joint efforts from central and local governments, an additional 2.5 million people have acquired electrical services between 2013 and 2015, making China a country that achieves almost 100% electrification rate (NEA, 2014). Despite the great success, today there are still 237,800 people in China don’t have the access to electricity, and the government intends to electrify these people through decentralized systems by 2020 (NEA, 2015). Those unelectrified population are primarily locate in villages and farming areas in the western regions and islands in the eastern coastal areas (NEA, 2015). These areas are characterized by dispersed rural settlements and they are far from loan centers and from existing national grids. However, those areas are rich in renewable resources (solar, hydro and wind), which makes renewable electricity a promising option to help those areas achieving full electrification by 2020.

Access to Clean Cooking Facilities Although China has almost achieved the universal electricity access, clean cooking remains a major problem in China. Today, many people, especially poor people in China continue to use traditional stoves that burn solid fuels. Biomass and coal are the main types of solid fuels used in China, and the regional usage rates of

11 each depend on local supplies. In rural areas, the least dependence on biomass for cooking is found in the Eastern regions, such as in Beijing, Tianjing and Shanghai as they are the most developed municipalities in China. The Northeast region, such as Heilongjiang, Jilin, and Liaoning, has the most households rely on biomass. For example, 93% of households in Jilin rely on biomass for their cooking demands, while only 15% in Beijing (World Bank, 2013). In addition, western province such as Sichuan, Shandong, and central province of Henan, also have significant amount of rural households that rely mainly on biomass for cooking. Of all the 34 provinces and special districts in China, 22 of them rely on solid fuels for cooking more than 90% of their population, of which the top 6 include Henan, Hunan, Anhui, Hebei, Shandong and Sichuan, with Henan and Hunan show the highest proportions, at 97% each (World Bank, 2013).

Figure 1.4 Distribution of Rural Households Using Biomass as Primary Cooking Energy in China. Source: World Bank, 2013.

According to IEA, there are more than 450 million in China today – 33% of its total population – still rely on traditional biomass resources as their primary fuel for cooking (IEA, 2016), and only a few economically developed provinces in the East are found have less dependence on solid fuels (World Bank, 2013). Based on the national census data in China, the fuels used for cooking varies significantly between rural and urban regions. In rural areas, households rely heavily on biomass for cooking – about 58.6% of its population use biomass to meet their cooking demands compared with only 3.5% is in urban areas (Tang & Liao, 2014). In addition, the proportion of urban households using clean energy (such as electricity and gas) as their primary fuels for cooking reaches 90.3%; conversely, the proportion in rural areas is only 23.2% (IEA,

13 2016). Although evidences have shown that modern energy such as electricity and gas demands have been increased in rural areas of China since 1990, their energy pattern stayed the same – solid fuels in the form of crop residues, fuelwood and coal are still the dominant energy types for rural households energy demand and they are likely to be still dominant in the near future. Without any new energy policies intervention, Mainali et al. estimated, that 24% of the rural population in China would still depend on solid fuels for their cooking needs by 2030 (Mainali & Ngai, 2012).

Table 1.3 People Relying on Biomass Resources as Their Primary Fuels for Cooking in China, 2013

Total population Rural population Urban population % Million % Million % Million China 33 450 58.6 428 3.5 22 Source: IEA, 2016; Tang & Liao, 2014.

This reliance on inefficient cook stoves and fuels leads to a wide variety of problems. First, cooking by solid fuels create sever indoor air pollution. Many rural families who rely on solid fuels for cooking have fires running a lot of time at their homes, creating massive amounts of smoke at home. Oftentimes, exposing to the indoor air pollution can cause fatal diseases such as respiratory infections, lung cancer and reduced lung function. The Global Burden of Disease Study 2010 reveals that each year about 4 million people die prematurely due to exposure to air pollution from use of solid fuels for cooking and of whom 1.04 million are in China (Lim, 2012). This number is equivalent to the premature deaths caused by the atmospheric particulate matter (1.23 million) and it accounts for 12.5% of all premature deaths in China (Lim, 2012). In rural South China, scientific research has shown that solid fuels are the probable risk factors for chronic obstructive pulmonary disease in the region

14 (Liu, 2007). Second, solid fuels require extra workload to acquire. In many cases, if a rural family is harvesting biomass instead of buying kerosene from a local market, then the family members, most likely the women and children will spend 2 to 4 hours a day of collecting firewood. This will in the long-term affect women and children’s health conditions and education opportunities. Third, burning solid fuels cause severe environmental problems that leads to the regional and national climate change. Of all these problems, it is clear that some actions must be taken to tackle them.

1.2 Providing Modern Energy Access with Renewable Energy

1.2.1 Synergy between Renewable Energy and Energy Access Renewable energy, according to Renewable Energy Association, refers to a broad range of energy sources, including solar, wind, biomass, geothermal and small hydro that are sustainable and can be used indefinitely without degrading the environment (Renewable Energy Association, 2004). Worldwide, nearly 1.2 billion people today do not have access to electricity and 2.7 billion people do not have access to clean cooking facilities, this presents a strong need for the increased development of renewable energy. In terms of electricity access, according to International Renewable Energy Agency, half of the universal electricity demand to 2030 could be met with decentralized renewable electricity (IRENA, 2016). Moreover, many areas that are now without electricity but with abundant solar and other renewable resources, renewable options like solar PV, wind and small hydro have been shown cost- competitive than the existing traditional diesel or kerosene based systems, and these technologies are even cheaper than extending the grid in those areas. In terms of clean

15 cooking facilities, switching from traditional inefficient cook stoves and fuels to improved cook stoves or household biogas digesters could help to reduce deforestation due to less use of solid fuels and to save thousands of lives a year due to reduced indoor air pollution. In addition, clean cook stoves can contribute substantially to a country’s sustainable development and to its energy mix. There are now many successful examples of utilizing renewable energy as solutions to improve modern energy access worldwide. For example, Bangladesh represents a very successful story in terms of using standalone solar home systems to offer more access to electricity. At present, more than 50,000 such systems are sold each month and 2 million systems have been installed in the country (Alam & Bhatacharyya, 2016). This shows the cost of such systems are dropping dramatically and their uptake is rising rapidly. In India, by March 2014, 4.75 million biogas plants has been installed in the country with a further target of 1.1 million to be installed during 2014 to 2015 (Ministry of New and Renewable Energy, 2016). And these systems have been proved to be the best options to help rural households becoming self-dependent for cooking gas in India. They also provide solutions to protect households from problems of indoor pollution and while saving them time and expenses on collecting the solid fuels.

1.2.2 Renewable Energy for Modern Energy Access in China Since 1990s, Chinese government has been trying to find alternative ways to provide energy access to its people. In terms of electricity access, because grid extension to off-electricity areas where are remote and dispersed is very expensive, renewable energy technologies have emerged as an alternative in meeting the needs of the rural people of cost-effective and reliable electricity. China introduced its first

16 rural electrification project, the Brightness Program, during 1996 World Solar Peak Conference in Zimbabwe. The program aimed at providing 23 million people in remote areas in five provinces (Gansu, Qinghai, Inner Mongolia, Tibet and Xinjiang provinces) by 2010 using renewable energy technologies like solar home systems and wind systems (NREL, 2004). This program was later scaled up to China Township Electrification Program and China Village Electrification Program in 2001 and 2005 respectively. These two programs have powered more than 1,000 townships or nearly 3.5 million people by decentralized renewables in Western China (NREL, 2011). Outside China, the US/China cooperation has focused on the application of solar home systems application in western China for its rural electrification. The cooperation started in Gansu in 1995, and it was later expanded to Qinghai and Xinjiang, providing electricity to more than 600 remote homes and schools during the course of the project (Stone, J.L. et al., 1998). In 1999, the World Bank and the Global Environment Facility launched the Renewable Energy Development Project focused on solar energy and wind power in China. The project, which closed in mid-2007, provided electricity to more than 400,000 households in 9 northwestern provinces and autonomous regions in China through PV systems (World Bank, 2001). Besides renewable technologies for electricity, technologies for clean cooking facilities such as biogas digesters have also been disseminated rapidly during the late 1990s. The increase of biogas digesters in China was motivated by the need to address the problems such as indoor air pollutions from solid fuels, lack of clean cooking fuels and facilities, water pollutions and water-borne diseases from human and animal wastes, and forest degradation due to collection of firewood for cooking. In China, by the end of 1988, only 4.7 million household biogas digesters were reported (Bond &

17 Templeton, 2011). Particularly after 1990s, there was a rapid increase of number of plants in China. By the end of 2011, the total biogas users in China has reached to 41.68 million of households, including 39.96 households with domestic biogas digesters with volumes from 6 to 10 m3 (Xia, 2013). This equals to 23% of the total rural households in China. It is estimated that in 2015, total number of households with domestic biogas digester is over 50 million (Cui, 2015). The rapid development of domestic biogas digester was mainly dedicated to the increase in government investment. With funding from central government, the annual investment in the national rural biogas program in China has reached a historical high of nearly 6 billion CNY in 2008, or roughly $863 million at 2008 exchange rate (Xia, 2013).

1.2.3 Problems of Renewable Energy Development in China Although renewable energy options such as solar PV systems and household biogas digesters have helped hundreds of millions of people in rural China in getting modern energy access, there are still some problems remained unsolved. The first problem is, even with the implementation of various programs that promote renewable energy development, there are still many people in China who could be served by it. As mentioned above, today there are more than 200,000 people in China still have no access to electricity, and even more have no access to reliable electrical services. Turning to fuels for cooking, more than 450 million people today still rely on traditional biomass for cooking. These people should not be ignored; instead, they should be paid attention with top priority in the following years in order to change their energy access situation. Second, the ability of renewable energy to meet rural households’ energy is still uncertain in China. None of existing renewable energy programs in China have

18 paid attention to the energy performances of renewable systems implemented in rural China and the households’ energy needs in a systematic way. Since energy patterns vary from household to household, from province to province, it is of necessary to determine the ability of renewable energy technologies to provide electricity and cooking services to rural households in China. In addition, the overall impacts of renewable energy on rural development in China are still not clear. People are more concerned with economic impacts of using renewables rather than non-economic impacts. For example, in China, the social and environmental benefits beyond the economic benefits of solar PV systems and household biogas digesters to rural households are not clear. In addition, rapid development of renewable systems has caused some growing pains. For example, a major concern for solar PV and household biogas digester systems in recent years is the utilization rate, or how many of these systems remain in use after installation. Evidences have shown that quite a number of systems are out of use or only use occasionally each year either because of broken parts or poor maintenance. This can severely affects the future development of renewable energy in rural areas. Obviously, this concern should be taken into account seriously when we are trying to address rural energy development problems in China. Together, these problems present great opportunities that we can further promote the development of renewable energy in China. They also show a significant need to develop a better and more-comprehensive approach to analyze, measure and assess the impacts of off-grid renewable energy options on rural energy development in China. For this aim, this dissertation develops an integrated approach to off-grid renewable energy systems for modern energy access in the context of rural China. The

19 aforementioned concerns will be addressed in this study. And the results of this study can be used as guidance for strategies to facilitate renewable energy development in rural China. The government or nonprofit organizations can also use the results to implement rural renewable energy systems in rural areas. Moreover, this study will be a good model for any future studies on renewable energies such as solar, wind and biogas, or other forms for rural development in the developing world.

1.3 Research Objectives Considering still many people in China have no access to electricity, and more than 1/3 of China’s population relies on solid fuels for cooking (NEA, 2016; IEA, 2016), finding appropriate ways to provide modern energy services to these communities has been a key issue for Chinese government. Recently, renewable energy has been emerged as an appropriate option for providing modern energy services, thus the main research objective of this dissertation is to assess the economic-social-environmental impacts of off-grid renewable energy systems on rural households in China. The impacts will be accessed from three perspectives, namely economic, social and environmental. Based on the identified impacts, this dissertation provides recommendations that could speed up the development of off-grid renewable energy technologies in rural China. Two types of renewable energies are considered in this study which are solar and biogas. Therefore, technologies analyzed in this study including a solar home system of array capacity of 520W and a household biogas digester system of 8m3. In addition, an integrated system that combines these two technologies is also discussed in this study as an option to provide electricity and cooking services for rural households simultaneously. And Guizhou province, southwestern of China, is selected as the case study region.

20 To reach the main research objective, this study is carried out in three phases. The first is a feasibility study involving an assessment of renewable resource availability in Guizhou province. The objective of this feasibility study is to assess the renewable energy potential (solar resources and biogas resources) in the case study region and then to use the resource potential to determine the energy performances of solar PV systems and household biogas systems. The second phase is to evaluate the energy performances of off-grid renewable energy systems. The objectives of this phase are: (1) to characterize the analyze the energy demand patterns in rural households in Guizhou; (2) to configure the optimal size for the solar home system and household biogas digester; (3) to calculate the daily, monthly and annually energy output from solar home systems and household biogas digesters based on their size configured; and (4) to compare the systems energy outputs with the households’ energy requirements to determine if energy shortfall happens. The third phase is to assess the sustainability performance of the off-grid renewable systems. The objectives of this assessment are: (1) to determine the levelized energy costs (LCOEs) of the systems; (2) to compare their LCOEs with their competing conventional energy systems; (3) to assess the social and environmental impacts that these systems have on rural development in China and (4) to discuss any challenges or barriers that might prevent the development of renewable energy development in rural China. Based on the analysis, the study finally offers policy recommendations. And the objective of policy recommendations is to eliminate the potential barriers and to speed up the development of off-grid renewable energy systems in rural China.

21 1.4 Research Questions To achieve the aforementioned objectives, the main research question of this dissertation is: what are the economic-social-environmental impacts of off-grid renewable energy systems on rural households in China? There is a lot of work has been done in the area of providing modern energy services by off-grid renewable technologies, however, none of the research is conducted in an integrated manner. In addition, studies of today have seldom mentioned of ability of off-grid renewable systems to deliver services that will provide rural households with non-economic benefits. That is why the research question is raised here. To answer the main research question, several different sub-questions are required to be answered as well. They include,

 What are the renewable resource potentials in the case study region? To be more specific, what are solar and biogas potentials in Guizhou province? This is an important question because the performances of the system must build upon solid understanding of resource potential, because the resources vary by location and time. Resource uncertainty may have a big influence on the economics and market situation for renewable energy. Thus, it is important to know the potential of renewables in the target area first.

 What are the energy performances of off-grid renewable systems? How the systems’ energy performances vary over a year? And can the systems’ energy outputs satisfy the energy demands of rural households? Answering these questions helps provide an understanding of systems reliability.

22  What are the sustainability performances of the renewable systems? What are the levelized energy costs (LCOEs) of these systems? How their LCOE compared with traditional energy systems that are now being used widely in rural China? What variables that have the most significant impact on the economic performance of the systems? And what are the non-economic benefits such as social, and environmental benefits that these systems can provide to rural households in China? And how their social and environmental benefits compared with other energy systems? Answering these questions provides an overall assessment of impacts of renewable energy on rural development in China.

 What are the potential barriers facing the rural renewable energy development in China? And what are the policy suggestions that could further promote these systems in rural China? And what are the additional issues that should be addressed in this study?

1.5 Dissertation Outline Based on the case study of Guizhou province, China, this study confirms that off-grid renewable energy options such as solar home systems and household biogas digester systems can be the most economical and practical way to address rural energy needs in China. The details are provided in the following chapters. In Chapter 2, a literature review on existing studies of renewable energy for rural development is presented and the significance of this dissertation is raised. Following that, Chapter 3 describes the methodology and data that are used to conduct this study. Chapter 4 presents an overview background of Guizhou province, the case study region of this

23 dissertation. Also this chapter describes the household modern energy access situation in the province in terms of access to electricity and clean cooking facilities. Chapter 5 and Chapter 6 present a case study of solar home systems and household biogas digesters in Guizhou province respectively. These two chapters follow the similar format. They first determine the solar and biogas potential in the province. Then they go on evaluating the reliability of the renewable systems by assessing their energy performances. In addition, the chapters assess the sustainability performances of the two systems from three aspects: economic, social and environmental. And their sustainability performances are compared with other conventional energy systems that are now widely being use in rural China. Furthermore, potential barriers that are facing the development of these two renewable systems in Guizhou are discussed in these two chapters. Based on the analysis from Chapter 5 and 6, chapter 7 performs an evaluation of both economic and non-economic benefits of integrated solar-biogas systems that could potentially meet households’ electricity and cooking demands simultaneously in the context of rural Guizhou. Finally, Chapter 8 concludes the findings of this study and provides policy recommendations that can help promoting renewable energy development in rural China. Also this chapter indicates the future direction of the research work towards a Ph.D.

Figure 1.5 Dissertation Outline.

25 Chapter 2

LITERATURE REVIEW AND SIGNIFICANCE OF THIS STUDY

2.1 Key Observations from the Existing Literature on Renewable Energy for Rural Development This chapter represents a literature review of studies on renewable energy for rural development. The aim of this literature review is to gain knowledge of earlier studies regarding renewable energy for rural development in China as well as in other developing countries. This contributes to a better understating of ability of renewable energy to address rural energy needs and a better understanding of impacts and benefits of renewable energy bring to the developing world. In addition, performing a literature review can help identifying research gaps and needs – which is also the motivation and significance of conducting this dissertation. This chapter summarizes the work that has been carried out in the area of renewable energy for rural development. Information on renewable energy technologies, projects and programs such as solar home systems for rural electricity and domestic biogas digesters for rural cooking in the developing world are collected,. As explained below, studies on the ability of renewable energy options to address rural energy needs are reviewed. In addition, the benefits and impacts of renewable energy for rural households are reviewed from three perspectives, namely social, economic and environmental. Studies reviewed in this chapter include scientific reports, research journal articles, book chapters, project reports, governmental and NGO publications such as

26 the World Bank Group, International Energy Agency, UN, UNICEF, and the Global Environmental Facility. The key words used to search for these studies include “sustainable development”, “renewable energy”, “rural development”, “off-grid solar home systems”, “household biogas digester systems”, etc. Only off-grid renewable energy options in developing countries are included in this study. Therefore, large scale renewable energy systems, or renewable energy development in developed countries are excluded from this study.

2.1.1 Renewable Energy for Sustainable Rural Development: An Overview Developing countries have 80% of the world’s total population but consume only 30% o global commercial energy (Martinot, 2002). As the demand of energy is continuous growing with the increase of population and livings standards, awareness is also growing about the needs to expand access to modern energy services in alternative ways. A viable solution for providing modern energy access in remote and poor rural areas is the deployment of renewable energy technologies. Renewable energy technologies, according to Renewable Energy Association, refer to technologies that utilize energy sources in ways that do not deplete the Earth’s natural resources (Renewable Energy Association, 2009). Theses sources, like solar, wind, and biogas, are sustainable so that they can be used indefinitely without degrading the environment. By exploiting these sources, renewable energy technologies can help the rural people to meet their energy demands while mitigate the negative impacts from traditional energy generation like climate change, indoor and outdoor air pollution and environmental health problems. In addition, because most of the household renewable energy systems are decentralized or off-grid, it allows those systems to meet the people’s specified energy needs in different rural areas.

27 A lot of work has been done in the area of providing modern energy services by using off-grid renewable energy technologies such as solar homes systems and household biogas digester systems. Many have argued that off-grid renewable options can serve as reliable ways to bring electricity and clean cooking services to rural households in developing countries. For example, many studies that have focused on rural electrification have indicated that solar home systems can meet the lighting and other basic electricity needs for users in rural areas (Byrne et al., 2001; Kumar & Zubair, 2012; Kamalapur & Yaragatti, 2011; Stojanovski et al., 2017; Feron, 2016; World Bank, 2016). And studies of rural cooking have revealed that a typical small- scale digester system is an essential technology for many rural households, providing a reliable source of cooking fuel (Usack et al, 2014; Rajendran et al., 2012; Tucho & Nonhebel, 2015; Amare, 2015; Raha et al., 2014; Xia, 2013). Studies have concluded that off-grid renewable energy systems bring enormous impacts and benefits to rural sustainable development. And these impacts/benefits have been recognized from three perspectives: (1) economic perspective, (2) social perspective and (3) environmental perspective. Economically, renewable energy is cost-effective in the long term, and it requires less maintenance than tis competing energy systems. In addition, it contributes to user income by providing extra energy for productivity uses. Socially, renewable technology has social benefits such as saving people time spent on daily household activities like fuel collection and cooking. As a result, people have more time for entertainment and productive activities. A better health condition is also achieved from reduced exposure to indoor air pollution from renewable energy for cooking. Moreover, renewable energy improves gender equity – by freeing women and children from daily household

28 workloads, they now can attend schools and conduct social activities. Environmentally, it is evident that renewable systems can improve rural environment. By replacing biomass, diesel, gasoline or other forms of traditional energy sources for lighting and cooking, renewable energies reduce CO2 emission and indoor air pollution levels, and improves water quality and protects forest.

Economic Impacts -- cost-effectiveness -- reliability -- productivity/users' income -- low operation and maintenance -- etc.

Environmental Impacts Social Impacts -- reduction of CO2 -- time allocation -- reduction of indoor -- health improvement air pollution -- gender equity -- water quality -- etc. -- protect forest -- etc.

Figure 2.1 Impacts of Renewable Energy on Rural Sustainable Development.

Although benefits are identified of renewable energy for rural sustainable development, drawbacks are also noticed from previous studies that might weaken the benefits and lead to a constraint for future rural sustainable development. These drawbacks include high initial costs, lack of users’ know-how, lack of maintenance, insufficient subsidies, etc. These drawbacks should also be paid with full particular

29 attention because they might hinder rural renewable energy development in the long term.

2.1.2 Economic Perspective Cost-effectiveness Economic sustainability of rural renewable energies is come from literature on the cost-effectiveness of renewable technologies to improve modern energy access in rural areas. Studies showed that renewable technologies, such as solar PV systems and household biogas digesters can be cost-effective energy solutions, especially for rural populations who don’t have the access to electricity or clean cooking facilities. For example, IRENA’s most recent solar PV report shows that solar home system is a very economical solution to the electrification challenge in Africa (IRENA, 2016). Under a conservative assumption, the annual cost for a 20W to 100W solar PV system installed in an off-grid household in Africa is between $56 to $214, while the annual energy expenditure for that same household relying traditional energy production means today is between $84 to $270 (IRENA, 2016). And Raha et al. point out household biogas digester provides low-cost fuel for cooking in India, and this is also the main reason for households to adopt biogas plants (Raha, 2014). Statistically renewable technologies are more cost-effective than conventional energy sources, however, in the real world, governments and individuals often favor more costly conventional energy sources. Subsidy to traditional energy sources is the major barrier that deteriorates the competitiveness of renewable energy technologies (Ottinger, 2005; UNEP, 2013). Globally, according to IEA, subsidy for fossil fuels is at $312 billion per year, compared to $57 billion for renewable energy (IEA, 2011). This situation is particularly obvious in many developing countries. India for instance,

30 the country has the largest use of subsidized kerosene in the world, thus making it difficult to shift from kerosene to cleaner and more efficient alternatives in India (Lam et al., 2016). And in China, subsidies to coal-fired generation were at $37.7 billion in 2014, making renewable energy hard to compete (Denjean, 2016). As a result of these favorable policies to unsustainable energy resources, cost-effective solutions such renewable energy technologies are usually blocked. The excessive subsidy on fossil fuels is not the only factor that exerts resistance to renewable system development. Numerous studies have noticed that although renewable energy systems are cost-effective in the long-term, their initial costs (particularly for solar PV systems) are high, usually beyond the affordability of rural households in developing countries (Oparaku, O.U., 2006; Adouane, 2016; Ani, 2015). Therefore, low-income households can’t afford those systems. In Ghana for example, given the low household income situation, solar home systems are only available to a salaried worker (Naah, 2015). Removing the high initial cost barrier to the development of renewable energy requires policy intervention, which means certain carefully designed financing models must be used to help the rural household to pay for the high initial cost. These models should be country and project specific, because a suitable model must depend on the country’s institutional, legal and socio- economic conditions and the types of project (Nieuwenhout, 2001). Nieuwenhout et al., Reinmuller & Adib, and Sovacool have identified four major financing models to overcome initial cost barrier to the uptake of rural renewable energy systems, and each of these models has its own pros and cons (Nieuwenhout, 2000; Reinmuller & Adib, 2002; Savacool, 2012). (1) Donation model: equipment and technologies are provided by donors with no cost. In rural El Salvador

31 for instance, solar home systems are given free (Balint, 2006). Although this model enables quick deployment, it has been seen as unsustainable because users are less involved thus they feel less responsible to the systems. (2) Loan/credit model: users need to pay for the down payment, while the rest of the cost is paid over a period of time via loans from local finance institutions. For example, in Bangladesh, Infrastructure Development Company offers a 10% down payment, 12% service charge and monthly payment scheme to consumers who would like to install a solar home system at home (Urmee, 2009). Because this model spreads cost over time, it improves access and affordability for many low-income people. (3) Subsidy model: the government pays a fixed amount of subsidy and the rest is borne by users in terms of cash or credit. In China for instance, the central government covers about 50% - 90% of the initial cost of household biogas digesters subject to different areas or regions (Zhang, 2008). This model improves poor’s access to costly renewable systems, however concerns have been raised including its complexity and a delay in getting the subsidy (Mainali & Silveira, 2012). (4) Fee-for-service model: the customers pay regular fees to energy service companies (ESCOs) for using services. In this model, users do not own the systems, instead they just pay for using them. The best experience with this model has been found in the Dominican Republic, where 3,500 solar home systems were installed from 1996-2000, about 1,700 of these on a fee-for- service base (Martinot, et al., 2000). This model provides a solution to spread the upfront cost of a renewable system over a long period, however the main challenge of this model are system maintenance and fee collection. Because the users do not own the systems, they have less incentives to take care of them.

Reliability

32 Another aspect of economic sustainability of renewable energy is reliability. In rural areas, gaining access to a reliable source of electricity or clean cooking fuel is critical for rural people to increase their livings standards. Today, while 1.2 billion people still lack the access to electricity, many more lack reliable electricity even with public grid connection (IEA, 2016). Most of these people are in Sub-Sahara African and India. Blackouts are happened during thunderstorms or for other reasons. As a result, many of these people could only enjoy electricity for a certain amount of time a day, depending on month. Agarwal etl al. point out solar home systems can provide more reliable electricity for a set load, because there is a lower likelihood for a power shortage considering solar irradiation does not experience drastic variation (Agarwal, 2014). In a study on rural electrification in India and Nepal from WRI, Rao et al. identify that households with solar home systems consume less kerosene than grid customers (Rao, 2016). And this is because the higher reliability of solar home systems then grid as a stand-alone system for lighting. Turning to cooking, many studies have shown household biogas digesters present a more reliable source of cooking fuel compared to traditional biomass. For example, in Indonesia, China and India, household biogas digesters have become an essential technology for many rural households due to their reliability as a source of cooking fuel (Usack, 2014). And in Rwanda, Hilton reports that biogas digester provides a clean, smoke free, and reliable cooking system compared to traditional wood stoves (Hilton, 2014). However, renewable energy systems’ reliability is largely dependent on supply of system replacement parts and users’ adequate knowledge of system operation. For example, the availability of spare parts is a critical success factor for solar home system in Assam, India, as the system provider was repeatedly unable to supply the

33 spare parts to the service center (Barman, et al., 2017). Also for the case of household biogas digesters, there is always a lack of spare parts due to limited funding or transportation (Kileo & Akyoo, 2014). The inability to provide replacement parts will prevent the renewable systems from working, thus compromising their reliability to the rural sustainable development. Also the reliability of renewable energy systems is depend to a great extent on user’s level of knowledge about the systems. As is known in literature, lack of basic knowledge of renewable systems is a crucial barrier for systems working properly (Rebane % Barham, 2011; D’agostino, et al., 2011). For example, in Assam, India, because most of the village solar home lighting users do not have the basic know-how about the systems, systems are found installed in places where module does not receive the solar radiation (Barman, 2017). And a case study on household biogas digesters in Mekong Delta district in Vietnam reveals that user’s know-how about the biogas technology is an important factor influencing the potential users decision to invest in the systems (Truc, et al., 2017). All these previous experience has shown adequate knowledge of renewable systems can enhance the systems’ reliability.

Productivity Renewable energy does not only provide energy access to rural households, it can also contribute to a higher income to the users. Various studies have proved that solar PV systems could improve rural household income from income generation activities due to access to electricity (UNDP, 2014; Stojanovski, 2017; Blunck, 2008). For example, a research article on solar PV electrification in Ghana shows that an additional income of $5-$12/day could be obtained in grocery enterprises due to solar PV lighting (Obeng & Evers, 2010). In rural Bangladesh, researchers have found shop

34 owners who install solar home systems increase their sale revenue due to improved light from the systems attracting more customers (Siegel & Rahamn, 2011). And according to IRENA, solar pumps could increase the household income by 286% for the very poor, 173% for the poor and 47% for the middle-income groups in Zimbabwe (IRENA, 2016). Similarity to household biogas digesters, studies have shown there is a strong linkage between the increased rural household income and productivity and biogas digester users. This is because the slurry and waste from biogas digesters provide high quality fertilizers that can be used to improve the soil fertility and increase the agricultural productivity (Amare, 2015). And according to Kabir et al., in Bangladesh, using biogas plants, households could have income gain by BDT 16,001 per year (Kabir, et al., 2012). Although a great number of literatures have proved renewable energy systems can lead to income generating opportunities or productive loads for rural households, still majority of the systems are for residential use only, thus income generation activities are very limited. For example, electric lights from solar PV system are found only supporting income generation activities for middle-class households in rural Kenya (Jacobson, 2007). Similarly, in Africa, in most cases biogas digester systems offer only very limited income generation opportunities from the sale of biogas and fertilizer (Schafer, et al., 2011). The limited use for income generation activities is largely due to the systems’ limited sizes. Household renewable energy systems are usually small-scale in rural areas for little power input. To this point, the energy produced by those system is limited, and it will not automatically led to productive uses but to satisfy the household’s daily energy requirement first. For example, the capacity of solar home system in Mera Gao of India is very limited – for only two

35 compact fluorescent light bulbs, thus it is unlikely those systems will lead to income- generating opportunities or productive loads in the area (Agarwal, et al., 2014). In terms of biogas digesters, in India, researchers find that roughly 4-5 cattle are required to run even a small biogas system to meet a household’s daily cooking fuel needs (Hall & Barnard, 2013). Because only 10-12% of farmers in India possess this many, inevitably, therefore, most of household biogas systems in India are only enough for household energy use. Another factor accountable for the limited use for income generation is a lack of supporting facilities/services. For example, in a research on productive uses of electricity in rural areas, Sanghvi et al. notice that although PV for water pumping have installed in rural Africa, because those systems are limited to shallow wells, only a small percentage of population could be covered (Fishbein, 2003). Also Nygaard argues that PV has only rarely been used for productive use such as irrigation in sub- Saharan African countries, as its supporting battery charging stations are not always accessible (Nygaard, 2009). As a result of these previous experiences, the productive uses of rural renewable energy systems are compromised.

Operation and maintenance Renewable energy systems have been proved to require less operation and maintenance expenses than other off-grid energy systems. Thus these technologies offer greater economic benefits to rural households in the longer term. Solar PV systems and diesel generator are the most compared systems for the cost analysis as they are the most common types of small generators for providing electricity in remote rural areas. Various articles have shown the maintenance of solar PV system is significantly lower than the diesel generator, as it requires mainly periodic cleaning of

36 the glass panel (World Bank, 2008; Diemuodeke, et al., 2016; Isamil, et al., 2014; Sako, et al., 2011). For example, Setiawan et al. (2015) have found that in rural Indonesia, the cost of water PV pumps is only ¾ of diesel generator pumps. And this is because the maintenance cost of PV pumps is only ½ of those diesel systems (Setiawan, et al., 2015). Also, many small-scale biogas digesters do not require high maintenance (Rajendran, 2012). Sehgail observes that for the 200 flexi biogas systems installed in Kenya in 2011, so far their operating and maintenance costs have been close to zero (Sehgai, 2012). Although renewable systems require low maintenance, there is a severe lack of maintenance and repair of the systems, resulting in inefficiency and shortened system lifecycles. This is evident in a number of previous renewable energy projects. Mapako and Mbewe highlight that the lack of a maintenance system is one of the main causes of failures of renewable energy technologies in rural Botswana (Mapako & Mbewe, 2013). Another case study of solar PV systems installed in Nigeria shows only 14.52% of the solar home systems installed in Oke-Agunla village was properly utilized as a result of poor maintenance and lack of technical know-how (Isamil, et al., 2012). And a field investigation of domestic biogas digester in Danzhai County in Guizhou of west China finds that normal systems utilization rates are between 37% and 69% across various villages (Ding & Zheng, 2013). The major reason given for this low rate is lack of maintenance. Part of the problem is identified as a lack of capacity, skills or labors to carry out maintenance, and lack of funding to carry out maintenance. As a consequence, the maintenance has been frequently ignored, which leads to project failures.

Key Points

37 Renewable energy systems can deliver economic benefits to rural households since those systems are cost-effective, more reliable and require less maintenance than other off-grid generation systems. In addition, those systems have the potential to contribute to user income by providing extra energy for productivity uses. However, prior experiences have shown that these economic benefits are often compromised by a number of barriers such as high initial costs and size limits of the systems, excessive subsides on fossil fuels, a lack of replacement parts, users’ know-how and adequate maintenance. Therefore, assuring the economic benefits of renewable systems to rural household may involve special policy interventions.

2.1.3 Social Perspective Time Allocation Today, there are still 1.2 billion and 2.7 billion people without access to electricity and clean cooking facilities (IEA, 2016). Without those modern energy accesses, people, mostly women, have to spend most of their time on basic household activities including collecting biomass fuels for lighting and cooking. There is ample literature documenting how renewable energies such as solar and biogas help to provide modern energy access to those population. There are also numerous studies about how renewable energy helps to change the times people spend on their daily activities. With renewable electricity, people are provided with services such as lighting, TV, radio and appliances. Electricity provides higher quality of light and it replaces inefficient candles and kerosene lights that are usually used in a non-electrified rural household. With electricity, people do not need to spend time on collecting fuel woods, thus they have more time to study and access to information. Also because

38 lighting extends people’s effective working hours, therefore they can work longer time (after the dusk) and expand their income-generating opportunities. With electricity, people have more time spent on watching TV and listening to radio. This increases their access to social society and increases their social awareness. Electrification has been also shown to have clear positive impact on the education of boy and girls. With electrified schools, children’s school attendance has been improved. There is also a lot of literature talking about biogas digester helps to reduce time and labor required for the collecting of fuel for cooking and cooking itself. Mendis & Van Nes shows a biogas installed in rural Nepal can save approximately three hours per household per day (Mendis & Van Nes, 2014). Also Amare observes that household biogas investment can save up to 51 minutes on average day per household in Ethiopia (Amare, 2015). With time saved from biogas digester, household members, particularly women and children now have time to go to school. They can also use their spare/saved time in taking care of their families, in keeping household sanitation, and involving in productivity activities. For example, study from the World Bank indicates a domestic biogas in rural China can save labor time at 21 working days a year, of which 30% would be used for income-generating activities at CNY 20 per working day (World Bank, 2008).

Health Improvement Renewable energy has long been claimed to have many benefits to health. According to WHO, 4.3 million people a year die prematurely from illness attributable to the household air pollution caused by the inefficient use of solid fuel for cooking (WHO, 2016). The exposure to indoor air pollution has associated with many respiratory health problems. Biogas digesters, according to a number of literature,

39 have been proved to bring potential reparatory health benefits as alternative fuel source to rural households without access to clean fuel technologies (Dohoo, et al., 2012). For example, a case study by Dohoo et al. (2012) on impact of biogas digester of women on Kenyan smallholder dairy farms, 87% reported women improved personal respiratory health and 27% reported improved children’s health. Another case study in Nepal shows biogas digester users are associated with lower systolic and diastolic blood pressure as well as improved cardiovascular health (Neupane, et al., 2015). Electrification via renewable energy also brings numerous health benefits to rural people. These benefits include better health conditions from cleaner indoor air as households use cleaner fuels for lighting, improved health facilities, better health knowledge from access to TV, and better nutrition from improved knowledge and better refrigeration (World Bank, 2008). For example, in the past, numerous PV systems have been installed in health facilities that are used to power vaccine refrigerators in developing countries. And this has been approved to strengthen their routine immunization. In addition, with access to TV and radio, people increase their awareness for health issues thus result in changed health behavior. For example, a study from the World Bank on fertility impact from renewable electrification clearly shows that electrification results in fertility reduction in developing countries like Bangladesh, Ghana, Indonesia, Nepal, the Philippines, et al (World Bank, 2008). However, these social benefits might be weekend if renewable systems are not designed or used properly. For example, the failure rate of the first-generation solar- powered vaccine refrigerator is very high. McCarney et al. summarize a series of failure case studies in developing countries such as Ghana, Senegal, Nigeria, and

40 Indonesia (McMarney et al., 2013). Ghana for instance, for the 80 solar refrigerators that were installed in the late 1980s, more than half of them failed soon after installation (McMarney et al., 2013). They conclude that the main reasons for high failure rates in these countries are inadequate system design (e.g., poor battery system) and installation quality, inappropriate use, and lack of maintenance and delay in repairs (McMarney et al., 2013). A response to this problem is the development of second-generation solar refrigerator, which is called solar direct-drive refrigerator. Because this new generation has better system design – no need for batteries, studies have shown this new system has several potential advantages including simpler installation, less maintenance requirements, and more reliability (WHO, 2013).

Gender Equity In many parts of the developing world, women and children experience more severe energy issues than men. Considering the cultural roles of women and girls in the society, they do all or most of basic household activities, including collecting biomass fuels for lighting and cooking, which constraints them from educational opportunities, employment opportunities and productivity opportunities (UNIDO, 2014). And it is evident that renewable energy systems can bring greater social to women and girls. Take cooking for instance, indoor air pollutions from cooking with solid fuels mostly affect women and children’s health who typically spend more time at home. In addition, gathering fuel wood takes several hours a day – and this work is done almost entirely by women and children. Thus using renewable technology for cooking can save women and children’s time spent on collecting fuels and cooking, and then increase their leisure time and improve their health. In rural Kenya for example,

41 Dohoo et al. observe that women with biogas digesters spend significantly less time on cooking compared with women cook with wood fuels (Dohoo et al., 2015). By reducing time spent on cooking, their exposure to volatile organic compounds in the kitchen is much lower than households without biogas digesters. The literature on energy and gender suggests that electrification by renewable energy can bring greater gender equity – improving women and girls’ access to education, health care, and employment. It is well documented that with solar electricity, women have more free time while less household workloads (Urmee, et al., 2016). As a result, they are able to undertake income-generating activities after dusk. For example, a reliable source of electricity has been shown to increase women’s employment by 9% (Kohlin & Pattanayak, 2011). Also a research from UNDESA finds that solar electrified schools have increased levels of girls’ school attendance, improved performance, and drastically improved boy-to-girl ratios in 52 developing countries (UNDESA, 2016). It is well argued that women have gain tremendous benefits from renewable energy, however, numerous gender-based challenges still need to be addressed. First, the existing gender discrimination limits women’s opportunities in the renewable energy sector. For example, when women are employed in the renewable energy sector, they are only provided with less-paid positions. Moreover, some social norms prevent women from receiving renewable systems. For example, in some places of India, it is difficult for women to rent solar cook stoves due to social practices related to caste (Nelson & Kuriakos, 2017). Second, the affordability and mobility further limit women’s access to renewable technologies. According to Kuriakose & De Boer, women’s access to renewable energy is often constrained by affordability (Kuriakos &

42 De Boer, 2015). Moreover, in some rural remote places, discriminatory social norms limit women’s mobility. Thus, access to transportation for renewable energy training for the installation and maintenance of renewable systems can be challenge to women (World Bank, 2015). This limits the benefits that women might enjoy from renewables. Third, many renewable energy projects don’t take into account their impacts on women or the role of women in their implementation. For example, in the past, energy efficient cookstoves powered by biogas digester were designed by male engineer without consultation with women who are actually the main users of these stoves (Cecelski, 2000). This results in poor energy performance and limited adaptation of these systems. Realizing this problem, now most stove cook programs integrate women’s considerations into the system design. This shows gender inequality should be addressed properly in order to scale-up rural renewable energy development.

Key Points Renewable systems offer great social benefits to rural sustainable development, as they reduce rural people’s time spent on fuel collection and cooking, while increasing their time on watching TV, listening to radio and other productive works. In addition, renewable technologies improve rural people’s health conditions and improve their gender equity. However, these benefits are sometimes weakened due to a series of challenges such as lack of proper system design or ignorance of discriminatory social norms between women and men. To ensure these benefits, these challenges must be address and proper policies must be enforced.

2.1.4 Environmental Perspective It is widely accepted that the renewable energy systems provide significant environmental benefits in comparison to the conventional energy sources, contributing

43 to the sustainability of human activities. The utilization of solar PV systems has positive environmental implications such as reduction of CO2 emissions, improvement of the quality of water supplies, mitigation of global climate change and reduction of power transmission lines (Gekas, et al., 2002). In an UNDP paper, researchers have observed that solar generation could offer a carbon emission mitigation potential of 30 -100% of the widely used diesel only generation solutions (UNDEP, 2014). In addition, an ADB’s study recognizes renewables reduce deforestation in Bhutan: households electrified by renewables cut about 0.27 fewer tress per year compared to unelectrified households (ADB, 2010). In addition, households use less pollutants energy sources such as kerosene and fuelwood. The use of domestic biogas digester for cooking also offers environmental benefits such as reducing environmental pollution by recycling manure and reducing indoor air pollution with a clean cooking fuel alternative to fossil fuels or firewood (Xia, 2013). The WHO guideline for air quality are 50ug/m3 for PM10, however, in many developing countries the peak indoor PM10 concentration exceeds 2,000ug/m3 due to inefficient burning of biomass for cooking (WHO, 2006; Ezzati & Kammen, 2001). In Uganda, Tumwesige et al. have observed that with installation of domestic biogas digesters, 66% of the targeted rural households have experienced decreased levels of PM10 and CO in their kitchens (Tumwsige, et al., 2014). Also another study on biogas fuel use in rural Nepal, Neupane et al. have found substantially reduced kitchen PM10 level among biogas digester using households (Neupane, et al., 2015). In addition, adaptation of biogas plants can reduce deforestation that is caused by the over-collection of firewood for cooking. It is found that one household digester can save about 2 tons of firewood and 0.25 hector of forest per year (Gregory, 2010).

44 Although renewable energy systems provide environmental benefits to rural households as means of energy generation, their benefits could be compromised if they are not used properly. Solar PV system contains lead acid batteries. Once the batteries reach end-of-life, they need proper disposal – they should be kept intact, the acid should not be poured out, they should not be disposed outside, and they should be kept away from children (Sandgren, 2001). However, in many rural areas it is difficult to arrange such services (Varho, 2002). Turning to biogas digester, the slurry resulted from anaerobic fermentation is an excellent fertilizer that can contribute to better crop yield and lasting soil fertility (Mikeled, et al., 2002). However if the fermentation is poorly planned, the slurry produced and used as a fertilizer may cause ground and surface water pollution (Vorbrodt-Strzalka & Pikon, 2013). Also the excessive supply of slurry may stop flowering (Rajeshkumar & Ravichandran, 2015). These evidences indicate that regulation or policy should be adopted and enforced to further enhance environmental benefits of renewable energy systems.

Key Points Although renewable technologies for electrification and cooking have long- term environmental benefits such as emission reduction and protection of forests, improper use can lead to a big decrease of these benefits. Thus policy and regulation should be adopted, and people’s environmental awareness should be raised.

2.2 Conclusion of Literature Review and Significance of this Study A review of renewable energy for rural sustainable development has been presented in this chapter. The review is performed with regards to the three most important elements of sustainable development: economic, social and environmental. It has been well documented that off-grid renewable energy options can be a practical

45 way to provide electricity and clean cooking services to households who still don’t have the access to these two modern energy services in the developing world. Economically, off-grid renewable systems are cost-effective, more reliable and require less maintenance than other available technologies when attempting to solve rural energy problems. In addition, these systems have the potential to contribute to user income by providing extra energy for productivity uses. Socially, with utilization of renewable energies, people spend less time on daily household activities such as fuel collection and cooking. As a result, they have more leisure time for entertainment and productive activities while have less exposure to indoor air pollutions. In addition, renewable systems can help to improve gender equity – women and children’s workload is reduced and their access to modern energy, information, and education is improved. Environmentally, renewable energy has been proved to reduce CO2 emission, improve water quality, and protect forest. Over the past two decades, China has provided hundreds of millions of rural people with access to modern energy services. Despite the accomplishments, still many people in China have no access to electricity, and more than 1/3 of China’s population relies on solid fuels for cooking (NEA, 2016; IEA, 2016). Finding appropriate ways to provide modern energy services to these communities has been a key issue for Chinese government. To serve this aim, an important task of this dissertation is to examine off-grid renewable energy options for rural energy development in China. Based on the existing studies, this dissertation evaluates the ability of off-grid renewable energy technologies to provide energy services for rural households and assesses the sustainability of renewable energy utilization in rural China from three aspects: economic, social and environmental. In this sense, this study

46 is significant because it provides a useful contribution to the available literature on renewable energy for sustainable rural development in China. Because Guizhou province is selected as the case study of this dissertation, this study is also an update to the existing case studies about China’s rural renewable energy development. This chapter has clearly shown that a lot of work has been done in the area of providing modern energy services by renewable energy technologies. However, the aforementioned studies only addressed rural energy development problem in a non- integrated manner. In addition, although impacts of renewable energy for rural development have been identified from three perspectives, economic, social and environmental; in fact, studies of today have been mainly focused on the ability of renewable energy systems to deliver services that will provide rural households with economic benefits rather than non-economic benefits. Although studies have clearly shown renewable energy options may bring social and environmental benefits such as improving social activities, reducing time spent for cooking, mitigating greenhouse gases, etc. to rural households, these studies don’t offer a strong case that these non- economic indirect benefits are as important as economic benefits. For example, in China, the social and environmental benefits beyond the economic benefits of solar PV systems and household biogas digesters to rural households are not clear. These identified research gaps show that there is a significant need to develop a better and more-comprehensive approach to analyze, measure and assess the impacts of off-grid renewable energy options on rural development. For this aim, this dissertation develops an integrated approach to off-grid renewable energy systems for improving modern energy access in the context of rural China. This integrated approach is to utilize off-grid renewable technologies to meet the electricity and cooking fuel

47 demands of rural households in China in an integrated manner. In addition, both economic and non-economic benefits of renewable energy technologies are assessed. In this sense, this dissertation is able to fill the identified research gaps of current studies of renewable energy for rural development. Lastly, the results of this study can be used as the guidance for policies to develop renewable energy development in rural China. It will help the Chinese policy makers to develop a deeper understanding of how renewable energy assists rural energy development in China. The government or nonprofit organizations can also use the results to implement rural renewable energy systems in rural areas. In addition, the results can also be of interest to private sectors to better understand the interrelationship between policy and the market. Moreover, this study will be a good model for any future studies on investigating the energy performances, as well as evaluating the economic, social and environmental benefits of solar home systems, household biogas digester systems, or other renewable energy options in the rural areas of developing countries.

48 Chapter 3

CONCEPTUAL FRAMEWORK AND RESEARCH METHDOLOGY

This chapter introduces the conceptual framework and methodology that are applied in this dissertation. The chapter is intended that this will provide a better understanding for the readers to understand how this dissertation is developed.

3.1 Conceptual Framework A conceptual framework is the backbone of a research study. It provides the guidance for conducting the research to investigate a particular research question. The conceptual framework includes the main components of the study. Also it presents the relationship or the linkage between those elements. Essentially, a conceptual framework combines all the different elements of a study in a logic manner for the overall purpose of the study. The conceptual framework of this dissertation is based on the existing literature that focused the relationship between renewable energy and rural sustainable development. Past studies summarized in the previous chapter has shown renewable energy is a promising alternative to developing countries in achieving their long-term goal of sustainable rural development. The sustainability of renewable energy is analyzed from three perspectives – economic, social and environmental. Also potential drawbacks that may weaken those benefits are identified. In addition to the sustainability analysis of renewable energy to rural development, the framework in this study incorporates some other elements. First, this study recognizes the

49 importance of renewable energy resource potential. Therefore, the study develops a framework that includes the estimation of the potential of different renewables resource. Second, this study looks at the technology performances of the renewable energy systems. Therefore, the system’s energy potential of meeting customer’s daily, monthly and annually energy requirement is examined. In addition, the study looks at the sustainability of the renewable energy options from three aspects, namely economic, social and environmental. In this way, it identifies the factors that will affect the sustainability potential of the renewables. The overview of the conceptual framework of this dissertation is illustrated in Figure 3.1. In this dissertation, three types of potential analysis are provided: resource potential, energy potential, and sustainability potential. The figure below shows how these three analyses are related to one another. Their relationship is so called “resource-energy-sustainability” relationship. They each depend on the preceding type of potential study in a sequential manner.

Figure 3.1 Theoretical Framework of this Study.

The conceptual framework shows the basis of this study is built on the solid understanding of resource potential, which is an estimate of the theoretical potential for renewable resources in a region. Resource potential analysis addresses the quantity, timing of availability and geographic location in supply of renewable resources such as solar and biogas because resource varies by location and time. Hence resource uncertainty can have a large impact on the performances and impacts of renewable energy options on rural sustainable development. Based on the resource potential analysis, energy potential analysis investigates renewable energy systems from technical aspect. It determines the daily, monthly and annual net energy output of the systems. Moreover, the system’s energy output will be compared to household’s energy requirement to see if energy shortfall occurs. The sustainability potential analysis investigates the potential economic, social and environmental benefits that

51 renewable energy options brings to rural households. This type of analysis incorporates economic, social and environmental factors that can have great impacts on the sustainability potential of renewable technologies. In sum, the conceptual framework of this dissertation shows these three analyses are interlinked and they are the basis of how this study is conducted.

3.2 Research Methodology This dissertation develops an integrated approach to off-grid renewable energy systems for improving modern energy access in the context of rural China. This integrated approach is to utilize solar and biogas technologies to meet the electricity and cooking fuel demands of rural households in China. In addition, both economic and non-economic benefits of solar and biogas technologies are assessed. This integrated approach is carried out in three phases. The first phase is an evaluation of solar and biogas resources. Given the resource assessment, the second phase is an analysis of the energy performances of off-grid renewable energy systems (a solar home system of array capacity of 520W, a household biogas digester system of 8m3 and an integrated system that combines those two resources) to be operated in rural China. And the last phase involves conducing a comprehensive assessment of sustainability of renewable energy utilization from three aspects, namely economic, social and environmental. Each phase depends on the previous phase on a sequential manner. A flow chart of these three phases is illustrated in the Figure 3.2. Each phase involves certain steps or techniques to realize them.

Figure 3.2 Methodology Flow Chart.

The purpose of the first phase is to gain knowledge about solar and biogas resource potential in the case study region. Given the resource assessment, the second phase evaluates the energy performances of off-grid renewable energy systems. This phase investigates the reliability of the systems to see if they can meet the household’s energy requirements. Based on the previous two phases, the third phase assesses the sustainability of the renewable energy systems. In this phase, economic, social and environmental performances of the systems will be assessed. Their sustainability performances will be compared with their competing energy systems (e.g., solar PV systems versus diesel generator, and digester versus LPG and coal-based stoves) to see how the renewables can help to improve the rural development in a more sustainable way. In addition, this phase also discusses potential barriers facing solar and biogas development in rural Guizhou.

53 3.2.1 Selection of Case Study Region and Renewable Energy Options In order to answer the research questions, this dissertation is conducted as a case study of renewable energy for rural development in China. Guizhou province is selected as the case study region of this study due to several reasons. First, Guizhou is one of the least developed provinces in China. Its overall social and economic development is slow compared with other provinces, and more than 2/3 of its population is rural people. Considering its social and economic status, it is meaningful to see how renewable energy help Guizhou’s rural population to improve their livelihood. Second, even today electrification rate has achieved almost 100% in China, still quite a number of rural household doesn’t get access to electricity. Most of these population is found in remote rural areas, such as in Guizhou. Considering Guizhou’s landscape is mainly mountainous, for rural people who live in mountain areas and don’t have electricity, it is unlikely that they will be provided with electricity from electric grid extension in the near future. Thus the province is an ideal region that solar home system can be an alternative to provide electricity to its people. Third, today many rural households in Guizhou still rely on solid biomass for cooking. Lung diseases, teeth and eye diseases have been found in the province that is closely related to cooking with coal. Considering rural households in Guizhou are mainly agricultural households, and today both central and Guizhou governments have strong incentives for promoting clean cooking, it is very likely that the household biogas digester is an ideal option to provide clean cooking services to rural households in Guizhou. Fourth, governmental support is very important when doing a case study, especially in China. When doing a case study that involves provinces in China, official data is very hard to get without government supports. Among all potential case provinces, Guizhou is the

54 only province that governmental support is granted for data collection. Combined with all these reasons, Guizhou is selected as the case study region of this study. Solar home system and household biogas digester are the two renewable technologies selected by this study. Solar home system is an ideal alternative to provide electricity to unelectrified households where electric grid extension is unrealistic (expansive) or not going to happen in the near future. Household biogas digester is a cost-effective option of clean cooking for households who still rely on solid biomass for cooking. Hence, these two types of systems are potential alternatives for Guizhou rural households to get modern energy access. Since it is not feasible that a single solar home system or a biogas digester can meet rural household’s cooking and electricity loads at the same time, an integrated system that combines solar and biogas technologies can solve this problem. Thus an integrated solar-biogas is also discussed in this study. To data, there has been ample literature focusing on the solar home system and domestic biogas digesters separately, no one has ever talked about them together. Because access to electricity and access to clean cooking facilities are the two inseparable elements of modern energy access, it is of great significance for this study to talk about them together.

3.2.2 Phase 1 – Resource Potential Analysis In order to evaluate the impacts of the renewable technologies for rural development in Guizhou, the first step is to determine their resource potential. For solar home systems, annual solar radiation and annual solar hours are examined for each of Guizhou’s 88 counties. Annual solar radiation is the solar energy on the earth surface that is expressed as the average kilowatt-hours (kWh) of thermal energy incident on a square meter of horizontal area and nnual solar hour is the number of

55 sunshine hours in a year for a given location on earth (Byrne et al., 2001). Solar radiation and annual solar hours data retrieved from Guizhou Meteorological Administration are used as primary sources for analysis of solar energy potential in Guizhou. In addition, the solar data are put into ArcGIS map to show the solar resource map of Guizhou. The map helps to identify regions/areas with high solar potential, therefore these areas can be considered as the potential candidates for solar home system implementation. For household biogas digester, ground temperature, the amounts of crop and manure residues available for biogas production are estimated, using national and provincial agricultural statistics and several other data sources. The ground temperature is the most important factor that affects gas production performance of a biogas digester. In this study, the average ground temperature at the depth of 1.6m in the 88 counties of Guizhou is obtained. Crop residue is estimated for cereal crops such as rice, wheat and corn and non-cereal crops such as beans, potatoes, cotton, oil-seed, sugar and tobacco. The production of crop residues in each county is obtained by multiplying the county’s annual crop harvests by residue-to-crop ratios. Manure residue is estimated for cattle, pigs, sheep and chicken. The calculation is based on animal population statics from each county’s latest Social and Economic Status Reports available online. In principle, the available manure resource for each county is estimated by multiplying each animal population by its average excretion rate.

3.2.3 Phase 2 – Energy Analysis Based on the evaluation of the resource potential in Guizhou province, the second phase is to assess the technical capacity of solar home system and household biogas digester to meet rural energy needs.

56 RREAD model is used to calculate the solar electricity generation of the solar home system in Guizhou’s 88 counties. Developed by Dr. Byrne and his students from Center for Energy and Environmental Policy (CEEP), RREAD is a multidimensional simulation tool that helps to evaluate decentralized energy options for rural development from a broad range of perspectives (CEEP, 2001). The model has been used in several CEEP-based research projects such as the off-grid renewable energy options for rural electrification in western China project that has been conducted in 2001. It is consisted of three modules: a data input module, a calculation engine and an output module. When resource data and system data are put into RREAD, it automatically calculates the hourly solar electricity output from the solar system. And once hourly energy output values are estimated, RREAD aggregates the hourly values to arrive at daily, monthly and annual values. In addition, by calculating the daily electricity output, RREAD is able to determine the storage requirement of the battery bank and also to determine if energy shortfall happens.

57 Data inputs RREAD calculation Results/Outputs

Resource and climate data --solar insolation --hourly/monthly Wind speed --ambient temperature

Load data Energy performances --number, type and --sizing of renewable rated power of energy system (battery appliances bank, inverter and --daily operating hours controller) of appliances Energy --energy output Evaluation --monthly energy shortfall days and the System configuration magnitude of the energy data shortfall --PV system: angle, --comparison to area, efficiency, competitive engine lifetime, etc. generator --wind: height, diameter, power, lifetime, etc. --BOS: battery size, depth of discharge, lifetime, size of controller, size of inverter, etc. --engine generator: power, operating hours, fuel consumption, lube consumption, etc.

Figure 3.3 Overview Structure of RREAD to Calculate the Energy Performance of Solar Home System.

58 Animals database for energy potential estimation (ABEPE) model is used to calculate the biogas output of the household biogas digester. The ABEPE model was first proposed by F.A. Batzias et al. to estimate biogas production from major crop residual (rice, wheat and corn) and manures of livestock (pig, cattle, sheep and chicken) in Greece (Batzia, et al., 2005). Now this model has been implemented in a number of Chinese literatures including Tang et al., Chen et al., to estimate the rural household biogas potential in China (Chen, et al., 2015; Tang, et al., 2010). For this study, ABEPE model is used to estimate the annual and daily gas potential from crops and manures of the 88 counties in Guizhou province at household level. Similar to RREAD model, the ABEPE model also has three modules: data input, energy calculation and results. The input data includes resource data (manure and crop residue), and various factors need to be considered during the calculation such as dry matter factors, biogas yield factors, temperature factors and usage factors. When the data is input, the model first calculates the annual household theoretical biogas output of all types of manure and crop residues. After that, the model will adjust the theoretical output based on temperature and usage factors to have a more accurate number for the biogas output.

Figure 3.4 Overall Structure of ABEPE to Calculate the Energy Performance of Household Biogas Digester.

3.2.4 Phase 3 – Sustainability Analysis The sustainability performance of renewable energy systems in Guizhou province will be evaluated from three perspectives: economic, social and environmental. RREAD will be used to evaluate the economic performance of the renewable energy systems. Again, the model has three modules for economic evaluation: a data input module, a calculation engine and an output module. Cost

60 information of the systems, as well as financial terms and subsidy data are used as the input values in RREAD for its economic evaluation. Once data are input, RREAD calculates the levelized energy costs (LCOEs) of renewable energy systems over their evaluation periods. In addition, the model reports the economic performance of the competitive traditional energy generation systems such as diesel generator, LPG-based and coal-based cooking. This provides a clear idea of how the selected renewable systems in this study provide greater economic benefits than their competitors.

Data inputs RREAD calculation Results/Outputs

Cost data --capital costs of PV, biogas digester, competitive energy generators --replacement costs of system parts Economic --shipping performances --installation --net present value --O&M costs (NPV) of the systems --fuel delivery costs Economic --levelized energy costs --salvage values (LCOE) of the systems Evaluation --comparisons between renewable systems and Financial data their competitive --discount rate traditional generation --lifetime systems in terms of --current exchange rate LCOE --tariff --sensitivity analysis

Policy data --subsidy --rebate --social and environmental value

Figure 3.5 Overall Structure of RREAD to Calculate the Economic Performance of Renewable Energy Systems.

61 Many existing studies of off-grid renewable energy systems used HOMER (Hybrid Renewable and Distributed Generation System) for energy and economic evaluation, however this study utilizes RREAD because: first, the logic behind RREAD is the same of HOMER, or in other words, both RREAD and HOMER calculate solar electricity output from solar home systems or biogas output from biogas digester systems with same resource data input. Also both RREAD and HOMER calculate levelized energy cost of off-grid energy systems with cost, financial and policy data with same logic flow. The only difference between the two models is as a commercialized software, HOMER has a fancier page layout, while RREAD is only excel-based. Second, this study compares the performances of off-grid energy options with studies that were conducted more than 10 years ago by CEEP. The original CEEP’s studies were constructed based on RREAD model, therefore, utilizing RREAD in this study provides a more accurate comparison. In addition to LCOE analysis, sensitivity analyses are performed on a number of variables such as discount rate, module and maintenance cost, energy output, etc. The aim for the sensitivity analyses is to determine how important that variable is, and in what extent the levelized costs (LCOEs) of solar home system and household biogas digester varies by varying the variables. The social and environmental performance evaluations are mainly conducted by qualitative approaches such as observations from existing studies. It focuses mainly on earlier studies regarding the positive effects renewable energy systems can have in developing countries and how they can affect the social status and environmental condition of a rural community. This study looks at the qualitative analysis of how solar and biogas energy can improve the social and environmental status of rural

62 households in developing countries, and then apply these experiences to the rural households in Guizhou. In addition, potential barriers facing the development of solar and biogas technologies in Guizhou will also be discussed in this phase, so that recommendations could be given to better assist their dissemination in the province. In all, this dissertation develops an integrated approach to off-grid renewable energy systems for rural electrification and clean cooking in the context of rural China. As an integrated approach, this dissertation can provide better policy making guidance than existing non-integrated approaches when addressing rural energy needs.

63 Chapter 4

PROFILE OF GUIZHOU PROVINCE

4.1 Background of Guizhou Province

4.1.1 Geography Guizhou Province is located in the southwestern part of China, adjunction Sichuan province to the north, Yunnan province to the west, Guangxi province to the south and Hunan province to the east. As country’s one of the smallest province, its total area is 176,200 square km, or 1.8% of the country’s total area (National Bureau of Statistics, 2016). Overall Guizhou is a mountainous province however it is more hilly in the west while the eastern and southern parts are relatively flat. The western part of the province forms part of the Yunnan-Guizhou Plateau. The annual average temperature is 15C, ranging from 22-25 C in July to 4-6 C in January, usually necessitating heating in wintertime (National Bureau of Statistics, 2016).

Figure 4.1 Map Showing the Location of Guizhou Province in China.

4.1.2 Population The latest 6th national population census shows that Guizhou has a population of 34.7 million, accounting for 2.59% of China’s total population (National Bureau of Statistics, 2011). It is demographically one of China’s most diverse provinces. Minority groups account for more than 35% of the population and they include Miao, Yao, Yi, Qiang, Dong, etc. And more than 55% of the province area is designated as autonomous regions for ethnic minorities. Of all the population in Guizhou, more than 2/3 are rural people. And the average family size is 3.24 persons per household.

65 Table 4.1 Main Indicators on Guizhou’s Population.

Total population 34,746,500 Urban population 11,747,800 (33.81%) Rural population 22,998,700 (66.19%) Total number of households 10,389,600 Total number of urban households 385,180 Total number of rural households 6,515,200 Family size (person/household) 3.24 Urban family size (person/household) 3.05 Rural family size (person/household) 3.53 Source: National Bureau of Statistics, 2011.

4.1.3 Economy In terms of economic development, Guizhou is recognized as an underdeveloped province in China given its GDP per capita. The province relies heavily on agriculture and tourism to develop its economy. And Guizhouis China’s 3rd largest grower of tobacco, and the home to the well-know brand Guizhou Tobacco. Throughout the 1990s and beyond, the Guizhou economy grew sluggishly and was among the slowest growing Chinese provinces. In 2015, Guizhou’s GDP per capita was 29,847 CNY, 40% less than the national GDP per capita at 49,992 CNY (National Bureau of Statistics, 2016). The people’s living condition in Guizhou is also lower than the national average. The rural poverty rate in Guizhou is significant. In 2015, there are 4.93 million people living in poverty (with an annual per capita net income of 2,300 CNY or less), the largest province in China and making up 8.77% of the nation’s poor population (Guizhou Bureau of Statistics, 2016). Of all the 88 counties in Guizhou, 66 of them are national level poverty-stricken counties, or 75% of the province (Guizhou Bureau of Statistics, 2016). And 16 of these counties are included in the 14 concentrated poorest areas as defined by the central government.

66 Table 4.2 Poverty Population and Poverty Rate in Guizhou, 2011 – 2015.

Year Poverty Poverty Poverty Poverty Poverty rate county township village population 2011 66 868 13,973 11.49 33.4% million 2012 66 740 13,973 9.23 million 26.8% 2013 66 568 13,973 7.45 million 21.3% 2014 66 409 9,000 6.23 million 18% 2015 66 190 9,000 4.93 million 14% Source: Guizhou Bureau of Statistics, 2016.

In 2015, Guizhou’s per capita disposable income was 13,696 CNY, 38% less than the national per capita disposable income at 21,966 CNY, the 3rd lowest in China (National Bureau of Statistics, 2016). The urban national per capita disposable income in China was 31,195 CNY in 2015, and Guizhou was 22% lower at 24,579 CNY (National Bureau of Statistics, 2016). In terms of rural living, in 2015, the rural per capita disposable income in Guizhou was 7,387 CNY, which was 35% than the national level of 11,422 CNY (Guizhou Bureau of Statistics, 2016).

67 35,000

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0 per capita disposable urban per capita rural per capita income disposable income disposable income National 21,966 31,195 11,422 Guizhou 13,696 24,579 7,387

Figure 4.2 Per Capita Disposable Income of National Average and Guizhou, 2015 (unit: CNY). Source: National Bureau of Statistics, 2016; Guizhou Bureau of Statistics, 2016.

From 2011 to 2015, government of Guizhou has made tremendous efforts to improve the living status of people in the province, especially to rural households. Although the rural per capita disposable income in Guizhou was 35% lower than the national level in 2015, it has been increased by 78% than the year 2011 (Figure 4.3). Despite the low economic status in the province, both the central and Guizhou provincial governments have made tremendous efforts to improve its people’s living conditions. Now Guizhou province is listed as one of the key provinces supported by the central government in implementing a new round of poverty reduction and development. In 2015, the central government has provided a subsidy of 232.4 billion CNY to Guizhou for its poverty alleviation, the 10th largest in the nation (National

68 Bureau of Statistics, 2016). With those efforts, now the province’s poverty rate has reduced from 33.4% to 14% from 2011 to 2015, and its rural per capital disposable income has increased 78% during the same time period (Guizhou Bureau of Statistics, 2016). This trend is expected to carry on as the government has been putting in place numerous policies for future economic development.

35,000

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0 2011 2012 2013 2014 2015 National (rural) 6,977 7,917 9,429 10,489 11,422 National (urban) 21,809 24,565 26,467 28,843 31,195 Guizhou (rural) 4,145 4,753 5,434 6,671 7,387 Guizhou (urban) 16,495 18,700 20,667 22,548 24,579

Figure 4.3 Per Capita Disposable Income of National Average and Guizhou, 2011 – 2015 (unit: CNY). Source: National Bureau of Statistics, 2016; Guizhou Bureau of Statistics, 2016.

69 4.2 Access to Electricity in Guizhou Province Access to electricity in Guizhou Province is discussed from two main groups: (1) individual households in areas that are not currently electrified; (2) electrified households that are without adequate or reliable electricity supplies.

4.2.1 Individual Households in Areas without Electrical Services In the past decade, Chinese government has been highly successful in electrifying rural households in China. To date, China almost achieves a 100% electrification rate – the highest among all other developing countries. However, there are still less than a million people in China without electricity, and these people are mainly located in remote rural areas where national electricity grids are hard to reach (He & Victor, 2017). Guizhou province has the highest level of population that don’t have electricity or reliable electrical services in China. There are still 32,120 rural people in Guizhou that are not electrified according to the latest data available (China Southern Power Grid, 2016). Considering these families are hard to be reached by grid in the short term, government is planning to provide electricity to these last people through off-grid renewable systems such as solar home systems.

4.2.2 Individual Households in Areas without Adequate Electrical Services Potential market of solar homes system in Guizhou also includes rural households with inadequate electricity supply. In Guizhou, although majority of the rural households have been served with electricity via national grid, a lot of them still experience inadequate and unreliable electric power supply characterized by high voltage variations, recurrent power failure and black-outs, and pervasive reliance on self-generated electricity. The unreliable and inadequate power supply has made it inability to meet the growing electricity demand of rural households in Guizhou

70 province. And also because those households without reliable electrical services have to rely on self-generation when power failures occur, their costs spent on electricity are increased and their economic burdens are also raised. According to the latest “Report on the Work of the Government” issued by each 88 counties in Guizhou province, an estimate of a total 812,000 rural people in the province still suffer from inadequate or unreliable power supply, that equals to 3.54% of Guizhou’s total rural population. Altogether, around 4% of the rural population in Guizhou has no electricity or reliable electrical services – one of the highest in China. Therefore, the need for the alternative source of electricity supply becomes more apparent. And off- grid renewable energy options particular solar home systems become an ideal alternative considering its reliability and cost competitiveness.

Table 4.3 Assess to Electricity in Guizhou Province.

Number of population % Of rural population Without access to electricity 32,120 0.14% Without adequate or reliable 812,000 3.54% electrical services (high voltage variations, power failure, blackout, pervasive self-generated, etc.) Source: China Southern Power Grid, 2016.

The main obstacle to adequate and reliable electricity supply in Guizhou is the lack of adequate power infrastructure and services. Power grid infrastructure in Guizhou, especially in remote rural areas are poor, resulting in it is unable to meet the increasing electricity demand of rural households. Especially during the evening when the loads surpass the grid generation, a blackout occurs. In addition, existing power facilities in rural Guizhou lacks maintenance due to inadequate financing and

71 techniques, and this leads to many reliability issues. For example, by the end of 2014, the coverage of power grid maintenance in rural Guizhou was only 29% (SASAC, 2016). This means when power outrage occurs, only a small percentage of rural households could get immediate maintenance. In the past decade, Guizhou provincial government has made great efforts to improve electricity supply situation in the province. In 2014, China Southern Power Grid proposed a “Well-off Electricity Plan”, planning to invest 1.5 billion CNY for power infrastructure upgrade in rural Guizhou (China Energy, 2014). Under the Plan, by 2020, the rural electrification rate is expected to reach the same as urban rate in Guizhou, and the power grids will be smarter, safer and greener. In addition, Guizhou governments will invest 30 billion CNY for upgrading the rural electrical grid system for 1,301 counties and towns during the 13th Five-Year Plan period (China Southern Power Grid, 2016). By 2020, it is expected that grid reliability in rural Guizhou will reach 99.8%, voltage eligibility rate will reach 97.9%, and the average capacity of the distribution transformer should be no less than 2,000 VA per rural household (China Southern Power Grid, 2016). Besides the power infrastructure gird upgrade, renewable energy particular solar energy has been regarded as an ideal alternative to power supply in Guizhou in recent years. In the past, Chinese government has been actively promoting the implementation of distributed and stand-alone renewable systems, such as solar home systems for rural households to meet their energy demands, however Guizhou province is lagging behind. By the end of 2014, Guizhou has no installations of solar systems of any kind, and it is also the only province that has no solar installation in China. Until 2015, a first distributed solar project was proposed in Liu Zhi, a township in rural Guizhou, aiming at poverty reduction and power supply. The first round of

72 this project was implemented in 2016, constructing solar home systems for 13 rural households and showing great success (Solar Bee, 2016). The idea behind this first solar PV project is to allow Guizhou to draw lessons before a more provincial-wide PV project is implemented. In addition, this project raises awareness for the benefits of solar home system in terms of poverty reduction and power supply. In 2013, the NDRC announced a 20-year feed-in tariff (FIT) of 0.42CNY/kWh on top of the local coal-fired electricity price for distributed solar PV projects implemented in China (NDRC, 2013). Until of today, this rate remains the same. The FIT creates a favorable environment for solar home system implementation in Guizhou, as this subsidy reduces households’ economic burdens for system installation and operation. Provinces and cities are encouraged to develop extra premium on the top of the national level FIT pricing scheme to complement the national FIT. As of today, Guizhou has no specific regulations or rules on pricing scheme for the solar projects installed in its area. However, the government has put this on its agenda for the future development of solar energy in the province.

4.3 Access to Clean Cooking Fuels in Guizhou Province Although China has achieved ubiquity of electricity access in rural areas during past years, solid fuels are still widely used in the rural areas especially in relatively poor provinces such as Guizhou. In this study, the potential target market for biogas digester in Guizhou Province includes individual households in areas currently still rely on solid fuels (coal and biomass such as firewood) as their primarily cooking fuels. In Guizhou, traditional biomass stoves are widespread in rural areas, and some households still use open fire. According to the national census data, 90% of Guizhou

73 households used solid fuels for cooking in 2000 (National Bureau of Statistics, 2004). However, in the past decade, coal and biomass have been replaced by electricity or gas, and increasing number of rural households in Guizhou have been seen using biogas digester to produce gas from animal manures and crops residue. According to the census data, 30% of households used coal and 32% of households used biomass as their main cooking fuels in 2010 in the province (National Bureau of Statistics, 2012). Among rural households, 34.7% used coal and 45.4% used biomass (National Bureau of Statistics, 2012). Considering that there are about 6.5 million rural households in Guizhou, that equals to about 2.25 million and 2.97 million rural households still use coal and biomass for cooking respectively. Given this situation, Guizhou is now among the top provinces in terms of using solid fuels for cooking, after Inner Mongolia, Jilin, Liaoning, and Heilongjiang (Figure 4.4).

Figure 4.4 The Distribution of Rural Households Mainly Using Solid Fuels for Cooking in China. Source: Tang & Liao, 2014.

In the past decade, the sources for energy used for cooking in Guizhou have been gradually diversified due to increased household income and improved living conditions. Now modern fuels used for cooking in Guizhou mainly includes gas and electricity. In 2000, only 0.5% of rural households relied on electricity for cooking (National Bureau of Statistics, 2005). This number increased to 1.4% in 2010 (National Bureau of Statistics, 2011). Likewise, the percentage of rural households rely on gas for cooking increased from only 1.4% in 2000 to 17.7% in 2010 (National Bureau of Statistics, 2011). However, the uptake of modern fuels in Guizhou still remains low in terms of absolute number. Today, less than 20% of rural households in the province cook from electricity or gas because modern fuels are relatively

75 expansive while biomass sources are available through non-commercial means in rural areas. Therefore, improving access to affordable and clean cooking fuels for rural households remains a great challenge that Guizhou government needs to address. And this also presents great opportunity to develop alternative sources for cooking that are cheaper, cleaner and more reliable.

Table 4.4 Changes of Rural Households Cooking Fuels Structure in Guizhou Province, 2000 – 2010.

2000 2005 2010 Coal 34.7% (2.25 million households) Biomass 45.4 % (2.97 million households) Total rural house 99.1% 97% 80.1% using solid fuels Gas 0.5% 1.8% 1.4% Electricity 0.3% 1% 17.7% Total rural 0.8% 2.8% 19.1% households using modern fuels Source: National Bureau of Statistics, 2005; National Bureau of Statistics, 2011.

76 Chapter 5

CASE STUDY OF SOLAR HOME SYSTEMS IN GUIZHOU PROVINCE

5.1 Overview of Solar Home Systems Solar home systems are stand-alone PV systems that produce electricity. Such system is one of the most commonly used stand-alone systems that offer a cost- effective way of supplying electricity to remote off-grid households. In rural areas where households are not connected to the grid, the system is used to meet the household’s basic energy needs. Globally, the system has been implemented in numerous countries and provided power to thousands of households in remote areas where grid extension is not feasible. A solar home system is typically composed of a solar panel consisting of solar cells, an inverter that converts DC (direct current) power to AC (alternating current), a charge controller which distributes power and protects batteries and appliances from damage and sometimes a battery storage to store energy for use when the sun is not shinning. Furthermore the system is connected to the household’s load such as lights, radio and small TVs.

Figure 5.1 Major Components of a Solar Home System.

The most important component of the system is the solar panel, which is made of solar cells that made from silicon. Today, the most common types as the material for solar cells include monocrystalline silicon, multicrystalline silicon, polycrystalline silicon, and amorphous silicon. An individual PV cell is usually small both in size and power output, typically producing about 1 or 2 watts of power (Department of Energy, 2016). To produce more power, PV cells are connected together to form large units which are called PV modules. Modules can also be grouped together to form even larger units called panels or arrays, if more power is needed. No matter PV cells, modules or arrays, they can directly covert sunlight into electricity using semiconductors, in a manner similar to electronic transistors.

Figure 5.2 PV Cell, Module and Array. Source: Department of Energy, 2016.

In addition to electricity generation device of solar panel, the system is usually equipped with balance of system (BOS) that includes a charge controller, an inverter and a battery storage. Because solar is an intermittent energy resource that is only available at certain times of a day, it is critical for the solar home system to have an energy storage capability. Batteries are often used in solar home systems in order to store energy produced by PV modules during times of resource availability and then supply the excess energy to electrical loads as needed (such as during the night or when there is no other energy input). Another reason that batteries are used in solar home system is to operate the PV modules near their maximum power point and to power electrical loads at stable voltages (Florida Solar Energy Center, 2016). To protect the batteries from being over-charged by the PV panel and to keep it from being over-discharged by electric loads, a battery charge controllers is used to reduce or stop the charging current when the battery reach its charge or discharge limits. Benefit of having charge controller is that it can automatically connect and disconnect

79 an electrical load at a specified time, such as operating a light from sunset to sunrise. Furthermore, to invert the direct current (DC) output into alternating current (AC) powered appliances, a DC/AC inverter is needed so that the systems’ DC power can be used by the loads.

5.2 Solar Resource Potential in Guizhou Province

5.2.1 Overview of Solar Resource in China China’s solar potential is estimated using annual radiation values and annual solar hours values provided by the China Meteorological Administration. According to the 716 China Meteorological Administration stations, there are four major solar zones in China (NEA, 2014). Zones are identified based on the geographical differences of thermal and electric powers that solar radiation can produce. In general, China’s solar resources are concentrated in the western, northern, and southwestern regions of the country. Table 5.1 breaks down the regions into zones for greater detail and shows the annual solar radiation and hours of sunshine for each zone. It is noted that any areas in zone 3 or above are considered as suitable area for developing solar energy.

Table 5.1 Solar Zones in China.

Zone Classification Total solar Hours Covering areas radiation per of year sunshine (kWh/m2) per year 1 Very Rich >6300 MJ/m2 >3200 West Qina Banner of Inner >1750 Mongolia, West of Jiuquan of kWh/m2 Gansu, West of Qinghai, West of Tibet, East of Xinjiang, Ganzi of Sichuan 2 Rich 5040-6300 2200- Most areas of Xinjiang, East of

80 MJ/m2 3200 Gejina Banner of Inner Mongolia, 1400-1750 West Heilongjiang, West Jilin, West kWh/m2 Liaoning, Most area of Hebei, Beijing, Tianjin, East Shandong, Most area of Shanxi, North Shan’xi, Ningxia, East Jiuquan of Gansu, East Qinghai, East Tibet, Central and West Sichuan, Yunnan, Hainan 3 Good 3780-5040 1400- North Inner Mongolia, Most area of MJ/m2 2200 Heilongjiang, Central and North 1050-1400 Jilin, Central and East Liaoning, kWh/m2 Central and West Shandong, South Shanxi, Central and South Shan’xi, East Gansu, Central Sichuan, East Yunnan, South Guizhou, Hunan, Most area of Hubei, Guangxi, Guangdong, Fujian, Jiangxi, Zhejiang, Anhui, Jiangsu, Henan 4 Moderate <3780 MJ/m2 1000- East Sichuan, Most area of <1050 1400 Chongqing, Central and East kWh/m2 Guizhou, West Hubei, West and East Hunan Source: NEA, 2014.

The map below shows annual total sunshine hours vary considerably across provinces in China (CMA Wind and Solar Energy Resource Center, 2011). The largest annual totals could be as high as 3,330 hours per year, and the smallest totals is low as 900 hours per year (cities of Lenghu and Yibin respectively). As a whole, the western parts of China, which cover the Tibetan Plateau and Xinjiang, are extremely favored by high sunshine hours. In addition, there is also ample sunshine in a small belt area from Xinjiang to Inner Mongolia. The annual sunshine duration is over 2,500 hours in these areas. By comparison, sunlight duration is shorter in South China including southeastern Tibetan Plateau and south Yunnan Plateau. The sunlight duration rarely exceeds 2,000 hours in these areas due to their geographic conditions. The lowest

81 sunshine totals occur in the Sichuan Basin where, on average, the annual sunlight duration even drops to 1,000 hours.

Figure 5.3 Average Annual Total Sunshine Hours across China. Source: CMA Wind and Solar Energy Resource Center, 2011.

5.2.2 Overview of Solar Resource in Guizhou Province In general, solar resources in Guizhou Province are not as aggressive as popular solar provinces such as Xinjiang or Inner Mongolia. Its average annual total solar radiation ranges from 1,194 to 1,600 kWh/year, where eastern part of the province has less sunshine while western and southwestern areas have more sunshine (China Energy Storage, 2016). The average annual total solar hours in Guizhou

82 province varies from 900 to 1,800 hours/year (China Energy Storage, 2016). Again, western and southwestern areas have more solar hours than the east. In this sense, western and southwestern Guizhou is considered as solar zone 2 and 3 (rich and good), while eastern part of Guizhou is belonged to the solar zone 4 (moderate). Of all the cities and counties in Guizhou, Weining County has the riches solar resource with a total solar radiation of 1,600 kWh/year and total hours of sunshine of 1,812 hours/year (Xinhua Net, 2015). This makes the county as competitive as some counties in Inner Mongolia and Xinjiang that are well known for their abundant solar resources.

5.2.3 Potential Solar Home System Markets in Guizhou Province By the end of 2014, no single solar project has ever been implemented in Guizhou province. Only by recently in 2016, a first solar project is implement in Liu Zhi city in Guizhou, constructing solar home systems for its 13 rural households (China Energy, 2016). This is because in the past, solar technology only favors big solar cities over cities with moderate solar resources. However, with technology development, more and more people recognize that even with moderate solar resources, solar systems are still applicable to those areas and could provide sufficient electricity to meet people’s daily energy demand. It is usually accepted that a daily sunlight hours no less than 3.5 hours will be sufficient power a solar home system for a household with 2-3 people. In this sense, any area with annual solar hours more than 1,250 hours will be considered as potential places to develop solar home systems. The annual solar radiation and annual solar hours data are extracted from China Meteorological Administration for each county of Guizhou province. Among all its 88 counties, 42 counties are identified with annual solar hours more than 1,250 hours (China Energy Storage, 2016). This means nearly half of the province has

83 potentials to develop solar home systems that could provide power to meet their people’s daily electricity needs. The map below drawn by GIS shows the annual average solar hours across 88 counties in Guizhou. The highlighted counties are the ones that have annual solar hours more than 1,250 hours and are considered as potential counties for developing solar home systems. Geographically, all these counties are concentrated in the south and southwestern parts of Guizhou where solar resource is better than the rest of the province. Among all these 42 counties, Weining County ranks first in terms of both annual solar radiation and annual solar hours.

Figure 5.4 Annual Solar Hours of Guizhou Counties.

85 In terms of electricity access, all together, these counties account for 95.1% (a total of 30,546 households) of the total unelectrified households in Guizhou and 80.6% (a total of 654,427 households) of the households that without adequate electrical services in the province (Guizhou Academy of Social Science, 2015). Therefore it is of great significance to develop solar home system in those 42 counties because the system offers an alternative model of providing power to households that don’t have the access to reliable electricity. The table below lists each of these 42 counties in terms of their annual solar radiation and solar hours, and number of households that don’t have access to electricity or reliable electrical services.

Table 5.2 Potential Markets for Solar Home Systems in Guizhou Province.

Counties Annual Annual No. of No. of % solar solar hours households households Households radiation (hours/year) without without without (kWh/year) electricity reliable electricity or electrical adequate services electrical services 1 Weining 1,600 1,812 20,235 80,544 27.79% 2 Xingyi 1,555 1,769 3,855 21,307 9.26% 3 Ceheng 1,555 1,713 3,212 2,6762 38.94% 4 Liupanshui 1,388 1,253 NA NA City 5 Zhongshan 1,400 1,556 101 17,200 8.93% 6 Panxian 1,388 1,593 95 23,500 5.36% 7 Liuzhi Tequ 1,397 1,252 87 15,626 9.76% 8 Shuicheng 1,394 1,430 108 24,022 10.11% 9 Renhuai 1,333 1,400 76 4,736 2.15% 10 Chishui 1,333 1,297 122 6,821 6.81% 11 Tongren 1,361 1,250 NA NA City 12 Jiangkou 1,306 1,257 77 4,500 5.75% 13 Sinan 1,361 1,250 87 51,933 23.71%

86 14 Yinjiang 1,344 1,310 95 10,095 6.96% Tujiazu 15 Qianxinan 1,556 1,589 133 Buyizu 16 Xingren 1,528 1,564 88 30,128 17.3% 17 Pu’an 1,389 1,528 79 28,108 25.58% 18 Qinglong 1,444 1,462 78 7,000 6.56% 19 Zhenfeng 1,528 1,549 69 6,000 5.03% 20 Wangmo 1,556 1,520 54 8,000 7.88% 21 Anlong 1,528 1,545 107 4,000 2.7% 22 Bijie City 1,472 1,423 NA NA 23 Dafang 1,400 1,335 98 9,130 2.97% 24 Qianxi 1,389 1,348 96 10,000 3.34% 25 Nayong 1,383 1,423 111 9,480 2.92% 26 Hezhang 1,400 1,548 69 21,395 8.33% 27 Ziyun 1,400 1,455 144 20,000 15.79% Miaozu 28 Kaili city 1,306 1,289 79 10,299 6.62% 29 Sanhui 1,300 1,255 71 3,900 5.4% 30 Jianhe 1,311 1,236 87 4,500 5.18% 31 Taijiang 1,344 1,300 69 5,620 12.39% 32 Liping 1,306 1,317 88 8,900 7.16% 33 Rongjiang 1,350 1,312 79 15,442 13.12% 34 Congjiang 1,350 1,440 114 25,700 28.11% 35 Duyun 1,306 1,298 108 34,671 21.98% 36 Libo 1,311 1,311 99 19,479 34.71% 37 Fuquan 1,311 1,253 97 7,900 7.47% 38 Dushan 1,344 1,323 84 15,907 14.04% 39 Pingtang 1,350 1,363 74 7,800 7.41% 40 Luodian 1,400 1,398 77 6,300 6.4& 41 Changshun 1,398 1,227 76 7,670 9.13% 42 Huishui 1,389 1,325 69 9,800 6.67% Total 1,306 – 1,250 – 30,546 654,427 1,600 1,812

5.3 Energy Analysis of Solar Home Systems in Guizhou Province In order to exam the sustainability solar home system in Guizhou rural areas, the first thing first is to figure out what the size of the system will be best utilized in

87 the province. Thus this section reviews technical issues regarding system design, supply capacity and energy reliability of solar home system in Guizhou.

5.3.1 An Overview of RREAD for Energy Analysis The energy performance of solar home system in this dissertation is evaluated by the spreadsheet model RREAD (Rural Renewable Energy Analysis and Design Tool). This model is developed by researches from the Center for Energy and Environment Policy (CEEP), and it has been used in several CEEP-based research projects such as the off-grid renewable energy options for rural electrification in western China project that has been conducted in 2001. The model is consisted of three modules: 1) a data impute module, 2) a calculation engine and 3) an output module. For energy analysis, the input data includes (1) resource and climate data, (2) household load data and (3) solar home system configuration data. Each of these sets includes a number of sub-category data. By running the model, RREAD is able to size the system component such as the battery bank, inverter and controller. Also, RREAD calculates the system’s net energy output. If the net energy output is equal or greater than the customer’s load requirement of the same day, RREAD will go to the next step. By contrary, if the net energy output is not sufficient to the household’s energy demand, then battery will be used. If the sum of net energy production and battery energy is still not sufficient than the demand, then this day will be regarded as an energy shortfall day. Once total shortfall days in a month are summed, monthly shortfall days are calculated.

88 Data inputs RREAD calculation Results/Outputs Resource and climate data --solar insolation --hourly/monthly Wind speed --ambient temperature

Load data Energy performances --number, type and --sizing of renewable rated power of energy system (battery appliances bank, inverter and --daily operating hours Energy controller) Evaluation --energy output

System configuration --monthly energy data shortfall days and the --PV system: angle, magnitude of the energy area, efficiency, shortfall lifetime, etc. --comparison to --wind: height, competitive engine diameter, power, generator lifetime, etc. --BOS: battery size, depth of discharge, lifetime, size of controller, size of inverter, etc. --engine generator: power, operating hours, fuel consumption, lube consumption, etc.

Figure 5.5 An Overview of RREAD Energy Analysis for Solar Home System.

5.3.2 Sizing of Solar Home Systems Sizing the Solar PV Panel In order to exam the sustainable benefits of solar home system for rural development in Guizhou, first thing first is to figure out what type of the system is utilized in the Province. Today the most widely used solar panel in China is the 60-cell ALLMAX module by Trina Solar, a leading solar manufacturer in China (Trina Solar, 2016). The power output of this module is 260W, and its maximum module efficiency

89 is 16.5% (Trina Solar, 2016). The module lifetime warranty, as claimed by manufacturer, is 10 years (Trina Solar , 2016). However, many modules currently come with a longer period of warranty, which is often from 15 to 20 years (Solar of Week, 2017; BJX, 2016; Solar of Week, 2016). Considering the average electricity consumption for rural household in Guizhou is about 1.8kWh/day, 2 sets of this module will be required for the household to meet its daily electricity consumption (Guizhou Bureau of Statistics, 2016). This is to say the assumed solar home system capacity for Guizhou rural households will be 260W * 2 = 520W.

Sizing of Battery Bank In addition to the panel size, BOS components such as battery bank, inverter and controller are critical to a renewable energy system, hence they should be properly sized. If not, they can hurt the operation of the system. Unlike the shallow-cycle batteries, as those for cars, that are designed to deliver instantaneous high amperes for a few seconds to start an engine; batteries in a solar home systems are designed to provide constant currents over a period of time. The size of a battery bank is depended on several factors, such as the battery’s daily energy output, the depth of discharge rate (DoD), and the power reserve margin. The size can be set from two ways: one is from supply perspective and the other is from customer perspective. From a supply side, the battery size is equal to the energy delivered to the battery bank from the PV modules. From the customer side: the battery size is set at a value equal to customer’s load demand each day. As the battery size could be set either in supply or in demand perspective, RREAD calculates the size of the battery bank in both ways.

90 Battery capacity is generally measured in “amp-hour” (Ah), which is derived from watt-hour (Wh) divided by voltage (V) (IRENA, 2012). Battery voltages are generally 12, 24 or 48 V and the actual V is determined by the requirements of the system. As a general rule, the recommended system voltage increases as the total load increases. For small daily loads, a 12 V voltage can be used. For intermediate daily loads, a 24 V voltage can be used (IREANA, 2012). From a supply perspective, the battery capacity is measured as daily energy output of the generation device (kWh) divided by the battery voltage (V). For example, for a 200 W solar home system whose daily output is 1 kWh, the daily energy delivery value of a 12V battery bank would be 1,000Wh/12V = 83.3 Ah; for a 24 V battery bank, the daily energy delivery value would be 1,000Wh/24V = 41.6 Ah. In this study, the battery size is determined from customer perspective. From a customer perspective: the battery’s daily delivery capacity is measured as the customer’s load requirement (kWh) divided by the battery voltage (V). So the key difference between the supply and customer perspectives is the former is the energy delivered to the battery bank, while the latter is the energy that the battery bank delivers to the loads. Typical electrical appliances used in rural households in Guizhou can be classified in two categories: (1) radio, television and other entertainment appliances and (2) refrigerators, rice cookers, lights, lamps and other appliances can be used for cooking or domestic work. The table below summarizes major appliances used in a typical rural Guizhou household and the number of hours used by each appliance (Guizhou Bureau of Statistics, 2016). It reveals that 1.8kWh of electricity is needed

91 for a rural household with an average of 3 people in Guizhou to power their basic appliances.

Table 5.3 Rural Household Electricity Consumption in Guizhou Province (kWh/day).

Appliances Number of Capacity (W) Number of Electricity units hours used consumption each day (kWh) Fluorescent lamp 4 18 5 0.36 TV 1 60 4 0.24 Refrigerator 1 75 12 0.9 Rice cooker 1 200 1 0.2 Other appliance 1 100 1 0.1 Total=507 Total=1.8 Source: Guizhou Bureau of Statistics, 2016.

It is important to note that the customers’ load requirement must take account the power losses. The power losses could come from both the battery bank when it is being charged and from the inverter when the DC power is converted to the AC. Normally a 10% to 30% power loss will happen in the battery bank and a 5% to 10% will occur during the energy conversion process (IRENA, 2012). Considering different models of battery or inverter have different losses values or efficiencies, RREAD allows the users to specify battery and inverter efficiencies values by themselves. In this study, the battery efficiency is assumed at 75% and 90% efficiency is assumed for the inverter. This is because the most commonly used battery and inverter used in China now have an average efficiency at 75% and 90% respectively (Solar of Week, 2017). A battery bank will be severely damaged if it is over-discharged. To protect the battery from being overused, the battery bank should be sized properly so that only a

92 portion of it will be charged/discharged each time. This is determined by the depth of discharge (DOD). This is the percentage of the battery capacity that you can withdraw from the battery. For instance, a 50% DOD refers to a battery that is being discharged at 50% of its total capacity each day. Max DOD stands for the maximum depth of discharge. In general rule, the deeper you discharge a battery the fewer life cycles the battery will have. For example, if you drain 90% - 100% of a battery’s power, you will shorten the life of that battery radically. To avoid this, a controller must be placed to prevent the battery of being over-discharged. The max DOD could be set from 30% to 80%, depending on battery’s manufacturer and quality (IRENA, 2012). New and high quality batteries tend to have deeper discharges while old or low quality batteries only have shallow discharges. Discharges rates could be specified in RREAD based on their quality and age. The battery DOD of this study is set at 40% since this is the most practical number to use on a regular basis, which means a battery is only be charged of its 40% total capacity each day (Growatt, 2017). In addition to DOD, days of autonomy should also be paid attention to when sizing the battery. Days of autonomy are the number of days that the appliances can operate without charging from the renewable systems devices. This is important because renewable energies such as solar and wind are intermittent resources, supply shortfalls are likely to occur when is raining or cloudy. If weather condition is not permitted, a battery bank should have the ability to ensure an uninterrupted flow of energy to appliances. In this sense, energy produced by the system from previous days will be stored in the battery bank, and then be used on days when weather condition is not good. Again, RREAD allows user to specify the days of autonomy based on users’ specific needs. The battery reserve margin is set at 2 days for this study since this is

93 generally accepted as standard (Civic Solar, 2016). This means that the battery bank should be capable of delivering to least 2 days of energy supply before it is being charged again. The battery capacity (Ah) could be determined based on the household’s load value, efficiencies of battery and inverter, battery’s DOD and reserve margins values. In this study, for a household of 1.8 kWh electricity consumption a day, a 12 V battery bank requires a total of storage of 1,111.11 Ah (12V). Considering a single battery size is of 200Ah, it requires 6 batteries to meet the household’s energy demand. The result is derived from the following steps: Step 1: Calculating the daily delivery value requirement for the battery: 1.8 kWh/day (daily energy load) ÷ 75% (battery efficiency) ÷ 90% (inverter efficiency) ÷ 12V (battery voltage) = 222.22Ah/day Step 2: Calculating the battery’s daily storage capacity with a 40% DOD: 222.22Ah/day ÷ 40% (DOD) = 555.55 Ah/day Step 3: Calculating the battery total capacity requirement with a 2-day reserve margin: 555.55 Ah/day * 2 days (reserve margin) = 1111.1Ah Step 4: Calculating the numbers of batteries needed: 1111.1Ah ÷ 200Ah/unit =~ 6

Sizing of Charge Controller and DC/AC Inverter Sizing a solar home system also requires determining the size of charge controller and DC/AC inverter. Compared to the sizing of battery bank, sizing charge controller and DC/AC inverter is comparatively simpler. Charge controller is a regulator that limits the rate of current that goes to and from the battery bank, therefore preventing batteries from over-charging. As RREAD designs, the size of

94 charge controller should be no less than the size of generation device. Because the solar PV panel examined in this study is at 520W, then a 600W charge controller is needed (there is no 520W charge controller available on Chinese market, the only smallest size available larger than 520W is 600W). In terms of inverter size, from supply perspective, RREAD designs the size of inverter equal to the rated power of the generation device. For example, if the related power of a PV solar system is 520W, than the inverter will be set at 520W. From customer perspective, RREAD sets the size of inverter equal to the total rated power of customers’ loads. Theoretically, the inverter size should be set higher than the total loads of customer’s appliances in order to handle both the surge requirements of appliances (such as refrigerator and water pump) that have electric motors and need higher startup surge and their continuous demand when operating for extended periods. In practice, today’s inverter design has included the both surge and continuous capacity protection so that they are able to start high surge loads and provide continuous output as well. The above-mentioned appliance load of an average rural household in Guizhou is at 507W, then a 600W DC/AC inverter is needed. The details of sizes of PV panel and BOS system are shown in the below table.

Table 5.4 Sizing Solar home Systems for Rural Household in Guizhou Province.

Province Guizhou Appliance Type (AC or DC) AC Total Appliance Load 507 W Daily maximum consumption 1.8kWh PV Required PV 520W Type of PV module Polycrystalline Manufacturer Trina Solar

95 Module areas 3.3 m2 Module efficiency 15% Module lifetime 10 years BOS Battery type Lead-acid Battery Voltage 12V Battery efficiency 75% Required battery capacity 1,111.11 Ah Numbers of battery required 6 Depth of discharge 40% Reserve margin 2 days Battery lifetime 4 years Charge controller size 600W Charge controller lifetime 10 years Inverter size 600W Inverter efficiency 90% Inverter lifetime 10 years

5.3.3 Energy Output of Solar Home Systems The energy output of stand-alone renewable systems is the calculation of how much net electricity could be generated from the solar home system. In this study, the energy output of 520W solar home system is examined in each of the 42 potential markets (the counties with annual solar hours > 1,250 hours and are regarded as potential sites to develop solar home systems). To calculate the electricity output of a PV system, several factors need to be considered. The region’s solar irradiation data should be known first. This is a measure of solar intensity in units of watts per square meter for a specific location. The irradiation information of Guizhou counties is obtained from the local weather data. In order to calculate the total amount of sunlight that solar module can actually receives, latitudes, orientation of the array and array angles information need to be determined for each county of Guizhou. Operating temperature is also an important factor to be considered. Usually PV modules are rated at 25C condition in factory,

96 however when it is operated actually, it is often operated at higher/lower temperatures. As the expected operating temperature or the ambient temperature will have an impact on module’s efficiency which affects the PV system’s total energy output ultimately, the ambient temperature also needs to be determined when calculating the energy output. When the irradiation data, county’s location information, temperature information are combined with PV module information such as module’s rated power, size, angle and orientation, RREAD automatically calculates each county’s hourly electricity output. The output will then be adjusted based on battery and inverter efficiency to get the county’s net energy output. In addition, RREAD aggregates the hourly energy output values to arrive at daily, monthly, and annual values. The daily energy output is used to see if the solar home system is able to meet the household’s daily electricity need in the county. The monthly energy output value is used to evaluate the solar home system’s seasonal performance. And the annual energy output is used to evaluate the system’s economic performance. The table below shows the energy output results from the RREAD for the 42 identified potential counties in Guizhou province. According to RREAD, net energy output from those 42 potential counties ranges from 526kWh to 647kWh per year. Geographically, in general, counties in southwestern Guizhou such as Xingyi and Weining have more annual electricity output, since these counties have higher solar radiation as well as annual solar hours. Seasonally, spring and summer months show the greatest energy output since there are less raining days in those months.

Table 5.5 Annual Net Energy Output for the 42 Potential Counties in Guizhou Province.

Counties Annual solar Annual Solar Annual net energy

97 radiation (kWh/m2) hours output (kWh) 1 xingyishi 1600 1,769 647.0 2 weining 1600 1,812 647.0 qianxinan 3 buyizu 1,556 1,589 629.0 4 wangmo xian 1,556 1,520 629.0 5 ceheng xian 1,556 1,713 629.0 6 xingren xian 1,528 1,564 617.8 7 zhenfeng xian 1,528 1,549 617.8 8 anlong xian 1,528 1,545 617.8 9 bijieshi 1,472 1,423 595.3 10 shuicheng xian 1,444 1,430 584.1 11 qinglong xian 1,444 1,462 584.1 12 zhongshan qu 1,400 1,556 566.1 13 dafang xian 1,400 1,335 566.1 14 hezhang xian 1,400 1,548 566.1 15 ziyunmiaozu 1,400 1,455 566.1 16 luodian xian 1,400 1,398 566.1 17 liuzhi tequ 1,397 1,252 565.0 18 liupanshui shi 1,389 1,253 561.6 19 pan xian 1,389 1,593 561.6 20 puan xian 1,389 1,528 561.6 21 qianxi xian 1,389 1,348 561.6 22 huishui xian 1,389 1,325 561.6 23 nayong xian 1,383 1,423 559.4 24 tongren shi 1,361 1,250 550.4 25 sinan xian 1,361 1,250 550.4 26 rongjiang xian 1,350 1,312 545.9 27 congjiang xian 1,350 1,440 545.9 28 pingtang xian 1,350 1,363 545.9 yinjiang 29 tujiazu 1,344 1,310 543.7 30 taijiang xian 1,344 1,300 543.7 31 dushan xian 1,344 1,323 543.7 32 renhuai xian 1,333 1,400 539.2 33 chishui xian 1,333 1,297 539.2 34 jianhe xian 1,311 1,236 530.2 35 libo xian 1,311 1,311 530.2

98 36 fuquan xian 1,311 1,253 530.2 37 jiangkou xian 1,306 1,257 527.9 38 kaili shi 1,306 1,289 527.9 39 liping xian 1,306 1,317 527.9 40 duyun shi 1,306 1,298 527.9 41 qiandongnan 1,300 1,296 525.7 42 sansui xian 1,300 1,255 525.7 Average 1,300 – 1,600 1,250 – 1,812 525.7 - 647

5.3.4 Reliability of Solar Home Systems Reliability of a solar home system is to see if the system could meet the household’s daily energy needs. Therefore, reliability could be determined by comparing the system’s capability and the customer’s energy requirements. In a certain day, if the system’s energy output couldn’t meet the household’s energy requirement, then the energy shortfall happens and outside energy supply should be captured from the battery bank. If the maximum capacity of battery bank has been reached but still the energy output is not sufficient, then a shortfall day occurs. The average rural household in Guizhou province consumes around 1.8kWh per day. Therefore, if the solar home system’s daily net energy output is equal or larger than 1.8kWh, it indicates that the system is sufficient to meet that day’s energy load. If the system’s daily net energy output is less than 1.8kWh, then potential energy shortfall occurs and battery bank is needed to make up for the shortage. If shortage still exists after taking into account the battery’s supply, then that day is regarded as a shortfall day. In Guizhou, in general, during the summer and fall months such as May, June and July, solar home system could generate higher electricity than other months in the year. This is because during these months, raining days are less and sun is shining stronger. Therefore, for these months, energy shortfall or energy shortfall days are less

99 likely to occur. By contrast, during the winter, because sunshine is limited, the energy output from the solar home system is unable to meet the customer’s requirement. Thus battery needs to be reached out or outside energy supply should be backed up. In order to see how reliable the solar home system is, Weining count is taken as an example here. The county has the best solar resource in Guizhou, thus it has the largest annual net energy output at 647 kWh. Figure 5.6 shows Weining’s monthly energy output from solar home system. May is the month that the county has the largest electricity output. From March to September, the system’s output exceeds the energy demand of the household in Weining, which means there is no energy shortfall occurs during the time. However, during the months of January, February, October, September and December, since the solar home system is unable to meet the household’s energy demand, batteries need to be reached out.

System Monthly Outputs in Weining (kWh)

100

kWh 40

0 Jan Mar May Jul Sept Nov

Month

Figure 5.6 An Example of Weining County in terms of its Monthly Net Energy Output.

100 RREAD can automatically calculate the shortfall days for a particular location. Figure 5.7 shows the monthly energy shortfall days after considering the energy supply from the batteries in Weining county. There are a total of 129 days are considered as energy shortfall days in Weining county, with most shortfall days occurred in March, November and December. When those days happen, households from Weining county need to seek alternative methods such as diesel generator to meet their electricity needs. This, on one hand, poses potential challenge for the sustainable development of solar energy in the long-term. However, in the other hand, it provides opportunity for technology advancement in future that can improve the energy performance of the solar home system.

Shortfall Days By Months in Weining 35 30 25 20 15 10

Monthly Shortfall Days 5 0 Jan Mar May Jul Sept Nov Month

Figure 5.7 An Example of Weining County in terms of its Monthly Energy Shortfall Days.

It is important to note that household energy requirement varies from day to day and month to month. For example, during the summer time, daylight hours are

101 longer, thus less energy is needed during the time due to less lighting demands. In this sense, the household’s day-to-day load profile needs to be determined to best study the reliability of solar home systems. In addition, the household could reduce the potential energy shortfalls either from supply perspective or demand perspective. From supply side, the customer could switch to a larger rated power system that has higher energy output (but this also results in higher capital cost). From demand side, household can achieve the goal of reducing energy shortfall by controlling their energy requirements. For example, during the wintertime, people can manage to offset energy inefficiency by turning off refrigerator. Or during the summer, they can help to avoid energy shortfalls by turning on lights for shorter time.

5.4 Economic Analysis of Solar Home Systems in Guizhou Province

5.4.1 Overview of RREAD for Economic Analysis The above-mentioned evaluation of energy output of solar home systems is very important because this helps to exam whether the system could meet the household’s daily, monthly and annual energy needs from technical perspective. Equally important, the economic analysis of solar home systems can help to evaluate the cost-effectiveness of the system and compares the system with other energy options. Similar to energy analysis, RREAD model is used to evaluate the economic performance of the solar home system in rural Guizhou. The model for economic analysis also has three modules: a data input module, a calculation engine and an output module. Cost information of the system, as well as financial terms and subsidy data are used as the input values in RREAD for its economic evaluation. Once data are

102 input, RREAD calculates the levelized energy cost of the solar home system over its evaluation period. In addition, the model reports the economic performance of the competitive traditional energy generation options such as diesel generator. This provides a clear idea of how the solar home system can provide greater economic benefits than their competitors in rural Guizhou.

Data inputs RREAD calculation Results/Outputs

Cost data --capital costs of PV, biogas digester, competitive energy generators --replacement costs of system parts --shipping Economic --installation performances --O&M costs --net present value --fuel delivery costs (NPV) costs of the

--salvage values Economic systems --levelized energy costs Evaluation (LCOE) of the systems Financial data --comparisons between --discount rate renewable systems and --lifetime their competitive --current exchange rate traditional generation --tariff systems in terms of LCOE

Policy data --subsidy --rebate --social and environmental value

Figure 5.8 Overview Structure of RREAD to Calculate the Economic Performance of Renewable Energy System.

103 5.4.2 Preparation of Cost Stream To evaluate the economic performance of solar home system, several cost factors need to be determined. These factors include the equipment costs, BOS costs, and annual operating and maintenance (O&M) costs. The equipment costs mainly include the cost of PV module and the costs of transportation and setting up the system. Since the equipment might be still valuable after the evaluation period, a straight-line depreciation method is used in RREAD to determine the scrap/residual value of the system. And this method is a default depreciation method used to gradually reducing the costs of the system in equal amounts over its useful life. The BOS costs include the sale prices of battery, inverter and controller. Because the battery, inverter and controller can’t last forever, their lifetimes should be considered as well as their replacement costs. The O&M costs include the regular services, maintenance and repair costs of the system. Usually solar home system requires very small maintenance every year and major maintenance every several years. In terms of PV module, the current price for a China manufactured PV system is at 4 CNY/W ($0.59/W), so the total module cost of a 520W system will be 4 CNY/W *520W=2080 CNY ($306) (Attia, 2016). For simplification, straight-line depreciation is used to calculate the system’s depreciation expenses. The residual value is what the system is worth at the end of its lifetime period. For this study, a residual value of 10% of its costs is assumed. In terms of BOS system, the most commonly used lead-acid batteries for household PV system in China cost about 150CNY ($22.06) per unit (Taobao, 2017). Because a 520W system needs 6 units of battery, then the total battery cost will be 150CNY/unit * 6 unit= 900CNY ($132.4). Typically, the battery has a lifetime of 4 years. A typical 600W charge controller and 600W inverter cost about 200CNY

104 ($29.4) and 630CNY ($92.6) in China respectively (Taobao, 2017). Both charge controller and inverter have a lifetime of 10 years, which means every 10 years they need a replacement. In addition the up-front costs of a solar home system, operations and maintenance (O&M) costs are also essential in assessing the economic performance of solar home systems. The average cost for installing a solar home system for a home cost in China is around 0.3 CNY/W (Shi et al., 2016). In this sense, the total installation cost will be around 150 CNY ($22). Today, the costs of maintaining a PV system is falling everyday so that it is now increasingly affordable and easy to maintenance a small PV system. Due to technology improvement, once installed, PV systems need very little maintenance. For this study, we assume that the annual operation and maintenance costs around 40CNY ($5.9) per year (Yingli Solar, 2017). This includes simple and limited maintenance such cleaning a few times a year. When summing up all these costs together, the initial upfront cost for a household PV system of 520W is 3,850CNY ($566). Of which, PV module accounts for 54% of the total cost. Other economic information need to be considered includes the interest rate, evaluation year, currency conversion rate, etc. The current discount rate for Chinese manufactured PV system is 2.9%, and the current currency rate is at 6.8 (Attia, 2016; XE Currency Converter, 2017). The financial evaluation time for the solar home system is set at 10 years – same as its manufacturing warranty. The detailed assumption and economic parameter used in this study is shown in the below table:

105 Table 5.6 Cost Streams of Solar Home Systems in Guizhou Province.

System total capital cost 3,850 CNY ($566) PV module as % of the total cost 54% System lifetime 10 years PV Module unit cost 4 CNY/W ($0.59/W) Module size 520W Total module costs 2,080 CNY ($306) Module lifetime 10 years Depreciation Straight-line PV residual value 10% (208CNY, $30.6) BOS Numbers of battery required 6 Battery lifetime 4 years Battery cost (CNY/battery) 150 CNY ($22.06) Total battery cost 900 CNY ($132.4) Charge controller cost (CNY/controller) 200 CNY ($29.4) Charge controller lifetime 10 years Inverter cost (CNY/inverter) 630 CNY ($92.6) Inverter lifetime 10 years O&M Costs Construction including labor fee, labor 156 CNY ($22) insurance, and transportation Annual operation and maintenance 40 CNY ($5.9) Other Basic Economic Information Discount rate (%) 2.9 Evaluation period (year) 10 Currency conversion rate (CNY/US$) 6.8

5.4.3 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) The cost components of solar home systems are only a simple and shallow measure to estimate the economic performance of solar home systems. Consider that nowadays solar home systems have an expected lifetime of approximately 10 – 15 years, in most cases the simple initial cost is not enough because it doesn’t take into account that costs are discounted over the evaluation period. Nor does it include price

106 inflation/discount. For these reasons, it is important to compute net present value (NPV) costs of the solar home system. After the cost stream of solar home system is prepared, the costs are discounted in order to calculate the net present values of systems over the evaluation period. The following formula illustrates how RREAD is used to discount each of the future costs to their present values in the evaluation period. Once the yearly discounted future costs are determined, RREAD sums up all values to arrive at a total NPV. NPV (i, N) = ∑ where, NPV (i, N) = the total net present value of costs over the evaluation time N, N = the number of years in the evaluation time

Ct = net costs value in the year t, and i = discount rate The total net present value costs of solar home system are further standardized over its evaluation years. And this is called the levelized annual NPV cost. In this study, the levelized annual NPV costs refers to the yearly constant cash payment of should be made for solar home system over its evaluation time (Byrne et al., 2001). RREAD utilizes the following formula to calculate the levelized NPV cost: L = ∗ ∗ (L = NPV/n, when i = 0) where L = levelized annual NPV cost NPV = total NPV costs of solar home system in its evaluation time i = discount rate n = number of years in the evaluation time

107 Once the levellized annual NPV cost is determined, the annual NPV cost is divided by the annual electricity value to obtain the unit cost of electricity ($/kWh). And this is called levelized cost of energy (LCOE). In RREAD, LCOE could be calculated from both supply perspective and demand perspective. From supply side, the annual electricity value is how much electricity produced from solar home systems. From the demand side, annual electricity value is how much consumed from the end-users. In this study, the demand perspective is used when calculating the LCOE. However, when the system supply couldn’t meet the household’s consumption, then supply perspective is applied instead. The below table depicts the results of RREAD analysis for the levelized energy costs for the 42 potential counties in Guizhou. The quality and quantity of renewable energy resource influences the generating capacity of solar home systems by county, so does it affects the overall economic performance of systems. Counties with more solar resources such as Weining, has levelized energy costs as low as $0.13/kWh, while counties such Jiangkou, Kaili, Sanhui, etc. have lower a high levelized energy cost of $0.17/kWh as they have relatively less solar resources.

Table 5.7 Levelized Energy Costs for Solar Home Systems in the 42 Potential Counties in Guizhou Province.

Annual Net Total solar Levelized solar energy Counties radiation costs hours output (kWh/year) ($/kWh) (kWh)

1 Weining 1,600 1,812 647 0.13 2 Xingyi 1,555 1,769 628.8 0.14 3 Ceheng 1,555 1,713 628.8 0.14

108 Liupanshui 4 1,388 1,253 561.3 0.16 City 5 Zhongshan 1,400 1,556 566.1 0.15 6 Panxian 1,388 1,593 561.3 0.16 Liuzhi 7 1,397 1,252 564.9 0.15 Tequ 8 Shuicheng 1,394 1,430 563.7 0.15 9 Renhuai 1,333 1,400 539.0 0.16 10 Chishui 1,333 1,297 539.0 0.16 Tongren 11 1,361 1,250 550.4 0.16 City 12 Jiangkou 1,306 1,257 528.1 0.17 13 Sinan 1,361 1,248 550.4 0.16 Yinjiang 14 1,344 1,310 543.5 0.16 Tujiazu Qianxinan 15 1,556 1,589 629.2 0.14 Buyizu 16 Xingren 1,528 1,564 617.9 0.14 17 Pu’an 1,389 1,528 561.7 0.16 18 Qinglong 1,444 1,462 583.9 0.15 19 Zhenfeng 1,528 1,549 617.9 0.14 20 Wangmo 1,556 1,520 629.2 0.14 21 Anlong 1,528 1,545 617.9 0.14 22 Bijie City 1,472 1,423 595.2 0.15 23 Dafang 1,400 1,335 566.1 0.15 24 Qianxi 1,389 1,348 561.7 0.16 25 Nayong 1,383 1,423 559.3 0.16 26 Hezhang 1,400 1,548 566.1 0.15 Ziyun 27 1,400 1,455 566.1 0.15 Miaozu 28 Kaili city 1,306 1,289 528.1 0.17 29 Sanhui 1,300 1,255 525.7 0.17 30 Jianhe 1,311 1,236 530.1 0.16 31 Taijiang 1,344 1,300 543.5 0.16 32 Liping 1,306 1,317 528.1 0.17 33 Rongjiang 1,350 1,312 545.9 0.16

109 34 Congjiang 1,350 1,440 545.9 0.16 35 Duyun 1,306 1,298 528.1 0.17 36 Libo 1,311 1,311 530.1 0.16 37 Fuquan 1,311 1,253 530.1 0.16 38 Dushan 1,344 1,323 543.5 0.16 39 Pingtang 1,350 1,363 545.9 0.16 40 Luodian 1,400 1,398 566.1 0.15 41 Changshun 1,398 1,227 565.3 0.15 42 Huishui 1,389 1,325 561.7 0.16 528 – $0.13 – Overall 647kWh 0.17/kWh

The levelized cost analysis RREAD suggests that the 520W home solar system can meet the energy demand for rural households in those identified 42 potential counties in Guizhou at a reasonable cost. In fact, solar home systems are less expensive than gen-sets, which have long down-times and high maintenance requirements, parts failures and fuel shortfalls. Compared to grid electricity prices in Guizhou at 0.4556Yuan/kWh ($0.076/kWh) to 0.7556 CNY/kWh ($0.11/kWh), solar electricity is still not very cost competitive (Guizhou Government, 2016). However, considering grid extension is costly and not available in the near term for those rural households in Guizhou who still do not have electricity access or adequate electrical services, solar system offers them an alternative way for meeting their electricity needs. In addition, in China in 2013, the National Reform and Reform Commission (NDRC) announced a 20-year feed-in tariff (FIT) of 0.42 CNY/kWh ($0.06/kWh) on top of the local coal-fired electricity price for distributed solar PV projects in China (NDRC, 2013). Once the household is qualified for this subsidy, it will be available for 20 years. In this sense, if solar home system is adopted in those 42 counties in Guizhou, households in these counties will be able to receive an additional annual

110 income from 222 CNY ($33) to 272 CNY ($40). Which means, the households could spend the earning from solar electricity on other activities to improve their standards of living. Today many provinces in China such as Jiangsu, Zhejiang and Shandong have provided additional provincial level subsidy on top of national solar FIT for distributed solar home systems installed in their areas. Although there is no such subsidy exists in Guizhou now, once Guizhou government decides adopting similar policies in the province, solar technology will be more competitive in more counties in Guizhou.

5.4.4 Comparison with Competing Diesel Engine Generator Systems An engine generator is a device that can covert mechanical energy obtained from an external source into electrical energy as the output (Byrne et al, 2001). It is a combination of an electric generator and an electric engine, and it is also known as an engine-generator set or a gen-set. In remote areas where grid connection is unavailable, a gen-set is served as a competitive option to stand-alone renewable systems to provide electrical services to rural households in these areas. This is also the usual case in rural Guizhou. When the electricity is not available or electrical services are not stable, diesel gen-sets are always used as a back-up plan for providing electricity. Rather than using a renewable resource to spin the generator device, a gen- set often operates on a variety of fuels such as diesel, gasoline, propane, or natural gas. Small-scale engines usually operate on gasoline or diesel, while larger ones run on liquid propane or natural gas (Byrne et al, 2001). Unlike the renewable systems that are powered by intermittent energy sources, a gen-set can run continuously as long as sufficient fuel is provided.

111 5.4.4.1 Sizing of Diesel Engine Generators For rural households in Guizhou that don’t have the access to electricity or reliable electrical services, the most commonly used gen-set is a small-scale diesel generator. Although diesel engine generator has advantages such as providing long- hour power to continuous duty cycle equipment such as refrigerator on an all day basis, it has constraints of high fuel costs and high maintenance requirements that make it impossible to provide extended hours of energy output in rural areas. Hence, it is essential to equip a diesel generator with necessary BOS components (such as charge controller, an inverter and a battery bank) so that power needed for continuous duty cycle appliances could be charged from the battery storage. For other appliances such as television or lamps that are only used for a couple of hours per day, they could be directly hooked into the gen-set without using the battery bank. Sizing the BOS components of a diesel generator is similar to the procedures of sizing a solar home system. From the demand-side perspective, the BOS size is determined by the daily load requirement by the continuous duty cycle appliance and several other factors (other appliances are hooked up directly to the system without being connected to the battery). In a typical rural household in Guizhou, the most commonly used continuous duty cycle appliance is a 75W refrigerator (Guizhou Bureau of Statistics, 2016). And the refrigerator usually runs for 12 hours a day that results in a daily load requirement of 0.9 kWh per day (75W*12hours). It is important to note that the customers’ load requirement must take account the power losses. The power losses could come from both the battery bank when it is being charged and from the inverter when the DC power is converted to the AC. Similar to the solar home system, in this study, the diesel generator’s battery efficiency is assumed at 75% and 90% efficiency is assumed for the inverter. This is

112 because the most commonly used battery and inverter used in China now have an average efficiency at 75% and 90% respectively (Solar of Week, 2017). A battery bank will be severely damaged if it is over-discharged. To protect the battery from being overused, the battery bank should be sized properly so that only a portion of it will be charged/discharged each time. This is determined by the depth of discharge (DOD). This is the percentage of the battery capacity that you can withdraw from the battery. The battery DOD of this study is set at 40%, which means a battery is only be charged of its 40% total capacity each day (Growatt, 2017). In addition to DOD, days of autonomy should also be paid attention to when sizing the battery. This is important because when the engine fuel is not available, a battery bank should have the ability to ensure an uninterrupted flow of energy to the loads. The battery reserve margin is set at 2 days for this study (Civic Solar, 2016). This means that the battery bank should be capable of delivering t least 2 days of energy supply before it is being charged again. The following calculations are performed to obtain the size of the diesel engine generator’s battery bank. Based on the daily load requirement and several other factors, a 12V battery bank requires a total of storage of 555.56Ah (12V). Considering a single battery size is of 200Ah, it requires 3 batteries to meet the household’s energy demand. Step 1: Calculating the daily delivery value requirement for the battery: 0.9 kWh/day (daily energy load of continuous duty cycle appliance) ÷ 75% (battery efficiency) ÷ 90% (inverter efficiency) ÷ 12V (battery voltage) = 111.11Ah/day Step 2: Calculating the battery’s daily storage capacity with a 40% DOD: 111.11Ah/day ÷ 40% (DOD) = 277.77 Ah/day

113 Step 3: Calculating the battery total capacity requirement with a 2-day reserve margin: 277.77 Ah/day * 2 days (reserve margin) = 555.56Ah Step 4: Calculating the numbers of batteries needed: 555.56Ah ÷ 200Ah/unit =~ 3 Compared to the sizing of battery bank, sizing charge controller and DC/AC inverter of diesel engine generator is comparatively simpler. The size of the charge controller is equal or larger to the rated power of the engine generator. For a typical rural household in Guizhou, a 600W diesel generator is usually used to meet their daily energy requirement. Then a charge controller of 600W is needed. In terms of inverter, it is set equal to the total rated power of all continuous duty cycle appliances since only these appliances are connected to the battery. The only continuous duty appliance used in the rural Guizhou households is a 75W refrigerator, then a 100W inverter is needed in this case. The details of the diesel engine generator is shown in the table below:

Table 5.8 Sizing of Diesel Engine Generators.

Province Guizhou Appliance Type (AC or DC) AC Total Appliance Load 507 W Daily maximum consumption 1.8kWh Diesel Genset Rated power 600W Manufacturer Guangdong Zunyuan System lifetime 15 years BOS Battery Voltage 12V Battery efficiency 75% Required battery capacity 555.56Ah (6.67kWh) Numbers of battery required 3

114 Depth of discharge 40% Reserve margin 2 days Battery lifetime 4 years Charge controller size 600W Charge controller lifetime 10 years Inverter size 100W Inverter efficiency 90% Inverter lifetime 10 years

Table 5.9 Comparison of Solar Home System and Diesel Generator in Terms of Sizes.

Solar home system Diesel engine generator Required size Number of units Required Number of units (total) needed size (total) needed

System 520W 2 600W 1 Battery 1,111 Ah 6 555.6 Ah 3 Inverter 600W 1 100W 1 Controller 600W 1 600W 1

5.4.4.2 Energy Analysis of Diesel Engine Generators The energy performance of diesel engine generator is evaluated by its daily, monthly and annual energy output. If without BOS components, the calculation is quite simple because there are no power losses occurred in the battery bank and inverter. However, if BOS components are integrated because continuous duty cycle appliances are utilized at home, then energy losses from battery bank and inverter should be considered. Therefore, the total energy output is reduced. In this study, a 600W diesel generator which runs 4 hours a day can only generate 1.96 kWh of

115 electricity daily (or 715.4 kWh annually), based on the battery and inverter efficiencies at 75% and 90% respectively, supposing a refrigerator in rural Guizhou household needs 0.9 kWh a day to keep continuous running. The calculation steps are shown below: Step 1: Calculating the daily energy output without considering power losses from energy storage and conversion: 600W * 4hours/day = 2.4 kWh/day Step 2: Calculating the daily power losses from energy storage and conversion with a 75% battery efficiency and 90% inverter efficiency: 0.9 kWh/day/0.75/0.9 – 0.75 kWh/day = 0.58 kWh/day Step 3: Calculating the daily net energy output from diesel engine generator: 2.4 kWh/day – 0.44 kWh/day = 1.82 kWh/day Unlike solar home system that has great variation of energy output over the course of a year, diesel generator’s energy output is quite stable. For example in Guizhou, during the summer time when daytime is longer and sun is stronger, the daily energy output of a solar home system exceeds the daily energy requirement of a typical rural household in the province. While during the winter when daytime is shorter, solar home system cannot satisfy the daily energy needs of the rural households thus energy shortfall occurs. By contrast, as long as diesel supply is available, a diesel engine generator can be operated continuously to provide AC power directly. Its energy output doesn’t fluctuate throughout a day or a year. In this study, a daily 1.82 kWh of electricity can be generated from a proper diesel generator in rural Guizhou, that is sufficient to meet the daily energy requirement of a rural household in Guizhou.

116 5.4.4.3 Economic Analysis of Diesel Engine Generators The economic analysis of diesel generator helps comprising the cost- effectiveness of diesel generator and solar home system. To evaluate the economic performance of diesel generator, several cost factors need to be determined. These factors include the system costs, BOS costs, and annual operating and maintenance (O&M) costs. The system costs include the cost of the diesel engine, the cost of transportation and the cost of setting up the system at home. Since the system might be still valuable after the evaluation period, a straight-line depreciation method is used to determine the scrap/residual value of the generator. The BOS costs include the sale prices of battery, inverter and controller. Because the battery, inverter and controller can’t last forever, their lifetimes should be considered as well as their replacement costs. The O&M costs include the running the system, maintenance and repair costs of the system. Usually diesel engine generator requires regular maintenance every year and major maintenance every several years. Different than the solar home system that has no fuel costs, fuel consumption is the major portion of the operation costs of a diesel generator and is also the major concern of the system. Therefore, fuels costs as well as fuel transportation costs should be taken into account when evaluating the economic performance of diesel engine generator. In terms of the system cost, the average price of a 600W diesel gen-set is of 1,650 CNY ($246) in China, including shipping and installation. The brand of the system is Zunyuan and it is manufactured in Guangdong Province (Taobao, 2017). For simplification, straight-line depreciation is used to calculate the system’s depreciation expenses. The residual value is what the system is worth at the end of its lifetime period. For this study, a residual value of 10% of its costs is assumed.

117 In terms of BOS system, the most commonly used lead-acid batteries for diesel gen-set in China costs about 150CNY ($22.06) per unit (Taobao, 2017). Because the 600W system needs 3 units of battery, then the total battery cost will be 150CNY/unit * 3 unit= 450CNY ($66.2). Typically, the battery has a lifetime of 4 years. A typical 600W charge controller and 100W inverter cost about 200CNY ($29.4) and 400CNY ($58.8) in China respectively (Taobao, 2017). Both charge controller and inverter have a lifetime of 10 years, which means every 10 years they need a replacement.

Table 5.10 Cost Comparison between Solar Home Systems and Diesel Gen-set in terms of System Cost and BOS Components Cost.

Solar Home System Diesel Engine Generator Rated power 520W 600W System cost 2,080CNY ($306) 1,650CNY ($246) Battery cost 900CNY ($132) 450CNY ($66) Charge controller 200CNY ($29.4) 200CNY ($29.4) Inverter 630CNY ($92.6) 400CNY ($58.8) Total 3,810CNY ($560) 2,700CNY ($397)

The above table shows the cost comparison of system and BOS components between solar home systems and diesel gen-sets that are used in rural Guizhou. Apparently, solar home systems are characterized by a higher system and BOS components costs (or initial costs as a whole). Diesel gen-sets, on the other hand, their system costs are only 70% of solar home systems costs. However, unlike solar home systems that requires low operation and maintenance costs, diesel gen-sets are characterized by a very high maintenance and operation costs. For example, the average maintenance cost for diesel gene-set in rural China costs about 150 CNY per year ($22.4), which is 4 times of the maintenance cost of a solar home system (Dong, 2014). For a solar home system, the only maintenance needed is to clean up the solar

118 panels every month. By contrast, the maintenance for diesel engine generators require both minor and major services at regular time intervals. A minor service includes oil changing, and air, fuel and oil filters. While major service includes decarburization, adjustments, and requires professional personnel to be on site or at a close-by service center (SELF, 2008). Fuel cost is the major concern for the operation of a diesel generator. There are two types of fuels used in a diesel gen-set: diesel and lube oil. Diesel costs range between 6.14CNY ($0.91) per liter to 7.07CNY ($1.04) per liter in Guizhou, depending on at which store that the customers buys their diesel (Oil Price Check, 2017). The diesel generator fuel efficiency is expressed as fuel consumption per kWh generated from the system. Usually the high quality engine has higher efficiency, thus consumes less diesel than the low efficiency engine when generating same amount of electricity. According to the NREL, for a diesel engine smaller than 1kW, it fuel efficiency ranges from 0.3L/kWh to 0.5L/kWh (SELF, 2008). Also, diesel costs need to take into account the transportation costs since rural people need to take the fuel from the stores to their homes. Today, the transportation cost for diesel is at 1CNY ($0.15) per liter (National Bureau of Statistics, 2015).

Table 5.11 Factors Affecting Diesel Fuel Costs.

Fuel unit price $0.91/L - $1.04/L Fuel efficiency 0.3L/kWh - 0.5L/kWh (consumption) of diesel generator Fuel transportation cost $0.15/L Source: Oil Price Check, 2017; SELF, 2008; National Bureau of Statistics, 2015.

119 The following steps show the calculation of annual diesel fuel cost of diesel gen-set used in rural Guizhou, given its annual electricity generation of 715kWh calculated in the above: Step 1: Calculating the annual diesel fuel needed: (1) Low fuel efficiency generator: 715kWh * 0.5L/kWh = 358L (2) High fuel efficiency generator: 715kWh * 0.3L/kWh = 215L Step 2: Calculating the annual cost of diesel fuel: (1) Worst case – high fuel unit price and low generator efficiency: 358L * $1.04L = $372 (2) Best case – low fuel unit price and high generator efficiency: 215L * $0.91/L = $196 Step 3: Calculating the transportation cost of diesel: (1) Low generator efficiency: 358L * $0.15/L = $54 (2) High generator efficiency: 215L * $0.15/L = $32 Step 4: Calculating the total costs for diesel (fuel + transportation): (1) Worst case: $372+$54 = $426 (2) Best case: $196 + $32 = $228 Lube oil used in diesel engines is for lubrication for the engine’s internal parts. Its consumption is based on the engine design and the operating conditions. Compare to the cost calculation of diesel fuel, cost analysis for lube oil is quite simple. The factors influence the lube cost are lube unit cost, lube consumption and lube transportation cost. Unlike diesel consumption which is depend on energy output, lube consumption is only depend on how hours that the gen-set works each day (Pan,

120 2013). In addition, the lube oil unit price is much higher, six or seven times of price of diesel (Taobao, 2017).

Table 5.12 Factors Affecting Lube Oil Costs.

Lube oil unit price 50CNY/L ($7.35/L) Lube oil consumption 0.004L/hour Lube transportation cost 1CNY/L ($0.15/L) Source: Pan, 2013; National Bureau of Statistics, 2015.

The following steps show the calculation of annual lube oil cost of a diesel generator used in rural Guizhou, given the system works 4 hours per day, or 1,460 hours a year: Step 1: Calculating the annual consumption of lube oil: 0.004L/hour * 4hours/day * 365 day = 5.84L/year Step 2: Calculating the annual cost of lube oil: 5.85L/year * $7.35/L = $43 Step 3: Calculating the annual transportation cost of lube oil: $0.15/L * 5.85L/year = $0.9/year Step 4: Calculating the total annual cost of lube oil: $43 + $0.9 = $43.9 The below table is a cost comparison between solar home systems and diesel engine generators in terms of their maintenance and operation costs. Although solar home systems cost 30% higher than diesel gen-sets in terms of system costs and BOS costs, their maintenance and operation costs are significantly lower than diesel gen- sets. Solar systems need very limited maintenance, at around $6 per year (Yingli Solar, 2017). And it doesn’t consume any fuels to generate electricity. By comparison, fuel cost is the major concern for diesel engine generators. The total maintenance and operation cost of a 600W diesel gen-set in rural Guizhou costs from $295 to $492 per

121 year, of which fuel costs (both diesel fuel and lube oil) account for 80% of the costs. And the next section will compare the cost-effective of diesel gen-set and solar home system in terms of their levelized energy costs.

Table 5.13 Cost Comparison between Solar Home Systems and Diesel Gen-set in terms of O&M.

Diesel Engine Generator Solar Home System Annual maintenance $22.4 $5.9 Annual total cost of diesel fuel $228 - $426 None Annual total cost of lube oil $43.9 None Total $294.3 - $492.3 $5.9

5.4.4.4 Comparison of Cost-effectiveness between Solar Home Systems and Diesel Engine Generators RREAD is used to evaluate the cost-effectiveness of diesel generator given its energy output and the economic parameters mentioned above. For a better comparison with solar home system, the evaluation time period of diesel gen-set is also set as 10 years, and the discount rate is set at 2.9%. RREAD first discounts each of the costs of diesel generator (including system cost, BOS cost, maintenance and operation cost) to its net present value over the evaluation period. Once the yearly discounted future costs are determined, RREAD sums up all values to arrive at a total NPV. The total net present value costs of diesel generator then are standardized over its evaluation years to arrive at the levelized annual NPV costs. And finanlly, the levelized annual NPV cost is divided by the annual electricity output to obtain the levelized cost of energy ($/kWh). The below table depicts the cost-effective comparison between solar home systems and diesel engine generators. Although the initial capital cost of solar home

122 system is 30% higher than the diesel gen-set, its requires a minimum annual operation and maintenance cost of 1.2% to 2.2% of the annual O&M costs of diesel gen-sets. The NPV costs of both solar home system and diesel gen-set are calculated over a 10- year period taking into account initial cost, operating cost, maintenance cost and replacement cost. As a result, the NPV cost of solar home systems is only 14% to 22% of the costs of diesel gen-set during the evaluation period. High maintenance and operation costs have been a major concern for the diesel gen-sets. Depending on the diesel prices and diesel gen-set efficiency, the levelized energy cost (LCOEs) of diesel gen-sets range from $0.58/kWh to $0.92/kWh, which is 4 to 7 times of the costs of solar home systems. If national subsidy to distributed solar projects is accounted, energy cost of solar home system will be more competitive. In this sense, solar home systems have had clear economic advantages in the long time period. And the advantages will become more obvious if diesel fuel price is rising in future. Considering in rural Guizhou, the households who use diesel gen-sets as backup electricity supply are among the poorest people in the province, not only will them not be able to afford diesel for their gen-sets, they may not even ben able to get the fuel when they run out of fuels at home.

Table 5.14 Cost-effectiveness Comparison between Solar Home Systems and Diesel Engine Generators.

Initial Annual Annual Total NPV Levelized capital maintenance operation costs energy cost cost cost ($/kWh) Solar home $560 $5.9 None $720 $0.13/kWh - system $0.17/kWh Diesel gen- $397 $22.4 $271.9 - $3,285 - $0.58/kWh set $469.9 $5,183 – $0.92/kWh

123 1

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0 solar home system diesel engine generator

Figure 5.9 LCOE Comparison between Solar Home Systems and Diesel Engine Generators (unit: $/kWh).

In addition to cost advantage, solar home systems are also more reliable than diesel engine generators. They are simple to operate, and have fewer moving parts and require mostly unskilled personnel to keep systems running. In a worst-case scenario, if solar home systems don’t have maintenance at all, they can still run for months or years unattended. They don’t require professional operators on site or fancy maintenances, as do diesel gen-sets. By contrast, diesel engine generators require constant supply of diesel fuels and maintenances. The complex and expensive maintenances, along with difficulties of purchasing fuels and replacement parts have made diesel gen-sets unreliable. As a result, normally after 5-7 years of operation, diesel gen-sets are always left abandoned. In addition, according to the World Bank

124 and Dr. Lemaire, reliability has become a real issue that prevents diesel gen-set from meeting the demand of rural population (World Bank, 2001; Lemaire, 2007). As a conclusion to the cost-effectiveness comparison, solar home systems are more reliable and cost-effective in terms of electricity supply than diesel gen-sets. Although solar systems require higher initial costs, in effect, they are cheaper in a long time period. Solar systems require minimum operation and maintenance and most importantly require no fuels, which means when purchasing a solar system you will know clearly what your costs are going to be for the next 10 years or more. Therefore, the levelized costs of the kWh produced from solar home systems are considerably lower than from diesel gen-sets. In terms of reliability, solar PV systems are much easier and cheaper to operate than diesel engines. In contrast, the costs of maintenance and diesel of diesel gen-sets make the systems prohibitive to rural population. It is highly possible that in future the fuel price will continuously increase, this will make diesel gen-sets a more expensive means of energy supply. Thus, seeking to reach remote households with solar home systems is a real alternative solution to meet the demands of electricity for rural population in China.

5.4.5 Sensitivity Analysis of Solar Home Systems in Guizhou Province In order for this economic analysis to be dynamic and to estimate the efforts of uncertainty, a sensitive analysis is performed, taking into account that technical, financial and policy conditions might change in future. In this section, RREAD is used to perform a number of sensitivity analyses by testing input variables into the economic analysis, to examine the impacts of possible changes in the economics of solar home systems in Guizhou province.

125 Variables such as advances in technologies and the development of renewable energy markets can have significant impacts on the use of off-grid renewable energy systems. For example, solar home systems with better energy performance and lower module cost will have lower LCOEs. In addition, longer lifetimes and lower discount rates can also improve the competitiveness of solar PV systems relative to conventional fossil fuel-based systems. By examining the potential impacts from the changes of these and other variables, it helps to identify the key variables that have major influence on the costs and benefits of the system. Better knowledge of these relationships can be used to guide future development of solar energy in Guizhou. To serve this aim, four major input parameters of the RREAD model are selected for sensitivity analyses of solar home systems in Guizhou province, namely: (1) varying solar electricity output; (2) varying technology cost; (3) varying technology lifetimes; and (4) varying discount rates. Studies have noted that changes in solar electricity output can affect the results of economic analysis significantly (Xue et al., 2017; Shi et al., 2016; Wang, 2016). Since the solar home system’s electricity output is correlated with various factors including solar radiation, temperature, module efficiency, and efficiency of the BOS, it is important to evaluate system performance with weather data over a long period and allow technical parameters of the system to vary. Accordingly, the solar home system’s energy output is varied at 10% increase and decrease as shown in Table (Shao et al., 2014; Wang 2006; Wang, 2016). Furthermore, PV module cost has been considered as a key cost parameter reported in the literature during the cost stream preparation stage of the cost analysis (in section 5.4.2). It is useful to consider module cost as a sensitivity parameter during

126 the analysis as presented in the below table. This is due to the fact that the module cost is highly dependent on the type of the solar PV system and location and brand. For example, the current PV module price for decentralized solar systems varies from 3.5 CNY/W ($0.51/W) to 6 CNY/W ($0.88/W) in China (Silicon Industry of China, 2015; China Power, 2016; Chen et al., 2015). In addition, solar manufacturing prices have been rapidly declining in the past five years due to efficiencies of production, product and material innovations and economics of scale (Meza, 2016; Pearce, 2008; NREL, 2016; Puttaswamy & Ali, 2015). For this reason, it is expected the module price will further drop to 2.5 CNY/W ($0.37/W) in China in the next 3 to 5 years (China Power, 2016; Sohu, 2017; Wang, 2017). By 2030, it is expected the module cost will be further reduced to lower than 50% of today’s cost, or at 2 CNY/W (IMECAS, 2015; Meza, 2016). In this respect, module costs at 2.5 CNY/W ($0.37/W) and 2 CNY/W ($0.29/W) are compared to the estimated cost of 4 CNY/W ($0.59/W) in the simulation. A third variable of interest is the system’s lifetime. This study assumes, because Trina Solar offers and suggests currently in China, a 10-year warranty on panel lifetime for the economic analysis (Trina Solar, 2016). However, many modules currently come with a longer period of warranty, which is often from 15 to 20 years (Solar of Week, 2017; BJX, 2016; Solar of Week, 2016). In addition, research has shown that the lifetime of solar PV panels could be well beyond 20 years, even for older technologies and the current ones are of even longer lifetime (Skoczek et al., 2009; Laronde et al., 2011; Charki et al., 2012; Kuitche, 2014). Thus, it is decided to consider a lifetime of 15-year and 20-year for the sensitivity analysis here.

127 The choice of discount rate comes with ample uncertainties and studies have noted that discount rates can heavily influence the competitiveness of solar power compared to a market benchmark (Peters et al., 2011; Pitz-Paal, 2005; Kost & Schlegl, 2010; Kneifel et al., 2016). Since the discount rate applied in the economic analysis is the average real discount rate in China regardless of project types, it is highly important to identify the discount rates that could accurately reflect the risks to renewable technologies. For this purpose, it is recommended that a sensitivity carried out for real rates of 5% and 1%. This is because for assessment models of solar projects, a discount rate of 5% is commonly used (IPCC, 2014; Riahi et al., 2013; Ondraczek et al., 2015). The lower discount rate of 1% is included since several studies argue that for long-term problems with larger risks of irreversible events, a lower discount should be included in the economic cost analysis (Admiraal et al., 2016; Stern, 2006; Weitzman, 2006; Markandya, 1998). To determine the sensitivity of the solar home system’s LCOE to those four variables, sensitivity analyses using RREAD are carried out. The Table and Figure below show the results. It is observed that the variations in solar module cost and lifetime can significantly impact the cost of using the solar system. The results indicate that with a 1.5 CNY/W and 2 CNY/W decrease of solar module price, the LCOE of the whole system could potentially reduce by $0.02/kWh (15.4%) and $0.03/kWh (23.1%) respectively. Also if the lifetime of the solar home system could be extended from 10 years to 15 years and 20 years, the LCOE could potentially fall by $0.03/kWh (23.1%) and $0.04/kWh (30%) respectively. Therefore, technology advances are likely to influence solar economics, but their influence will be favorable for the solar users.

128 The LCOE is also sensitive to solar electricity output since its line is the steepest. As solar electricity output is increased by 10%, its LCOE will be decrease by $0.01/kWh accordingly. Therefore, the influences from better system performance will be favorable for the user. By contrast, the decrease or increase discount rate have small effects on the total LCOE. Therefore, for investors or buyers, this parameter could be regarded with modest risk during the investment decision.

0.15

0.14 Solar energy output Lifetime 0.13 Discount rate Solar module cost 0.12

0.11 Base Case Energy output = 528 LCOE ($/kWh) 0.1 kWh - 647 kWh Module cost = 4 CNY/W 0.09 Lifetime = 10-year Discount rate = 0.08 2.9% LCOE = $0.13 - 0% 50% 100% 150% 200% 250% $0.17/kWh Value Relative to the Base Case

Figure 5.10 Sensitivity Analysis of Solar Home Systems in Guizhou Province.

Table 5.15 Sensitivity Analysis of Solar Home System in Guizhou Province.

LCOE ($/kWh) LCOE ($/kWh) Variables Base case Variations Base case After variation +10% 0.12 – 0.16 Solar energy 528 – 647 0.13 – 0.17 output kWh -10% 0.14 – 0.18

129 Solar module -2 CNY/W 0.10 – 0.13 cost 4 CNY/W -1.5 CNY/W 0.13 – 0.17 0.11 – 0.14 +5 year 0.10 – 0.13 Lifetime 10-Year +10 year 0.13 – 0.17 0.09 – 0.12 +2.1% 0.14 – 0.18 Discount rate 2.9% -1.1% 0.13 – 0.17 0.12 – 0.16

5.4.6 Comparison with Previous CEEP Work Previous work has been done on economic performances of solar home systems, and the most renowned work is conducted by Center for Energy and Environmental Policy (CEEP), led by Dr. John Byrne. First of its kind, Dr. Byrne et al. examined off-grid renewable energy options for rural electrification in Western China in 2001 (Byrne et al., 2001). The comparisons between CEEP’s previous work and this dissertation are listed in Table 5.15. The case study regions in CEEP’s study include Inner Mongolia, Qinghai and Xinjiang, which have the most abundant solar resources in China compared to Guizhou province that has moderate sunshine. The solar PV systems in the pervious work are of smaller sizes ranging from 22W to 120W due to technology and cost constrains at the time. PV efficiency utilized in previous CEEP’s work was 12%. Due to technology development, PV efficiencies have been increased and majority of panels range from 14% to 16% efficiency rating nowadays in China. In this study, an efficiency of 15% is assumed, showing the better PV performances of today than more than 15 years ago. It is obviously observed that now after more than 15 years, cost of a solar home system has been substantially reduced. The unit cost of PV module is now at $0.59/W, which is about only 10% of the unit cost 15 years ago. Additionally, cost of battery, controller and inverter have also reduced significantly than 15 years ago. As a

130 result, this dissertation shows levezlied costs of electricity at $0.13- $0.17/kWh in Guizhou, which falls far below the levelized costs for Inner Mongolia ($0.70 – 0.94/kWh), Xinjiang ($0.45 – 0.68/kWh), and Qinghai ($0.52 – 0.78/kWh) in the previous CEEP study. This result is impressive because it shows even provinces like Guizhou – which have less substantial solar potential than provinces in the original CEEP work, can still consider solar home systems as competitive options to address rural energy needs.

Table 5.16 Study Comparison between CEEP Previous Work and this Dissertation.

Byrne’s et al., 2001 Zhu, 2017 Basic Information Study area(s) Inner Mongolia (2 counties) Guizhou (42 counties) Xinjiang (5 counties) Qinghai (4 counties) Solar hours per year Inner Mongolia: 2,880 – 1,250 – 1,800 hours 3,330 hours Xinjiang: 4,406 – 4,704 hours Qinghai: 4,386 – 4,476 hours Technical and Economic Parameters PV size 22W – 120W 520W PV efficiency 12% 15% System total capital cost $7.39 - $7.55/W $1.09/W ($/W) PV array unit cost ($/W) $6.3/W $0.59/W PV array as % of total cost 83% - 85% 54% System life time 15 years 15 years Battery cost $36/kWh $9.9 /kWh Battery lifetime 2 years 4 years Inverter cost ($/W) $0.15 - $0.32/W $0.15/W Inverter lifetime 10 years 10 years Controller cost ($/W) $0.08 - $0.116/W $0.05/W Controller lifetime 10 years 10 years Annual O&M cost $2.5/year $5.9/year

131 Discount rate 12% 2.9% Evaluation period 10 years 10 years Currency exchange rate 8.3 6.8 ($:CNY) Energy and Economic Performances Solar electricity output Inner Mongolia: 37 – 526 – 647 kWh/year 225kWh/year Xinjiang: 55 – 400 kWh/year Qinghai: 47 – 328 kWh/year LCOE(s) Inner Mongolia: $0.70 – Stand-alone: $0.13 – 0.94/kWh 0.17/kWh Xinjiang: $0.45 – 0.68/kWh Integrated: Qinghai: $0.52 – 0.78/kWh

5.5 Social Analysis of Solar Home Systems in Guizhou Province Solar home systems provide huge positive social impacts not only to rural households in Guizhou Province, but to all poor people in China. The social impacts of solar home systems on the livelihood of rural peoples include poverty reduction, better electrification, better entertainment and education, extension of working hours, better health conditions, security in night, etc. Today, in China, solar home systems have been regarded as a strategic approach to help poor people in term of poverty reduction. In 2015, China’s President Xi Jingping announced China would get rid of poverty by 2020, targeting the country’s 70 million people who live below the poverty line (China Daily, 2015). In March 2016, NEA released a Plan to use solar PV systems to increase the income of 2 million Chinese households in 16 provinces and 471 countries (NEA, 2016). The Plan aims to install solar home systems for the poorest villages across the county, allowing households to generated electricity for their own use and make extra income from improved economic and social activities. Some pilot projects have been implemented following the Plan. For example, as a pilot county of China’s new solar poverty

132 alleviation project, Yuexi county of Anhui province, has witnessed the an extra income of 3,000 CNY ($440) for households who have installed solar home systems on their rooftops (Murray, 2016). Although Guizhou province is not listed as the targeting province under the national Plan, the government of Guizhou has recognized the importance of solar systems for poverty alleviation. With 4.93 million people who live under the poverty line in Guizhou today, the government plans to get rid of poverty in the province by 2020 and solar PV systems have been recognized as the strategic method. The first pilot solar poverty alleviation project was implemented in Liuzhi county in 2016. The projected installed solar home systems for 13 households who live under the poverty line in Liuzhi county and showed great success (Solar Bee, 2016). Though a small size project, the households who participated have noted that they are now be able to extend their hours of reading, listening to radio and watching TV (solar Bee, 2016). In addition to energy supply, the solar home system helps the household earning additional income. The current national solar FIT policy in China offers 0.42 CNY/kWh ($0.06/kWh) for distributed solar PV projects in China (NDRC, 2013). Once the household is qualified for this subsidy, it will be available for 20 years. In this sense, if solar home system is adopted in Guizhou, households in these counties will be able to receive an additional annual income from 222 CNY ($33) to 272 CNY ($40). In future, if households have surplus solar electricity due to the improvements of energy performance of solar home systems, then the households could sell their extra electricity to the national grid at the unit price of local grid price plus 0.42CNY/kWh. This enables the households gaining greater income from adopting the system. Today in Guizhou, the government have been proposing additional solar

133 projects for Weining county Liupanshui county, Panxian county, etc (China Energy Storage, 2016). These projects are expected to implement soon in the near future to achieve greater poverty alleviation in Guizhou. In addition to poverty reduction, solar home system also provides greater social benefits in terms of safety and security. Today, streetlights powered by solar systems are becoming more and more popular in China in the past few years. Particularly for Guizhou province, where many villages are located in the remote areas and are surrounded by mountains, solar streetlights are ideal alternatives to the traditional streetlights. This solar light provides high quality, sustainable and low cost lighting solution to people in remote Guizhou where conventional electricity grid is hard to reach. It also extends people’s day after sunset and increases their level of safety on roads and streets and allows people putting more time on economic and social activities. Starting from 2009, Phillips has been implementing its “Solar LED Lighting 1,000 Villages Program” in China, aiming to provide communities in rural China with solar powered LED street lighting (UNFCCC, 2009). Guizhou province has been part of the program. Under the program, Guizhou government first installed 157 sets of Phillips solar powered street lighting systems in total 15 villages of Huaxi district, Wudang district, Kaiyang county and Xiuwen county (Phillips, 2012). And all villagers in Guizhou province that have participated in this program believed that the lights bring safety to them at night, and they think the lights are comfortable and pleasant. After the experience with Phillips solar street lighting, Guizhou government (through Department of Municipal Engineering Administration) purchased additional solar powered light sets for the community park and schools around some villages.

134 And based on the experience with Philips solar light program, Guizhou government plans to promote solar powered lighting in more villages in the near future.

5.6 Environmental Analysis of Solar Home Systems in Guizhou Province In addition to economic and social benefit, solar home systems also contribute to rural sustainable development from environmental point of view. Energy use for electricity generation is by far the largest source of CO2 emissions, which is the main gas of greenhouse gases (GHG). The increased warming from GHG has many effects, including raising ocean temperatures and sea levels, and change in global precipitation, and melting glaciers (Ibrahim, 2000; Hughes, 2000). According to scientists, carbon accounts for more than 80% of all the GHG emission contributions to global warming. Because of the rising problem of carbon dioxide associated with the global warming, the reduction of carbon dioxide becomes necessary and counties are adopting policies to promote this. Solar home system is a viable option for providing clean electricity to meet the energy needs for a household. One of the main environmental benefits of a solar home system is that it generates significantly less carbon dioxide emissions than other means of traditional energy production. In terms of life-cycle CO2 emissions from electricity generation, typical solar home system emits 29 - 35g CO2/kWh with most of its emissions from its equipment manufacturing phase (Sovacook, 2008). By contrast, emission values for the diesel engine generator are about 778 g CO2/kWh and for the coal-fired electricity are about 960 – 1,050g CO2/kWh (Sovacook, 2008). And most of their emissions are from the system operation. In this sense, rural households that implement solar home systems can reduce their consumption of diesel or grid power,

135 therefore will reduce their household’s CO2 emissions. With less CO2 emission, the adoption of solar home systems can help reduce global warming. Existing solar home system projects in China have proved that the system positive environmental benefits to China in terms of CO2 mitigation. Launched in 1999, the Renewable Energy Development Project supported by the World Bank and the Global Energy Facility (GEF) have provided electricity to more than 400,000 rural household in 9 north-western provinces and autonomous region in China through the installation of solar home systems (World Bank, 2011). The supply of solar electricity to rural populations in remote and dispersed areas have contributed to the improved indoor air quality and reduced CO2 emissions. The project is estimated resulting in direct avoided CO2 emissions of 4.3 million tons over 20 years (World Bank, 1999). And the associated avoided emissions are 39,000 tons of NOx and 126,000 tons of SO2 (World Bank, 1999). More recently, the World Bank proposes a Sunshine Schools program in Beijing, China, aiming to install rooftop solar systems in 1,000 schools and other education institutions to make their energy consumption pattern greener (World Bank, 2012). The project has the potential to avoid 89,590 tons of CO2 emissions annually and will benefit more than 650,000 students in Beijing (World Bank, 2016). A study on reduction in carbon emissions due to solar home system installation in California has shown that: with 113,533 residential homes in California that have installed solar home systems, a mean of 696,544 metric tons of CO2 emissions have been avoided due to these installed systems (Arif, 2013). According to Yingli Solar, in China, a typical solar home system of 520W in Guizhou could help offset 6.2 tons of coal, 16 tons of CO2, and 0.14 tons of SO2 over 25 years (Yingli Solar, 2016). Based

136 on the calculation from Yingli Solar, in this study, if all the potential households in Guizhou province (the households that of favorable solar resource conditions but don’t have electricity access or reliable electrical services) have installed a 520W solar home system, an estimated of around 13.5 million tons of CO2 could be saved for 25 years. With rising awareness from Guizhou government of the development of solar home system in the province, greater environmental benefits from solar home system will be seen in Guizhou.

5.7 Potential Challenges Facing Solar Home System Development in Guizhou Province The above sustainability analysis has clearly demonstrated that solar home system is a viable solution to provide electricity services for rural households in Guizhou in a sustainable manner. However, the analysis also implies that solar development in Guizhou still faces a variety of challenges.

5.7.1 Energy Challenge Though solar home system can meet majority of the electricity needs for households in the solar potential counties in Guizhou province, the energy performance analysis shows still energy shortfall days exist. During the winter times such as November, December and January when solar radiation is less than in the summer, energy gaps occur even taking into account the energy supply from the batteries. To fill the energy gap, households have to either reduce their energy consumption or rely on other fossil fuel-based system such as diesel generator. In either way, households have to sacrifice their standards of living or increase their expenditure on energy. And this will in turn weaken the competitiveness of solar home system in future. Sensitivity analysis also shows the solar home system is most

137 sensitive to its energy performance. By increasing the energy output by 10%, the energy gap will be largely filled up and the cost of using the solar home system will be reduced accordingly. This provides the opportunity that if solar technology advancement is achieved in future, greater development of solar technology will also be likely achieved in Guizhou.

5.7.2 Cost Challenge Cost issue is also a challenge facing by the solar development in Guizhou. As seen from the cost analysis, the low fuel and operating costs makes solar a favorable technology on lifecycle basis, however its higher initial capital costs can often restrict access to it as it is an unaffordable solution for poor and rural communities. The initial upfront cost for a household PV system of 520W size in Guizhou is 3,850CNY ($566), accounting for 15% of the annual disposable income of an average rural household in Guizhou. The sensitivity analyses show the cost of using the system is quite sensitive to the costs of PV module cost. Thus in future, if technology development can brings down the initial cost of solar home system, more rural households will be able to enjoy and benefit from solar technology. The LCOE of solar home system is $0.13/kWh to $0.17/kWh across Guizhou counties. Although this is about only 20% of the cost of diesel generator, compared to the sale price of gird electricity in Guizhou at 0.4556Yuan/kWh ($0.076/kWh) to 0.7556 CNY/kWh ($0.11/kWh), solar home system is not very cost competitive. Therefore, methods to further bring down the solar cost are the key for its further development. Otherwise, solar technology will be only cost-effective for rural households who are not currently connected to the grid electricity in the short run. If those households are going to be reached by the national grid in future and no further

138 actions are made to bring down the cost of solar home system, solar might lose its competitiveness.

5.7.3 Financing Challenge Different financing methods are usually utilized to help reducing the cost of renewable technologies and while at the same time to make these renewable resources affordable. Depending on the circumstances, financing can come in the forms of loans, mortgage, third party financing or the government subsidies of either installation based (a direct reduction of capital costs) or performance-based (subsidies based on energy produced). Today, the only financing method for solar home system users in China is a national performance-based subsidy for installing a solar PV system at home. This subsidy, namely the FIT, is fixed at 0.42 CNY/kWh on top of local coal-electricity price and is valid for 20 years (NDRC, 2013). In addition to this national FIT scheme, provinces and cities across China are encouraged to provide additional subsidies to complement the national FITs. So far, provinces/cities such as Beijing, Shanghai, Wuxi, Zhejiang, etc. offer extra premium on the top of the national level FIT for the solar home systems installed in their areas (TD Energy Shanghai Limited, 2016). Evidences have shown that regions with additional FITs have more solar systems installed in their areas. The availability of this FIT is very important to the competitiveness of the solar home system. With this subsidy, the households are able to receive additional income from electricity generated from the solar home system. This levels up the overall competitiveness of solar technology in Guizhou when comparing to other fossil fuel based generating systems. However, today in China, debates about lowering

139 the FIT for decentralized solar technology have existed in China for a long time. In fact, FIT for utility solar projects have been lowered for two times since 2013 (NDRC, 2016). If in future, there is a reduction of FIT for decentralized solar home system in China, and since there is no additional subsidy for solar in Guizhou, solar system might lose its competitiveness in the long term. In addition, the current financing method of FIT for decentralized solar is performance-based subsidy rather than installation-based. This means, the rural households can only get subsidies after they have installed solar home systems at home and produce solar electricity. How much the solar home system costs will not affect the payment of the subsidy. This type of performance-based subsidy may prevent some households who can’t afford for the initial costs from adopting a solar home system at home. Considering the upfront costs of solar home system, rural households may be reluctant to adopt the technology, even if the levelized cost of solar electricity without FIT is substantially lower than the other traditional fossil fuel-based electrical systems. Furthermore, solar home systems are mainly cash-sold in China today. No other financing methods available for households who would like to adopt a system at home. Thus an important precondition of renewable system users is the need of enough money for the acquisition of the systems. One problem associated with this cash-sale model is comparatively poor populations will be excluded from acquiring the systems, unless the price of solar home system declines sharply in the near future. Another problem is the buyers usually choose the system with the lowest price but of poor quality, this usually results in the needs of higher maintenance and operational costs than expected. Studies have noted that using the loan can improve the

140 affordability of rural renewable energy system buyers. Under this scheme, renewable energy buyers enter in to an agreement with the sellers that the system capital cost will be paid in installments over a period. However, this financing method has not been practiced in Guizhou. This is due to leading to poor rural households with little “collateral” or “creditworthiness” is considered as risky by most financing institutions, resulting in a very high interest rate or a short loan terms comparative to the equipment lifetime. In some cases, credit applicants get refusal because of uncertainty as to whether they will be able to pay payments on time. Without having access to loan or other forms of financing methods, the interested poorer households in Guizhou will hardly be able to acquire a solar home system.

5.7.4 Awareness Challenge The social and environmental analyses of solar home system clearly show there are substantial non-economic benefits that the system can bring to the rural households in Guizhou. These non-economic benefits include more security, increased productivity, improved environment and reduced greenhouse gas emissions. However, in reality, solar users are far more concerned with economic than non-economic benefits when deciding whether or not to invest in a solar PV system at home. This requires the renewable energy users’ full acknowledgment of both economic and non- economic benefits that renewable resources possess. The ignorance of the non- economic benefits of solar raises issues of adequate education and training which in future should be paid with attentions.

141 5.7.5 Policy Challenge Although, solar technology has been demonstrated to offer a cost-effective source of energy for rural electrification in Guizhou, its long-term sustainability has to be relied on the adequate national and provincial policies. Today, renewable energy has been integrated into China’s overall national energy development plan. Especially in recent years, decentralized renewable technologies, such as distributed solar and household biogas digester has been recognized as strategic options for energy provision in a sustainable way. During the 12th Five-Year Plan period, China has set a goal to reach solar installed capacity of 21GW by 2015, and of which 10GW should come from distributed solar (NDRC, 2012). In its latest 13th Five-Year Plan for Renewable Energy Development, China puts an emphasis on further deployment of distributed PV by increasing its goal to 60 GW by 2020 (NDRC, 2016). Furthermore, China encourages household solar systems utilization in central and eastern areas where solar resource is abundant there by building up solar town and villages. Though, decentralized solar has been paid with great attentions at national level, at provincial level, development of solar is still in its very early stage in Guizhou province. Only until last year, the province witnessed it first-ever solar home system project implemented in Liuzhi county. Unlike other provinces or cities such as Shanghai, Zhejiang that have their own solar targets or cost-reduction policies, this area remains untapped in Guizhou. In addition, the province so far doesn’t have an organization that is dedicated to advancing the renewable energy in the province. As the previous chapters show that renewable energy is expected to deliver energy services for rural households in Guizhou in a sustainable manner, however, this will only be the case with the right policy framework.

142 5.8 Conclusion of Solar Home Systems in Guizhou Province The sustainability analysis of solar home system in this chapter shows that this system provides a cost-effective source of electricity for rural households who don’t have the access to electricity or reliable electrical services. An important aspect to highlight here is that a 520W solar PV system is sufficient in providing majority of the electricity needs for rural households in 42 counties in Guizhou. One of the main benefit of solar PV is its LCOE is of $0.13/kWh – $0.17/kWh, which is 80% lower than the diesel engine generator. Additionally, the solar home system has social benefits such as it provides households extra income from 222 CNY ($33) to 272 CNY ($40) per year which helps in poverty alleviation. Furthermore, using solar homes system for electricity generation can offset 328,787 tons of CO2 a year in Guizhou if all the solar potential households calculated in this study installs a 520W solar PV system at home. Though the solar home system is attractive in terms of economic, social and environmental benefits, there may be constrains such as energy shortfall may occur when during the winter time, high capital cost, lack of financing options, lack of public awareness of non-economic benefits of solar, and uncertainty of political environment. In the final chapter, policy options for stimulating development of solar home system in Guizhou province will be discussed.

143 Chapter 6

CASE STUDY OF HOUSEHOLD BIOGAS DIGESTER SYSTEMS IN GUIZHOU PROVINCE

6.1 Overview of Household Biogas Digesters A biogas digester, also known as anaerobic digester, is a system that can convert animal and plant wastes into useful fuel for lighting, cooking, and heating at home. A typical household biogas digester system usually involves an anaerobic digester (usually underground) in which plant and animal wastes are dumped and decomposed, and a tank that holds gases emitted by the slurry. The digestion process occurs with the aid of bacteria. When bacteria in the digester breaks down the wastes, biogases such as methane, hydrogen, and nitrogen are produced. The gases are then used to create an energy source for cooking and lighting at home. Unlike solar home systems, there is no particular type of biogas digesters for household use. Design of a biogas digester is varied based on the geographical location, availability of substrate, and climate conditions (Rajendran, 2012). Of all the biogas digester developed so far, the fixed dome model developed by China and the floating drum model developed by India are among the most popular ones. Less common but with gaining interests are plug flow digesters due to its easy operation. The fixed dome digesters, also known as Chinese digesters, are the most common digester model developed and used mainly in China. The typical structure of a fixed-dome system consists of a digester (usually underground) with a fixed, non- movable gasholder, which sits on top of the digester (Energypedia, 2016). The digester

144 is usually constructed under the ground to save space and to protect it from damage. In addition, when the plant is buried underground, day/night temperature won’t fluctuate a lot which will in turn positively influence its gas production process. The costs of fixed-dome biogas digester are relatively low. Its design is simple as there are no moving parts exist. Hence it has a long lifetime of 20 years or more as the system doesn’t have any rusting steel parts. The sizes of these systems are varied between countries: 4-20 m3 in Nepal, 6-10 m3 in China, 1-150 m3 in India and around 6m3 for a family of 9 in Nigeria (Gautam et al., 2009; Qiu et al., 1990; Tomar, 1994; Adeoti et al., 2000). There are many types of fixed dome digesters around the world, however, the most popular one by far is called Chinese deign, which is typically built of gas- sealed brick and cement. However the construction of the plant is not easy – it requires experienced biogas technicians otherwise the plants may not be gas-tight.

Figure 6.1 Typical Fixed-dome Biogas Digesters in China. Source: FAO, 2017.

145 The figure below is floating drum digesters. They are also known as Indian drum biogas digesters as they are most widely used in India. Unlike the fixed dome digesters, this type of system includes a movable floating gasholder, or it is called drum. The gas holder floats either directly on the fermentation slurry or in a water jacket of its own (Energypedia, 2017). The gas is collected in the gasholder. When gas is produced, the holder floats up. In reverse, if gas is consumed, the holder sinks. In the past, this type of biogas digester is most used in India. The floating drum digesters are used most frequently by small to medium sized households, ranging from 5-15 m3 or by larger institutions, from 20 to 100 m3 (Wrener, Stohr, & Hees, 1989). Compared to the fixed-dome biogas digester, the cost this type of plant is relatively higher. Also this system requires more maintenance as it contains movable parts and rusting steel parts. Thus its lifetime is shorter, up to 15 years and in some tropical coastal regions about only 5 years (Energypedia, 2017).

146

Figure 6.2 Typical Floating Drum Biogas Digesters in India. Source: FAO, 2017.

Plug flow digesters are getting more attention in recent year due to their higher gas production and lower costs. Unlike the fixed dome or floating drum models, plug flow digesters are built above the ground hence they are easy to move. Their structure consists of a long tank with the inlet and outlet of the digester at opposite ends. Typically, the tank is five times longer than it is wide and is made of concrete, steel or fiberglass (Ramatsal et al., 2014). The main advantage of this plant is they are simple to install and cheap to operate. Other advantages of this plant include easy handling and adaption to extreme conditions at high altitudes with low temperatures. In addition, since plug flow digesters are constructed above the ground, it is easy to transport that helps to reduce the costs. The sizes of these digesters are varied from 2.4

147 to 7.5 m3 (Werner, 1989). Despite the advantages, however, this plan is limited to the applications with low amounts of sand, dirt, or grit, because these substances tend to stratify inside the digester, requiring substantial efforts to clean out (Ramatsa, et al., 2014).

Figure 6.3 Typical Plug Flow Biogas Digesters. Source: FAO, 2017.

6.2 Optimum Conditions for Biogas Production in Guizhou Province The conditions that influence the biogas production and therefore influence the development of household biogas digesters in rural Guizhou include (1) temperature (ground temperature) and (2) carbon/nitrogen (C/N) ratio. Both temperature and C/N ratio are two important factors that determine the speed and efficiency of fermentation process in the biogas digester.

6.2.1 Temperature Temperature is the most important factor that affects the amount and the speed of the biogas production in household biogas digesters. Biogas production is the most rapid when the temperature reaches above 20 C (Ma, 2003). When temperature drops, the gas production reduces and the fermentation process stops at 10 C or less (Ma,

148 1993). Similarly, bacteria will be killed when the temperature reaches 50 C and gas production declines significantly especially after 60 C (Doggaer, 2015). In general, the range of an ideal fermentation temperature for a household biogas plant is from 8 C to 25 C (Chen et al., 2010; Chen et al., 2013). Usually household biogas digesters in rural China are built underground at a depth of 2 meters. The temperature at the depth of 2m of a biogas plant is approximately the same as the average ground temperature at a depth of 1.6m (Hou, Li, & Zhang, 1993). The below table and map show the distribution of average ground temperature at a depth of 1.6m in China (Chen et al., 2010; Chen et al., 2013). Based on the temperature data, China could be divided into 6 regions. The data indicates that region IV is the most suitable region for developing household biogas digester systems. In this region, biogas digesters can produce biogas all year round, and the time available for the digester to produce biogas most rapidly and efficiently is 8 months (when temperature > 20 C). Region IV and region V are also suitable areas for biogas digesters to produce biogas, where biogas could be produced all year, but the time available for the digester to produce biogas efficiently and effectively are 4 and 5 months respectively. In region I, there are 9 months that the average ground temperature at a depth of 1.6m above 10 C, however efficient and rapid biogas production is limited to 3 month. Cool ground temperature in region II and VI limit biogas production in these regions. In addition, ground temperatures never exceed 20 C in these two regions, thus it is not appropriate to develop biogas digesters in regions II and VI.

149 Table 6.1 Distribution of Average Ground Temperature at a Depth of 1.6 m in China.

Zones Months Months>=15C Months>=20C Months>=25C >=10C I 9 6 3 0 II 4 1 0 0 III 12 8 4 0 IV 12 10 8 4 V (Guizhou) 12 9 5 0 VI 7 3 0 0 Source: Chen et al., 2010; Chen et al., 2013.

Figure 6.4 Distribution of Average Ground Temperature at a Depth of 1.6 m in China. Source: Chen et al., 2010; Chen et al., 2013.

Guizhou province is located in region V, where biogas could be produced all year round and the time available for the digester to produce biogas most efficiently

150 and effectively is 5 months in a year. This means Guizhou is very suitable for developing household biogas digesters. The below table lists the ground temperature for each of the 88 counties in Guizhou. On average, the ground temperature at the depth of 1.6m in the province is around 18.6 C. Except for a few counties such as Weining, Dafang, Shuicheng, Xishui and Kauyang that have an average ground temperature below 17C, all other counties are regarded as thermic regime with the highest temperature occur in county of Wangmo, Jingping, Jianhe, Liping, Congjiang, and Libo (Lu et al., 2016).

Table 6.2 Average Ground Temperature at the Depth of 1.6 m for Each of the 88 Counties in Guizhou Province.

Ground Temperature at 1.6 m (C) Guiyang 18.6 Kaiyang xian 17.6 Xifeng xian 18.4 xiuwen xian 18 qingzhen xian 18.2 liupanshui shi 17.8 zhongshan qu 17.8 pan xian 18.1 liuzhi tequ 18.2 shuicheng xian 16.9 zuiyishi 18.4 zunyi xian 18.2 tongzi xian 17.8 suiyang xian 18.1 zheng an xian 18.4 daozhengelao 17.9 wuchuangelao 18.2 fenggang xian 18.5 meitan xian 18.5 yuqing xian 19.4 renhuai xian 18.2

151 chishui xian 19.9 xishui xian 17.1 tongren shi 19.7 jiangkou xian 19.5 yupingdongzu 19.8 shiqian xian 19.4 sinan xian 18.8 yinjiang tujiazu 19.1 dejiang xian 19.4 yanhetujiazu 19.7 songtao miaozu 19.1 wanshan tequ 18.4 xingyishi 19.2 xingren xian 18.7 puan xian 17.8 qinglong xian 18 zhenfeng xian 19.6 wangmo xian 20.8 ceheng xian 21 anlong xian 18.9 bijieshi 15.9 dafang xian 14.8 qianxi xian 16.7 jinsha xian 17.9 zhijin xian 16.8 nayong xian 16.4 weining 13.4 hezhang xian 17.2 anshun shi 18.1 pingba xian 18.3 puding xian 18.4 guanlinbuyizu 19.1 zhenningbuyizu 18.5 ziyunmiaozu 19 kaili shi 17.8 huangping xian 19 shibing xian 19.6 sansui xian 19.5 zhenyuan xian 19.8 cengong xian 19.8 tianzhu xian 20

152 jinping xian 20.3 jianhe xian 20.1 taijiang xian 19.6 liping xian 20.1 rongjiang xian 21 congjiang xian 21.3 leishan xian 17.6 majiang xian 18.9 danzhai xian 19.2 duyun shi 19.6 libo xian 21 guiding xian 18.7 fuquan xian 18.9 wengan xian 18.2 dushan xian 19.4 pingtang xian 19.9 luodian xian 21 changshun xian 19 longli xian 17 huishui xian 19.2 sandushuizu 20.5 Average 18.6 Range 13.4 – 21.3 Source: Lu et al., 2016.

6.2.2 Carbon/Nitrogen (C/N) Ratio Feedstock is used in biogas digesters to produce biogas. The most commonly used feedstock for many digesters today include animal manures (such as pig, cattle, sheep and chicken) and crop residues (such as rice, corn and wheat). Feedstock materials contain various chemical elements such as carbon (C), nitrogen (N), phosphor (P) and sulfur (S). And the C/N ratio is the most important parameter to evaluate the speed and efficiency of fermentation process in the biogas digester. In generally, the anaerobic digestion requires a balance between C and N. Too high or too low the ratio will be an obstacle to the successful biogas production from the

153 digester. Many studies have indicated that the optimal C/N ratio for biogas fermentation ranges from 20:1 to 30:1 (EPA, 2012; Tchobanoglous, 1992; Krause, 1993). Too high or too low the ratio will prevent the digester to function efficiently to utilize the nutrition in the feedstock and maximize the biogas yields. C/N ratios from different feedstock materials are indicated below. It shows that crop residues have high C/N ratios, while animal manures tend to have lower ratios. In this sense, when a single type of feedstock is digested, it is hard to achieve the most efficient production rate of biogas due to deficiency or surplus of carbon. Thus it is best to co-digest of two or more types of feedstock, which offers opportunity for adjustment of the C/N ratio to an optimum range (Wang et al., 2014; Monnet, 2003). Also co-digestion can increase the volume of biogas produced from the plant. Similarly in this study, both animal manures and crop residues are used as feedstock for biogas digester in Guizhou province.

Table 6.3 C/N Ratios from Different Feedstock Materials.

Type of material Carbon/nitrogen ratio Animal manures Pig manure 6:1 to 8:1 Cattle manure 9:1 Sheep manure 13:1 to 20:1 Chicken manure 6:1 to 7:1 Crop residues Rice 48:1 Corn 57:1 Wheat 80:1 Source: EPA, 2012; NRSC-USDA, 2016.

154 6.3 Feedstock for Biogas Production in Guizhou Province Materials used in the biogas digester are called feedstock. Quantity of feedstock can decide if gas produced from the digestion process can meet the household’s daily energy requirement. Common feedstock includes food wastes, crop residues, animal manures and fats, oils and greases (EPA, 2012). While in this study, two types of feedstock are analyzed which are: crop residues and animal manures.

6.3.1 Crop Residues Crop residues include all agricultural wastes coming from cereals and non- cereals such as stem, straw, stalk, leaves, husk, shell, etc. After crops are harvested, a portion of crop residue could be collected for use in biogas digesters. Main crops in China include cereal crops such as rice, wheat and corn and non-cereal crops such as beans, potatoes, cotton, oil-seed, sugar and tobacco crops. Only three types of cereal crops are analyzed in this study – rice, wheat and corn, as they are the most popular crops planted in Guizhou province and they are also the most commonly used crop materials in the anaerobic digestion. The production of crop residues for rice, corn and wheat are estimated at household level in the 88 counties in Guizhou province. To estimate the crop residues, the residue-to-crop ratio is applied (Koopmans & Koppejan, 1997). For a specific crop type, its annual residue production is calculated as using its annual yields multiply by its residue-to-crop ratio (Gu, Zhang & Wang, 2011). This method is widely used to estimate crop residues for biogas production and is based on the relationship between crop yields and the residues left after harvesting the crops (Rosillo-Calle, 2007). Although this method has limitations such as it doesn’t take into account the residues that remain on the fields, it is suitable to estimate the current county-specific and crop-

155 specific residues production. The general equation for estimating the county-level crop residue is as follow:

Pyra = Cyra * RPRyra (1)

Where Pyra is the amount of residue production for crop a in county r for the year y, kg; Cyra is the amount of crop production for crop a in county r for the year y, kg; and RPRyra is the residue-to-crop ratio for crop a in county r for the year y. The theoretical available crop types and the residue-to-crop ratios for those crops in China and Guizhou province are shown in the below table (Xie, Han & Wang, 2011). Accordingly, the ratios used in this study are 1 for rice, 1.17 for wheat and 0.92 for wheat.

Table 6.4 Average Residue-to-Crop Ratios for Major Crop Types in China and in Guizhou Province.

Cereal crops Non-cereal crops Rice Wheat Corn Cotton Potatoes Beans Oil- Sugar Tobacco seed National 1 1.17 1.04 2.91 0.71 1.5 2.87 0.43 0.71 Guizhou 0.92 0.56 3.17 0.92 Source: Xie, Han & Wang, 2011.

The data for rice, wheat and corn yields for the 88 counties in Guizhou province are obtained from each county’s 2016 Annual Economy and Social Status

Report. Once the county’s 2016 rice, wheat and corn yields are obtained, they are multiplied by the residue-to-crop ratios (rice: 1, wheat: 1.17, and corn: 0.92) to arrive at the residue production in the county in 2016. Because this study is focused on the household level, the county’s residue productions are further divided by the county’s household numbers to arrive at the crop residues per household. The general equation for estimating the household-level crop residue is as follow:

156 HPyra = Pyra / Hyr (2)

Where HPyra is the amount of residue production per household for crop a in county r for the year y, kg; Pyra is the amount of residue production for crop a in county r for the year y, kg; and Hyra is the number of households in county r for the year y. Similarly, the county’s population and number of households are obtained from its 2016 Annual Economy and Social Status report. The below table calculates the amount of residue production per household for rice, wheat and corn in Guizhou’s 88 counties in the year 2016. Overall, rice has the largest amount of residue production in the province since the main agricultural crop in Guizhou is rice. For all the 88 counties in Guizhou, households have pretty good residue production in 2016. Individually, big agricultural counties such as Xifeng, Chishui, and Shibing, they have the largest amount of crop residue productions among all other counties. And for some eastern counties such as Kaiyang, Chishui and Cegong, etc. where corn is mainly grown, their corn residues are the highest among all three types of crops.

Table 6.5 Residue Production of Rice, Wheat and Corn per Household for each of the 88 Counties in Guizhou Province, 2016.

Annual corn Annual rice residue, Annual wheat residue residue (kg/household) (kg/household) (kg/household) Guiyang 122.4 143.2 131.8 Kaiyang xian 685.5 802.0 737.9 Xifeng xian 786.6 920.3 846.7 xiuwen xian 353.3 413.4 380.3 qingzhen xian 267.5 313.0 287.9 liupanshui shi 123.6 144.6 133.0 zhongshan qu 124 143 134 pan xian 77.7 90.9 83.6

157 liuzhi tequ 419.3 490.6 451.3 shuicheng xian 75.0 87.8 80.7 zuiyishi 344.2 402.7 370.5 zunyi xian 124 143 134 tongzi xian 181.3 212.1 195.2 suiyang xian 551.6 645.4 593.7 zheng an xian 229.6 268.6 247.1 daozhengelao 359.7 420.8 387.2 wuchuangelao 308.2 360.6 331.7 fenggang 679.8 795.4 731.7 meitan xian 124 143 134 yuqing xian 658.5 770.4 708.8 renhuai xian 121.7 142.4 131.0 chishui xian 690.8 808.2 743.6 xishui xian 124 143 134 tongren shi 345.3 404.0 371.7 jiangkou xian 381.9 446.8 411.1 yupingdongzu 372.0 435.2 400.4 shiqian xian 331.3 387.6 356.6 sinan xian 387.9 453.8 417.5 yinjiang tujiazu 330.9 387.2 356.2 dejiang xian 320.4 374.9 344.9 yanhetujiazu 225.4 263.7 242.6 songtao miaozu 610.8 714.6 657.5 wanshan tequ 547.3 640.3 589.1 qianxinan buyizu 124 143 134 xingyishi 268.2 313.8 288.7 xingren xian 233.0 272.6 250.8 puan xian 317.6 371.6 341.9 qinglong xian 212.4 248.5 228.6 zhenfeng xian 124 143 134 wangmo xian 257.3 301.0 277.0 ceheng xian 261.1 305.5 281.0 anlong xian 566.7 663.0 610.0 bijieshi 120.5 141.0 129.7 dafang xian 40.2 47.0 43.3 qianxi xian 141.4 165.4 152.2 jinsha xian 269.5 315.3 290.1 zhijin xian 181.8 212.7 195.7 nayong xian 23.1 27.0 24.9 weining 124 143 134

158 hezhang xian 14.7 17.2 15.8 anshun shi 361.9 423.4 389.5 pingba xian 452.9 529.9 487.5 puding xian 284.5 332.9 306.2 guanlinbuyizu 329.7 385.7 354.9 zhenningbuyizu 447.8 523.9 482.0 ziyunmiaozu 391.9 458.5 421.8 qiandongnan 124 143 134 kaili shi 337.6 395.0 363.4 huangping xian 124 143 134 shibing xian 949.5 1110.9 1022.0 sanhui xian 272.2 318.5 293.0 zhenyuan xian 363.7 425.5 391.5 cengong xian 605.0 707.9 651.2 tianzhu xian 376.8 440.9 405.6 jinping xian 385.4 450.9 414.8 jianhe xian 339.0 396.6 364.9 taijiang xian 435.6 509.7 468.9 liping xian 784.0 917.3 843.9 rongjiang xian 124 143 134 congjiang xian 653.5 764.6 703.4 leishan xian 439.9 514.7 473.5 majiang xian 633.7 741.4 682.1 danzhai xian 463.2 541.9 498.6 qianxinan 124 143 134 duyun shi 369.8 432.7 398.1 libo xian 443.2 518.5 477.1 guiding xian 390.1 456.4 419.9 fuquan xian 560.2 655.4 603.0 wengan xian 462.7 541.4 498.1 dushan xian 596.1 697.4 641.6 pingtang xian 485.5 568.0 522.6 luodian xian 124 143 134 changshun xian 586.7 686.4 631.5 longli xian 489.2 572.4 526.6 huishui xian 473.1 553.5 509.2 sandushuizu 454.2 531.4 488.9

159 6.3.2 Animal Manures Animal manures are another important feedstock materials for anabatic digestion. Normally, the weight of crop residue is requested to be below 1/3 of total weight of raw materials for biogas production (Liu, Jiang, Zhang & Wang, 2008). Thus, animal manures are the main resources for biogas digestion. Most animal manures in China are from 4 categories: (1) cattle and buffaloes, (2) pigs, and (3) sheep and goats and (4) chickens. The production of manures for cattle, pigs, sheep and chickens are estimated at household level in the 88 counties in Guizhou province. To estimate the manure productions, the daily or annually manure production per animal is applied. For a specific animal type in a county, the county’s annual manure production is calculated as using the county’s total number of animal multiplies by the annual manure production per animal (Yuan et al., 2005). This method is widely used to estimate animal manures for biogas production and is based on the relationship between number of animals and the manure production per animal. The general equation for estimating the county-level animal manure is as follow:

Pyra = Ayra * Myra (1)

Where Pyra is the amount of manure production for animal a in county r for the year y, kg; Ayra is the number (head) of animal a in county r for the year y; and

Myra is the annual manure production per animal for animal a in county r for the year y, kg/head. The theoretical available daily/annual manure production per animal in China are given in the below table:

Table 6.6 Daily/Annual Manure Production per Animal, kg/head.

Daily manure production Annual manure production

160 (kg/head) (kg/head) Cattle and 27.6 10,100 buffalos Pigs 2.88 1,050 Sheep and goats 2.38 870 Chickens 0.15 53 Source: Yuan et al., 2005.

The data for number of cattle and buffalos, pigs, sheep and goats and chickens of the 88 counties in Guizhou province are provided by each county’s 2016 Annual Economy and Social Status Report. Once the county’s 2016 animal numbers are obtained, they are multiplied by the annual manure production per animal to arrive at the annual manure productions for each type of animals. Because this study is focused on the household level, then the county’s manure productions are divided by the county’s household numbers to arrive at the manure productions per household for each type of animals. The general equation for estimating the household-level animal manure productions is as follow:

HPyra = Pyra / Hyr (2)

Where HPyra is the amount of manure production per household for animal a in county r for the year y, kg; Pyra is the amount of manure production for animal a in county r for the year y, kg; and Hyra is the number of households in county r for the year y. Similarly, the county’s population and number of households are obtained from the county’s 2016 Annual Economy and Social Status report. The below table shows the amount of manure production per household for pig, cattle, sheep and chicken in Guizhou’s 88 counties in the year 2016. Overall, pig manures are the largest among all manure productions in Guizhou since almost every household in the province raises pigs at home. For all the 88 counties in Guizhou, households have pretty good manure productions in 2016. Individually, big animal

161 husbandry counties such as Yuqing, Congjiang, and Wengan, they have the largest amount of manure productions among all other counties. And for some counties including Tongzi, Daozheng Gelao and Zhengan, etc. where cattle is mainly raised, their manure productions from cattle are the highest among all animal types.

Table 6.7 Manure Productions of Pig, Cattle, Sheep and Chicken per Household for each of the 88 Counties in Guizhou Province, 2016.

Pig manure per Cattle manure per Sheep manure Chicken manure household household per household per household (kg/year) (kg/year) (kg/year) (kg/year) Guiyang 1558.6 405.8 17.6 613.5 Kaiyang xian 5869.9 0.0 0.0 465.9 Xifeng xian 2546.9 2587.4 82.8 0.0 xiuwen xian 3547.0 1639.3 0.0 713.4 qingzhen xian 2118.7 0.0 12.9 3342.0 liupanshui shi 2150.7 881.9 135.0 343.0 zhongshan qu 966.2 237.1 48.0 224.7 pan xian 2077.3 868.9 132.1 228.4 liuzhi tequ 2496.2 997.7 151.9 534.0 shuicheng xian 2288.6 875.7 111.5 344.8 zuiyishi 3554.0 886.9 4.3 357.5 zunyi xian 3034.5 0.0 0.0 0.0 tongzi xian 2080.7 3550.0 359.9 0.0 suiyang xian 2986.4 802.2 0.0 0.0 zheng an xian 2074.5 3452.7 160.3 0.0 daozhengelao 2704.1 3623.5 341.8 0.0 wuchuangelao 2602.0 1566.5 373.3 0.0 fenggang 4432.9 788.4 128.0 0.0 meitan xian 3391.5 0.0 0.0 0.0 yuqing xian 5046.2 1042.5 513.0 0.0 renhuai xian 3677.1 709.4 219.1 0.0 chishui xian 2991.6 86.2 41.8 309.8 xishui xian 2856.0 0.0 0.0 0.0 tongren shi 2749.1 4423.6 492.1 0.0 jiangkou xian 3681.6 837.3 198.9 218.3 yupingdongzu 2304.8 4075.3 219.2 0.0

162 shiqian xian 3242.2 1120.7 435.8 311.7 sinan xian 3448.4 3941.0 324.0 0.0 yinjiang tujiazu 2312.1 3529.9 403.0 0.0 dejiang xian 2489.5 1204.2 797.9 0.0 yanhetujiazu 2256.1 1115.1 859.7 214.4 songtao miaozu 3927.0 1310.4 600.7 0.0 wanshan tequ 3477.4 5527.6 232.1 0.0 qianxinan buyizu 2312 0 0 0 xingyishi 3076.6 1018.1 89.0 471.8 xingren xian 1937.3 1011.8 59.8 323.7 puan xian 1767.4 1017.5 160.3 292.0 qinglong xian 1643.7 917.9 825.3 225.3 zhenfeng xian 3213.0 0.0 0.0 0.0 wangmo xian 2315.4 2153.9 550.6 429.6 ceheng xian 2140.2 2164.8 340.2 335.7 anlong xian 3006.6 1009.3 54.9 302.8 bijieshi 2977.8 1033.2 157.6 332.9 dafang xian 1611.2 523.1 53.7 308.1 qianxi xian 2280.8 562.0 36.0 363.1 jinsha xian 2717.9 729.2 64.0 429.8 zhijin xian 1845.1 923.6 50.9 0.0 nayong xian 1579.9 2583.2 107.3 0.0 weining 3670.5 1431.6 436.4 195.5 hezhang xian 2103.3 591.9 249.5 135.5 anshun shi 2294.1 1304.3 77.5 0.0 pingba xian 3213.0 0.0 0.0 0.0 puding xian 2222.3 5264.3 38.4 0.0 guanlinbuyizu 2562.1 2409.3 224.5 470.1 zhenningbuyiz u 1581.8 1183.4 81.5 0.0 ziyunmiaozu 4128.4 9340.6 189.6 0.0 qiandongnan 2312 0 0 0 kaili shi 2311.6 0.0 0.0 0.0 huangping xian 3213.0 0.0 0.0 0.0 shibing xian 3220.1 1030.9 121.8 0.0 sanhui xian 3097.1 852.2 238.0 0.0 zhenyuan xian 2322.0 0.0 0.0 0.0 cengong xian 2196.0 861.2 345.0 0.0 tianzhu xian 2949.0 433.9 125.9 853.6

163 jinping xian 2605.7 638.3 56.3 0.0 jianhe xian 2328.0 1849.2 338.2 288.4 taijiang xian 2013.8 1033.9 81.5 0.0 liping xian 2140.3 1448.4 65.8 0.0 rongjiang xian 3034.5 0.0 0.0 0.0 congjiang xian 8653.0 1969.0 85.3 457.5 leishan xian 2414.8 1310.8 80.4 233.1 majiang xian 4101.6 1329.7 126.8 1096.3 danzhai xian 3235.9 0.0 0.0 0.0 qianxinan 2312 0 0 0 duyun shi 3018.0 842.7 26.9 0.0 libo xian 2788.0 1951.7 126.5 0.0 guiding xian 2279.3 5036.6 0.0 0.0 fuquan xian 1968.1 3903.8 56.0 241.0 wengan xian 4892.7 1113.1 130.1 467.6 dushan xian 2629.6 1436.5 255.1 218.8 pingtang xian 2473.8 741.2 187.4 134.5 luodian xian 3034.5 0.0 0.0 0.0 changshun xian 2858.1 1713.6 333.1 0.0 longli xian 2376.8 0.0 137.2 0.0 huishui xian 2234.4 6492.0 0.0 0.0 sandushuizu 2415.4 1279.7 35.2 0.0

6.4 Energy Analysis of Household Biogas Digesters in Guizhou Province

6.4.1 Overview of ABEPE Model for Energy Analysis Animals database for energy potential estimation (ABEPE) model combined with feedstock data are used in this study to investigate the estimation of biogas production for Guizhou rural households. The ABEPE model was first proposed by Dr. Batzias et al. to estimate biogas production from major crop residues (rice, wheat and corn) and manures of livestock (pig, cattle, sheep and chicken) in Greece (Batzia et al., 2005). Now this model has been implemented in a number of Chinese literatures including Tang et al., Chen et al., to estimate the biogas potential for household biogas digesters in rural China (Chen et al., 2012; Tang et al., 2010). For this study, ABEPE

164 model is used to estimate the household-level daily/annual gas potential from crop residues and animal manures of the 88 counties in Guizhou province. The workflow diagram of ABEPE is presented in the below figure, which describes the operation steps of the model in this study. The input data for the model are the quantities of household-level feedstock. Specifically, the data includes the above-mentioned household-level annual amount of residue productions of rice, wheat and corn and the amount of annual manures of pig, cattle, sheep and chicken in each 88 counties in Guizhou province. There are four major steps involved with this model. The first step is to calculate the dry matter content of the feedstock. This is because the majority content of crop residues and animal manures is water, but only dry matter content is correlated with the amount of available biogas could be produced from the feedstock. Depending on the dry matter content of the feedstock, the second step estimates the theoretical biogas production by each type of feedstock. For this step, the biogas yield values of each type of feedstock are applied. When each feedstock’s biogas production is calculated, the third step aggregates them together to arrive at the household’s total annual theoretical biogas potential. Because this aggregated gas potential is only a theoretical calculation, factors that affect the actual biogas potential include ground-level temperature, the biogas plant usage time, etc. should also be considered. Thus, the final step adjusts the theoretical values to actual daily/annual gas production per household based on temperature and usage time factors. Depending on the actual values, counties that have potentials to develop household biogas digesters are identified.

165

Figure 6.5 Flow Diagram Describes the Steps of “ABEPE” Model in this Study.

6.4.2 Energy Output and Potential Household Biogas Digester Markets in Guizhou Province Based on the APEPE model, the steps for calculating the biogas production potential for Guizhou rural households are provided below:

Step 1: Calculate dry matter content of crop residues and animal manures

DMyra = Pyra * DMFyra (1)

Where Pyra is the amount of crops residue/animal manure a in county r for the year y, kg; and DMFyra is the dry matter factor of crop residue/animal manure a in county r for the year y. This step is important because majority of the feedstock is water, but only dry matter content is correlated with the amount of biogas could be produced from the biogas plant. The below table provides the dry matter content factor for each type of crop residues and animal manures in China:

Table 6.8 Dry Matter Content Factors for Crop Residues and Animal Manures.

Items Dry matter factor (DMFyra) Crop residues Rice 0.36 Wheat 0.56

166 Corn 0.31 Animal manures Pig 0.15 Cattle 0.16 Sheep 0.37 Chicken 0.65 Source: Chen et al., 2012; Tang et al., 2010.

Step 2: Calculate theoretical biogas production for each type of crops and animals

Byra = DMyra * BYFyra (2)

Where DMFyra is the dry matter content of crop residue/animal manure a in county r for the year y; and BYFyra is the theoretical biogas yield factor of dry matter content of crop/animal a in county r for the year y, m3/kg. The yield factors of crop residues and animal manures depend on their physical and biochemical properties and on digestion process parameters such as temperature (Einarsson & Persson, 2017). The table below indicates the production of biogas per kg of dry matter consents for different materials typically use in a digester in China:

Table 6.9 Biogas Yield Factors for Crops Residues and Animal Manures (Dry Matter Contents).

Items Biogas yield factor (BYFyra, m3/kg) Crop residues Rice 0.4 Wheat 0.45 Corn 0.5 Animal manures Pig 0.42 Cattle 0.30 Sheep 0.04 Chicken 0.50 Source: Chen et al., 2012; Tang et al., 2010.

167 Step 3: Calculate the total theoretical amount of biogas quantity

∑ (3)

Where is the total amount of theoretical biogas production from all types of feedstock in county r for the year y, m3.

Step 4: Modify the total amount of biogas quantity

= ∗ Tyr * Lyr (4)

Where is the total modified amount of biogas production from all types of feedstock in county r for the year y, m3; is the total amount of biogas production before adjustment from all types of feedstock in county r for the year y, m3;

Tyra is the temperature factors in county r for the year y; and Lyr is the gas production time factor in county r for the year y. Temperature is the most important factor affecting biogas production from the biogas plant. The effect of temperature on biogas production has been mentioned in several studies (Chen & Hashimoto, 1978; Gavala et al., 2003; Ma et al., 2013). In general, biogas production drops dramatically in December and January than the rest of months because the temperature during the summer is higher than in the winter (Kalia & Singh, 1998; Pham et al., 2013; Pham et al., 2014). There is a cubic relationship between biogas production and the temperature increasing from 10 C to

35 C (Sommer et al., 2007; Pham et al., 2013). Biogas fermentation is happened most rapidly at the temperature of 35C of which the temperature factor is 1.0. As temperature decreases, the temperature factor decreases accordingly – at the temperature of 15C, the temperature factor drops to 0.63 (Chen et al., 2012). In Guizhou province, the average ground temperature varies from 13.4 C to 21.3 C in its 88 counties, thus the total biogas production in each county should be modified

168 according to their temperature factors individually. In addition, for most of the rural households in Guizhou, biogas plant isn’t operated all day 24 hours or all around the year – only a certain amount of hours the digester will work. Therefore, the biogas production should also be adjusted according to the actual usage time of the household. And the usage time information is obtained from existing literature regarding the average cooking time in each of Guizhou’s 88 counties. Based on the above-mentioned steps, the adjusted annual/daily total biogas potential from all types of feedstock in Guizhou’s 88 counties is calculated. According to Otim et al., the average quantity of gas required for cooking per person is about 0.227m3 (Otim et al., 2012). Considering the average rural household size in Guizhou province is about 3.53, then the required gas per day per household is abut 0.227 * 3.53 = 0.8m3 of gas. In this sense, the annual required gas per household is 0.8 * 365 = 292m3 of gas. Bear the daily 0.8m3 and annual 292m3 gas requirement per rural household in mind, out of all 88 counties in Guizhou province, 56 of them (64% of the province) can reach this level based on the above calculation steps. Therefore, these counties are regarded as the potential markets in Guizhou province to promote household biogas digester. The table under lists these 56 counties in terms of both of their theoretical and modified annual/daily biogas productions. Also the GIS map below highlights those counties. Counties such as Ziyun, Congjiang, and Majiang because they are big agricultural counties, they have daily gas potential larger than 2m3 per household.

169 Table 6.10 List of Potential Markets in Guizhou Province for Household Biogas Digester (Counties with Daily/Annual Modified Gas Production > 0.8m3/292m3 per Household).

Total annual Total daily Adjusted theoretical theoretical Tempera Adjusted daily gas gas gas ture Usage annual gas productio production production factor factor production n m3/year/hou m3/day/hou m3/year/h m3/day/h sehold sehold ousehold ousehold 1 Guiyang 352.7 1.0 0.89 1 313.9 0.9 Kaiyang 2 xian 619.9 1.7 1 1 619.9 1.7 Xifeng 3 xian 460.9 1.3 0.92 0.92 390.1 1.1 xiuwen 4 xian 638.1 1.7 0.98 0.99 619.1 1.7 qingzhen 5 xian 1281.5 3.5 0.84 0.92 990.3 2.7 liupanshu 6 i shi 391.8 1.1 1 1 391.8 1.1 7 pan xian 352.2 1.0 1 0.95 334.6 0.9 liuzhi 8 tequ 533.0 1.5 1 0.98 522.4 1.4 shuichen 9 g xian 397.2 1.1 1 0.97 385.3 1.1 10 zuiyishi 478.3 1.3 1 0.96 459.2 1.3 tongzi 11 xian 374.5 1.0 0.92 1 344.6 0.9 suiyang 12 xian 362.5 1.0 0.93 1 337.1 0.9 zheng an 13 xian 384.1 1.1 0.95 1 364.9 1.0 daozheng 14 elao 458.2 1.3 1 0.97 444.4 1.2 wuchuan 15 gelao 352.3 1.0 1 0.98 345.3 0.9 16 fenggang 486.3 1.3 1 0.99 481.4 1.3 yuqing 17 xian 532.5 1.5 1 0.95 505.9 1.4 chishui 18 xian 429.3 1.2 1 0.98 420.7 1.2

170 tongren 19 shi 478.5 1.3 0.99 1 473.8 1.3 jiangkou 20 xian 420.4 1.2 0.98 0.92 379.0 1.0 yupingdo 21 ngzu 421.2 1.2 0.98 0.97 400.4 1.1 shiqian 22 xian 456.0 1.2 0.89 0.99 401.8 1.1 sinan 23 xian 522.8 1.4 0.92 0.92 442.5 1.2 yinjiang 24 tujiazu 401.7 1.1 0.99 1 397.7 1.1 yanhetuji 25 azu 362.8 1.0 1 0.88 319.3 0.9 songtao 26 miaozu 449.7 1.2 0.98 0.92 405.4 1.1 wanshan 27 tequ 594.3 1.6 0.99 0.95 559.0 1.5 28 xingyishi 538.1 1.5 1 1 538.1 1.5 xingren 29 xian 399.2 1.1 1 1 399.2 1.1 puan 30 xian 348.5 1.0 0.99 0.88 303.6 0.8 qinglong 31 xian 343.0 0.9 0.89 0.96 293.1 0.8 wangmo 32 xian 489.8 1.3 1 1 489.8 1.3 ceheng 33 xian 444.7 1.2 0.98 1 435.8 1.2 anlong 34 xian 514.2 1.4 0.97 0.99 493.8 1.4 35 bijieshi 387.0 1.1 0.95 0.89 327.2 0.9 qianxi 36 xian 327.7 0.9 1 0.97 317.9 0.9 jinsha 37 xian 470.5 1.3 0.99 1 465.7 1.3 38 weining 448.8 1.2 1 0.95 426.3 1.2 puding 39 xian 465.6 1.3 0.99 1 460.9 1.3 guanlinb 40 uyizu 666.2 1.8 0.98 1 652.9 1.8 41 ziyunmia 801.2 2.2 1 0.98 785.2 2.2

171 ozu shibing 42 xian 390.9 1.1 1 1 390.9 1.1 sanhui 43 xian 318.9 0.9 1 0.98 312.5 0.9 tianzhu 44 xian 588.5 1.6 0.98 0.94 542.1 1.5 jianhe 45 xian 407.2 1.1 0.95 1 386.8 1.1 congjian 46 g xian 922.5 2.5 1 1 922.5 2.5 leishan 47 xian 386.7 1.1 1 0.99 382.8 1.0 majiang 48 xian 816.9 2.2 1 0.97 792.4 2.2 49 libo xian 360.3 1.0 1 0.98 353.1 1.0 guiding 50 xian 469.3 1.3 1 0.99 464.7 1.3 fuquan 51 xian 511.1 1.4 1 0.95 485.6 1.3 wengan 52 xian 640.3 1.8 1 1 640.3 1.8 dushan 53 xian 434.7 1.2 1 0.96 417.4 1.1 pingtang 54 xian 378.9 1.0 1 1 378.9 1.0 changshu 55 n xian 402.1 1.1 0.98 0.94 370.4 1.0 huishui 56 xian 559.1 1.5 0.97 0.99 536.9 1.5

172

Figure 6.6 Potential Markets in Guizhou Province for Household Biogas Digester (Counties with Daily/Annual Modified Gas Production > 0.8m3/292m3 per Household).

173 6.5 Economic Analysis of Household Biogas Digesters in Guizhou Province

6.5.1 Overview of RREAD for Economic Analysis Similar to the economic analysis for the solar home system in Guizhou mentioned in Chapter 5.4, RREAD is also applied to the economic analysis for household biogas digester in the province. The model of RREAD for economic analysis has three modules: a data input module, a calculation module, and an output module. Cost parameters of the system, as well as financial terms and subsidy data are used as the input values in RREAD for the economic evaluation. Once data are input, RREAD calculates the levelized energy costs (LCOEs) of household biogas digesters over the evaluation period. In addition, the model compares the economic performance of household biogas digesters with other competitive cooking methods such as cooking with LPG and cooking with coal. This provides a clear idea of how the household biogas digester can provide greater economic benefits than the other alternatives in rural Guizhou.

6.5.2 Preparation of Cost Stream The current cost of building a household biogas digester varies from $200 to $400 around the world. For example, the cost of a fixed dome model in Thailand costs around $180, in Peru the cost of a PVC tubular digester costs around $250, and in Costa Rica a plug flow digester costs $300 (Rajendran, 2012). In Guizhou and China, the most commonly installed household biogas digester is a 8 m3 fixed dome digester, and it is enough for daily cooking and lighting for a household with 4-6 people (Yang, 2012). The government data shows that a total construction cost of an 8 m3 biogas digester in usually ranges from 2,250 CNY ($330) to 4,850 CNY ($713) across all provinces in China, with a mean value of around 3,000 CNY ($442) (Xia, 2013). The

174 higher costs are likely occurred well-developed areas or remote rural areas, as the labor costs are high in the well-developed areas and the material and transportation costs are high in remote places. To calculate the economics of household biogas digesters in Guizhou, several cost factors need to be determined. The total cost of a household biogas digester is usually divided into three categories: (1) construction costs, (2) maintenance costs and (3) government subsidies. The construction costs have 3 major components: (a) materials that are used to construct the digester such as cement, sand, gravel, bricks, steel and wire; (b) labors (working hours) on excavation and construction such as workers spend days on digging the hole and steel mold used to cast concrete; (c) matching appliances such as gas pressure gauge, gas cookers and pipelines. Maintenance costs include (a) minor maintenances that occur every year and (b) major maintenance that occur every five years. In addition, the government subsidies need to be subtracted from the total costs paid by the rural households. In this study, the subsidies include (a) subsidy from central government and (b) the matching subsidy from provincial and county government. The equation to calculate the cost of household biogas digester in Guizhou is given below:

= L + A + T – S (1) Where C is the final costs of a 8 m3 fixed dome biogas digester paid by the rural Guizhou household; M is the material costs including bricks, cement, pipes, etc.; L is the labor cost of the workers; A is the cost of matching appliances; T is the cost of major and minor maintenances; and S is the national and local government subsidies and it should be subtracted from the total cost afforded by rural Guizhou household in the formula.

175 The materials to construct a household biogas digester include cement, bricks, sands, stones, concrete, ceramic tiles and bamboo and wood supports (Li et al., 2011; Ministry of Agriculture, 2007; Hao & Shen, 2006; Peng, 2009). To build a typical fixed dome 8 m3 biogas plant in Guizhou and China, it requires about 1.5 tons of cement, 1,750 pieces of bricks, 2m3 of sands and stones for each, 5m3 ceramic tiles, 8kg concretes and 1set of bamboo and wood supports (Ministry of Agriculture, 2007; Hao & Shen, 2006; Peng, 2009). On average, the total cost of these materials is around 3,270 CNY ($480) (Liu & Yu, 2009; Wang, 1999; Peng, 2009; Hao & Shen, 2006). The matching appliances for the digester include pipelines, pressure meters, utensils, etc., and their cost is about 400 CNY ($58.8) (Ministry of Agriculture, 2007). Usually the matching appliances need to be replaced every 10 years. To construct the digester, workers need to spend days on digging the hole and steel mold used to cast concrete. A 8m3 biogas plant usually takes about 15 working days to build and cost around 450 CNY ($66.2) (Ministry of Agriculture, 2007; Liu & Yu, 2009; Wang, 1999; Peng, 2009; Hao & Shen, 2006). Based on the energy analysis sector, the 56 selected potential markets in Guizhou can have daily household biogas potential more than 0.8m3. Since the households in those counties have enough feedstock to meet their daily gas requirement, they don’t need to buy crop residues or manures from the market. Thus the only operational cost for rural households is the maintenances such as repairing or replacement the worn parts. It is very difficult to determine the maintenance costs than the construction costs. The problem is the actual maintenance costs are difficult to estimate. In the past, the maintenance costs are largely ignored because the people don’t realize the importance of maintenances. Today, as the increase of awareness,

176 maintenance costs must be taken account into the costs of digester. Moreover, the insufficient of maintenance has been recognized as a major challenge to the use of biogas digester in many provinces in China. Studies have shown the annual maintenance cost for a typical 8m3 household biogas digester in China varies from 25 CNY ($4)/year to 165 CNY ($24)/year (Hao et al., 2015; Wang & Zhang, 2013; Kuang et al., 2011; Zhao & Guo, 2009; Xia, 2013; Huang, 2010). And skilled technicians are required to perform such maintenances like feeding and discharging the slurry (Garcia, 2011; Xia, 2013). As an average, this study considers the annual regular maintenance cost of around 100 CNY ($15) (Hao & Shen, 2006). And for the major repair and maintenance that occurs every 5 year, the cost is considered as around 500 CNY ($74) (Hao & Shen, 2006). In addition to the construction and maintenance costs of household biogas digesters, subsidies from the government must also be taken into account. In China, major sources of subsidies for household biogas digesters come from both the national government and matched or additional funding from local government at provincial or county levels. The amount of subsidy from Chinese central government was 800 – 1,200 CNY per digester in 2003. And this number was increased to 1,300 CNY ($191) – 3,500 CNY ($515) in 2011, depending on locations (XZBU, 2011; Ding & Zheng, 2013; Ministry of Agriculture, 2011). In specific, subsides for eastern, central and western regions are 1,300 CNY ($191), 1,600 CNY ($235) and 2,000 CNY ($294) respectively (XZBU, 2011; Ding & Zheng, 2013; Ministry f Agriculture, 2011). And subsidy from remote and less developed provinces of Tibet and Xinjiang Autonomous Region is 3,000 CNY ($441) (Ding & Zheng, 2013). Since Guizhou province is located at the western part of China, households who wish to build a biogas digester

177 will receive 2,000 CNY ($294) from the national government. On top of subsidy from central government, Guizhou province and local counties will match an additional subsidy of 450 CNY ($55) and 150 CNY ($22) respectively. When calculating the total cost of a household biogas digester that a rural household need to pay, these subsides should be subtracted. In addition to the above-mentioned cost parameters in terms of construction, maintenance and subsidy, a few other factors also need to be considered. For example, if the digester is failed to work during the summer, it will cause several odor problem. Again, when a digester is failed to work promptly, backup solutions are needed to satisfy the household’s daily gas requirement. Also when the workers are repairing the digester, potential risks such as suffocation may occur if no proper safety instructions are met. Due to the data and time limits, this study will not include these factors for the cost preparation, however, it is always good to bear in mind some extra costs may occur along with the construction and use of the household biogas digester. The table below lists the cost parameters considered in this study. Without national or local government subsidies, the upfront cost of a typical fixed dome 8m3 biogas digester installed in Guizhou province will be 4,120 CNY ($605.8). And majority (3/4) of the cost comes from materials used to construct the digester. However, if national and matching local government subsides are taken into account, its total cost will reduce to 1,520 CNY ($224), or a 63% decrease.

Table 6.11 Cost Parameters for a Typical Fixed Dome 8m3 Biogas Digester in China.

Basic information Volume 8m3

178 Lifetime 15 years Upfront costs without subsidy 4120 CNY ($605) Upfront costs with subsidy 1520 CNY ($224) Construction costs (materials, labor, matching appliance) Cement 1.5 tons, 1000 CNY ($147) Bricks 1750 pieces, 700 CNY ($103) Sands 2m3, 400 CNY ($58.8) Crushed stones 2m3, 400 CNY ($58.8) Concrete 8kg, 120 CNY ($17.6) Ceramic tiles 5m3, 400 CNY ($58.8) Bamboo and wood supports 1 set, 250 CNY ($36.8), replace every 10 years Matching utensils and accessories 1 set, 400 CNY ($58.8), replace every 10 (pipelines, pressure meters, etc.) years Labor costs 15days, 450CNY ($66.2) Maintenance Costs Annual minor maintenance 100 CNY/year ($14.7) Regular major maintenance 500 CNY every 5 years ($73.5) Government subsidies Central government 2000 CNY/household ($294.1) Provincial government 450 CNY/household ($66.2) City government 150 CNY/household ($22.1) Other Basic Economic Information Discount rate (%) 2.9 Evaluation period (year) 10 Currency conversion rate (Yuan/US$) 6.8

6.5.3 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) The above-mentioned upfront cost of a household biogas digester is only a simple measure and gives the number of costs needed at the initial year. Consider that normally biogas digesters have an expected lifetime of approximately 15 – 25 years, in most cases the simple initial cost is not enough because it doesn’t take into account that costs are discounted over the evaluation period. Nor does it include price

179 inflation/discount. For these reasons, it is important to compute net present value (NPV) costs of the household biogas digester. After the cost stream of biogas digester is prepared, these costs are discounted in order to calculate the net present values costs (NPV) over the evaluation period. Similar to the economic analysis of solar home systems discussed in the previous chapter, RREAD is again used to discount each of the future costs to their present values in the evaluation period. Once the yearly discounted future costs are determined, RREAD sums up all values to arrive at a total NPV costs. The total net present value costs of household biogas digesters will be further standardized over its evaluation years. Financially, this is called the levelized annual NPV cost. In this study, the levelized annual NPV cost refers to the yearly constant cash payment should be made for household biogas digester over the evaluation time. Again, RREAD is utilized to calculate the levelized NPV cost of the system. Once the levellized annual NPV cost is determined, the number is divided by the annual biogas production value to obtain the unit cost of biogas ($/m3), and this is called levelized cost of energy (LCOE). In the RREAD, LCOE could be calculated from both supply perspective and demand perspective. From supply side, the annual biogas value is how much biogas could be produced from the biogas digester. From the demand side, the annual biogas value is how much biogas consumed from the end- users. In this study, the demand perspective is used when calculating the LCOE. However, when the system supply couldn’t meet the household’s biogas consumption, then supply perspective is applied instead. The levelized cost of biogas ($/m3) is calculated for the rural households in the 56 counties in Guizhou that have the potential to develop household biogas digester.

180 And the calculations are based on both the demand perspective and supply perspective. In addition, the evaluation period of this study is set at 10 years, and the discount rate is set at 2.9% which is same as the real discount rate of China (Attia, 2016). The table here depicts the results of RREAD analysis for the LCOE for those counties. The quality of manure and crop residue influences the generating capacity of the household biogas digester system by county, so does it affect the overall economic performance of the system. For those 56 potential markets, the LCOE is $0.24/m3 regardless of how high or low the biogas yields from the system in that county. This is because the calculation in this study is based on the consumption perspective, which means the energy value used in the simulation equals to the user’s annual energy requirement (292 m3) instead of the system’s net production. By contrast, if under a supply perspective, RREAD sets the annual energy value equals to the system’s net production, the LCOE will be varied from $0.08/m3 to $0.24/m3 across these 56 counties. Counties with more manures and crop residues thus have higher modified biogas production, and they have lower levelized biogas costs.

Table 6.12 Levelized Energy Costs (LCOE) for Household Biogas Digester in the 56 Potential Counties in Guizhou Province.

Adjusted gas LCOE ($/m3) LCOE ($/m3) Counties production Consumption Supply (m3/year/household) perspective perspective 1 Guiyang 313.9 0.24 0.22 2 Kaiyang xian 619.9 0.24 0.11 3 Xifeng xian 390.1 0.24 0.18 4 xiuwen xian 619.1 0.24 0.11 5 qingzhen xian 990.3 0.24 0.08 6 liupanshui shi 391.8 0.24 0.18

181 7 pan xian 334.6 0.24 0.21 8 liuzhi tequ 522.4 0.24 0.13 shuicheng 9 xian 385.3 0.24 0.18 10 zuiyishi 459.2 0.24 0.15 11 tongzi xian 344.6 0.24 0.20 12 suiyang xian 337.1 0.24 0.21 13 zheng an xian 364.9 0.24 0.19 14 daozhengelao 444.4 0.24 0.16 15 wuchuangelao 345.3 0.24 0.20 16 fenggang 481.4 0.24 0.15 17 yuqing xian 505.9 0.24 0.14 18 chishui xian 420.7 0.24 0.17 19 tongren shi 473.8 0.24 0.15 20 jiangkou xian 379.0 0.24 0.18 21 yupingdongzu 400.4 0.24 0.18 22 shiqian xian 401.8 0.24 0.17 23 sinan xian 442.5 0.24 0.16 yinjiang 24 tujiazu 397.7 0.24 0.18 25 yanhetujiazu 319.3 0.24 0.22 songtao 26 miaozu 405.4 0.24 0.17 27 wanshan tequ 559.0 0.24 0.13 28 xingyishi 538.1 0.24 0.13 29 xingren xian 399.2 0.24 0.18 30 puan xian 303.6 0.24 0.23 31 qinglong xian 293.1 0.24 0.24 32 wangmo xian 489.8 0.24 0.14 33 ceheng xian 435.8 0.24 0.16 34 anlong xian 493.8 0.24 0.14 35 bijieshi 327.2 0.24 0.21 36 qianxi xian 317.9 0.24 0.22 37 jinsha xian 465.7 0.24 0.15 38 weining 426.3 0.24 0.16 39 puding xian 460.9 0.24 0.15 40 guanlinbuyizu 652.9 0.24 0.11 41 ziyunmiaozu 785.2 0.24 0.09 42 shibing xian 390.9 0.24 0.18

182 43 sanhui xian 312.5 0.24 0.22 44 tianzhu xian 542.1 0.24 0.13 45 jianhe xian 386.8 0.24 0.18 congjiang 46 xian 922.5 0.24 0.08 47 leishan xian 382.8 0.24 0.18 48 majiang xian 792.4 0.24 0.09 49 libo xian 353.1 0.24 0.20 50 guiding xian 464.7 0.24 0.15 51 fuquan xian 485.6 0.24 0.14 52 wengan xian 640.3 0.24 0.11 53 dushan xian 417.4 0.24 0.17 54 pingtang xian 378.9 0.24 0.18 changshun 55 xian 370.4 0.24 0.19 56 huishui xian 536.9 0.24 0.13 Overall: 0.08 – 0.24

6.5.4 Comparison with Alternative Cooking Methods

6.5.4.1 Comparison with LPG-based Cooking The above economic analysis shows that the household biogas digester can not only provide enough energy to meet household’s daily and annual cooking needs, it also offers an cost-effective way to meet the household’s cooking needs. Today in

Guizhou, for rural households that don’t have biogas digester, liquefied petroleum gas (LPG) is commonly used as an energy source for cooking and in more remote and dispersed communities also burning coal and biomass. The direct economic benefits of biogas as a cooking fuel could be calculated by substituting alternative fuels such as LPG, coal and biomass where biogas is used for cooking. The calculating results may change due to price difference of fuels. For example, LPG-based cooking is a useful

183 reference to biogas digester-based cooking from cost perspective since LPG is a similar cooking fuel to biogas. In Guizhou, the current market price for LPG is about 100 CNY ($14.7) per cylinder, and each cylinder contains about 14.5kg of LPG (CNgold, 2017). In terms of energy conversion, 1m3 of biogas has roughly equivalent energy to 0.45 kg of LPG (Ananthakrishnan et al., 2013). And the energy cost for LPG is derived from following steps: Step 1: Calculating the unit cost of LPG ($/kg) 100 CNY/14.5kg = 7CNY ($1.03)/kg Step 2: Calculating 1kg LPG equivalent of biogas 1 / (0.45kg/m3) = 2.22 m3/kg Step 3: Calculating energy cost of LPG ($/m3) (7CNY/kg) / (2.22m3/kg) = 3.15CNY/m3 = $0.46/m3 Considering that the levelized energy cost of cooking with household biogas digester is about $0.24/m3, cooking with LPG is thus about twice more expensive than biogas digester. However, the calculated energy cost of $0.46/m3 is only the operating costs for LPG (or fuel costs), the total costs associated with LPG based cooking should also include the security deposit for cylinder(s), pressure regulator, transportation, as well as the costs of gas stove and other administration costs (Jain et al., 2015).

Table 6.13 Cost Parameters for LPG Based Cooking.

LPG based cooking system costs Application, installation (labor), and 2,000 CNY ($426) administration fee Transportation cost 70 CNY ($10) Deposit for cylinder 50 CNY ($7.3) Matching utensils and accessories 1 set,500 Yuan ($73.5), replace every 10 (pressure regulator, stove, etc.) years

184 Operational costs Annual LPG fuel costs 9 cylinders (900CNY, $132) Maintenance Costs Annual minor maintenance 100 CNY/year ($14.7) Regular major maintenance NA Other Basic Economic Information Discount rate (%) 2.9 Evaluation period (year) 10 Currency conversion rate (Yuan/US$) 6.8 Source: CNgold, 2017; Jain et al., 2015.

Table 6.14 Cost Comparison between Household Biogas Digester and LPG-Based Cooking.

Household biogas digester LPG-based cooking

System Materials: 3,270 CNY ($480) Application, labor, administration: related costs Labor: 450 CNY ($66.2) 2,000 CNY ($426) Transportation: 70 CNY ($10) Deposit: 50 CNY ($7.3) Utensil 400 CNY (58.8), replace very 500 CNY ($73.5), replace every 10 10 years years Maintenances 100 CNY ($14.7)/year 100 CNY ($14.7)/year 500 CNY ($73.5) every 5 years Fuel costs NA 900 CNY ($132) Incentives 2,600 CNY ($382) NA

When all the cost parameters are included, the key outcome emerging from the above economic analysis shows biogas is a more cost-effective solution for cooking in economic terms. The LCOE for biogas is $0.24 per cubic meters, which is about 1/3 of that for LPG, which stands at $0.69 per cubic meter. However, it must be noted that the increased price of imported fuel will also directly increase that of LPG, which will

185 in turn increase the cost burden on customers. In addition, transportation cost is an important variable determining the cost of LPG based cooking. Consequently, in the future, if fuel costs and transportation costs continue to grow, it can be expected that biogas digesters will become even more economically viable.

0.8

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Figure 6.7 LCOE Comparison between Household Biogas Digester and LPG for Cooking (unit: $/m3).

6.5.4.2 Comparison with Coal and Biomass-based Cooking Today, in Guizhou province, about 2.25 million rural households rely on coal and 2.97 million rely on biomass for cooking (National Bureau of Statistics, 2011). Compared to the LPG based cooking, if biogas used for cooking is taken as a substitute for coal or biomass, the direct savings would be much lower since their prices are low.

186 In the case of cooking coal stoves, there are two major types of coal stoves in Guizhou province: (1) traditional cook stove and (2) advanced cook stove. The efficiency of traditional coal stove is around 35%, while the advanced cook stove has improved thermal efficiency of 45% (World Bank, 2013). Both two types of stove utilize coal bricks for fuel, and the weight of a typical sold coal brick in China is about 0.9kg and its average price is about 1CNY ($0.15) per piece (Taobao, 2017). As calculated in the previous section, the required biogas volume to meet cooking energy demand of a typical rural household in Guizhou is about 0.8m3 per day or 292m3 per year. If coal is used as the cooking fuel, then the energy conversation factor is applied. Theoretically, 1m3 of biogas is roughly equivalent to 1.458 kg of charcoal (Nijaguna, 2002). The table below lists the factors considered when calculating the fuel cost of coal for cooking in Guizhou.

Table 6.15 Factors Considered when Calculating the Annual Fuel Cost of Coal.

Required energy to meet household’s 0.8m3/day or 292m3/year of biogas average daily/annual cooking needs (in the case of biogas is used as cooking fuel) Energy conversion factor 1m3 of biogas = 1.458 kg of charcoal 1 piece of charcoal brick = 0.9kg of charcoal Cooking efficiencies 35% for traditional stove 45% for advanced stove Price of coal brick 0.5CNY/piece ($0.08) Source: Taobao, 2017; World Bank, 2013; Nijaguna, 2002.

The following are the steps to calculate the annual fuel cost of coal for cooking in Guizhou: Step 1: Calculating amount of coal needed per year to meet the cooking energy for an average rural household in Guizhou province:

187 292m3 * 1.458kg/m3 = 426kg Step 2: Adjusting the amount of coal needed based on cooking efficiencies

 For traditional stove: 426kg / 0.35 = 1,217kg  For advanced stove: 426kg / 0.45 = 947 kg Step 3: Calculating number of coal bricks are needed:

 For traditional stove: 1,217kg / (0.9kg/piece) = 1,352 pieces  For advanced stove: 947kg / (0.9kg/piece) = 1,052 pieces Step 4: Calculating the annual fuel costs

 For traditional stove: 0.5CNY * 1,352 = 676CNY ($100)  For advanced stove: 0.5CNY * 1,052 = 526CNY ($78) The calculation shows that the annual fuel costs for coal based cooking in Guizhou are about 676 CNY ($100) and 526 CNY ($78) depending on the type of coal stove. However, the fuel cost is only part of the total cost associated with coal based cooking. Other costs such as transportation, maintenance, installation, etc. should also be considered when comparing the levelized energy costs (LCOEs) of biogas and coal based cooking methods. It is noted that, unlike biogas plant or LPG stove, coal stoves have short life times. Thus it needs to be replaced every 5 years (Habermehl, 2007). Also coal stoves require minimum maintenance such as cleaning and the cost is as low as 10 CNY per year. And Table 6.16 lists the main cost parameters considered for the economic analysis of coal-based cooking (Habermehl, 2007; Jeuland & Pattanayak, 2012; Gujba et al., 2015; Wu et al., 2015; Feng, 2016).

Table 6.16 Cost Parameters for Coal-based Cooking.

Coal based cooking system costs Application, installation (labor) 600 CNY ($88.2), replace every 5 years

188 Transportation cost 50 CNY ($7.4) Matching utensils and accessories 1 set, 100 Yuan ($15), replace every 5 years Operational costs Annual coal fuel costs Traditional stove: 676CNY ($100) Advanced stove: 526CNY ($78) Maintenance Costs Annual minor maintenance 10 Yuan/year ($1.47) Other Basic Economic Information Discount rate (%) 2.9 Evaluation period (year) 10 Currency conversion rate (Yuan/US$) 6.8

Table 6.17 Cost Comparison between Household Biogas Digester and Coal-Based Cooking.

Household biogas digester Coal-based cooking

System related Materials: 3,270 CNY ($480) Installation, material, labor costs: costs Labor: 450 CNY ($66.2) 600 CNY ($88.2), replace every 5 years Transportation: 50 CNY ($7.4) Utensil 400 CNY (58.8), replace very 10 100 CNY ($15), replace every 5 years years Maintenances 100 CNY ($14.7)/year 10 CNY ($1.47) every year 500 CNY ($73.5) every 5 years Fuel costs NA Traditional: 676 CNY ($100) Advanced: 526 CNY ($78) Incentives 2,600 CNY ($382) NA

According the RREAD analysis, the levelized energy costs (LCOEs) of coal- based cooking are $0.33/m3 for advanced cook stoves and $0.41/m3 for traditional cook stoves over the evaluation period. Compared to the levelized energy costs (LCOEs) of biogas digester of $0.24/m3, coal-based cooking is about 40% to 70%

189 more expensive. However, it must be noted that the fluctuation of coal prices will also directly influences that of coal-based cooking, which will in turn increase or reduce the cost burdens on customers. In addition, transportation cost is an important variable determining the cost of coal based cooking. Consequently, in the future, if coal costs and transportation costs grow, it can be expected that biogas digesters become even more economically viable.

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Figure 6.8 LCOE Comparison between Household Biogas Digesters and Coal for Cooking (Unit: $/m3).

The economic analysis of biomass-based (such as firewoods) cooking is more difficult than coal-based cooking. This is because the estimation of fuel costs of biomass is not always available. Unlike people need to buy LPG or coal from the market, biomass, such as firewoods are collected by people, usually women and children for cooking, and they are free or don’t cost much. In this sense, the energy

190 cost of biomass-based cooking is cheaper than biogas-based cooking, since both the biomass stove and fuel costs are minimum. However, in the case of biomass-based cooking (as well as in the case of coal-based cooking), some indirect costs should also be considered. These costs include time spent on collecting the fuels and cooking, gender inequity between women and men in terms of collecting biomass, indoor air pollution when cooking with firewood, deforestation due to fuelwood harvesting, etc. Usually biogas users are far more concerned with direct benefits/costs (such as system capital cost, fuel cost, etc.) than indirect benefits/costs when deciding whether or not to implement a digester. While these indirect costs/benefits are important, they should be included in any study that compares biogas digester with alternative cooking methods. And these costs/benefits are discussed in the next sections.

6.5.5 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province Many have noted that the LCOE analysis of biogas digester is sensitive to the assumptions of input variables, and for this reason it is important to perform a sensitivity analysis (Darling et al, 2011; Velosa, 2010; SunPower Corporation, 2008; Branker et al., 2011). In this section, RREAD is used to perform a number of sensitivity analyses by testing several important variables, to examine how they affect the overall cost of household biogas digesters in Guizhou province. Variables such as advances in technologies, the development of renewable energy markets and the implementation of new policies can have significant impacts on the use of off-grid bioenergy systems. For example, more feedstock input can considerably improve biogas yield of a digester. Reduced construction and labor cost due to the development of a larger market can reduce the costs of using the system. Altering existing government policies (tax, financial, energy, environmental and other

191 relevant policies) or implementing new policies can also increase the cost- effectiveness of the household biogas system relative to other conventional cooking methods. With RREAD, by varying these variables, it can be determined how important each variable is, and in what extent the levelized cost of biogas varies with these changes. A number of variables have been suggested for sensitivity analysis when analyzing biogas technology, including availability of feedstock, biogas yields, economic lifetime of the technology, price of feedstock, the discount rate, the capital cost, the cost of operational and maintenance, government policies, etc. (ISAT, 2000; Garcia, 2011; Diyoke et al., 2014; SEAI, 2017; Cuellar, 2009; Khan et al., 2014). In this study, four variables are selected, namely: (1) varying biogas yields; (2) varying maintenance cost; (3) varying discount rate and (4) varying government subsidy. Biogas yield in the Guizhou case analysis is based on the county government estimation of crop yields and the size of animal heads in each county. Considering some counties’ data could miss the particular types of crops or animals, and other counties’ data may not up to date, it is possible that variations could be observed relative to the base case. Likewise the biogas yields can vary depending on a number of other factors such as temperature, the ratio of crop residues and animal manures, etc. Therefore, for the sensitivity analysis a 10% high and 10% low biogas yield scenario is analyzed (Liu & Yu, 2009; Zhou et al., 2012; Xiong et al., 2011). Furthermore, the cost of maintenance is a key consideration that has been reported in the literature on the economics of household biogas digesters (Ministry of Agriculture, 2007; Liu & Yu, 2009; Peng, 2009; Hao & Shen, 2006). Biogas digesters require regular maintenance to have good performance for biogas production. Skilled

192 technicians are required to perform the maintenance such as feeding and discharging the slurry (Garcia, 2011; Xia, 2013). For that reason, the normal cost of maintenance can go higher if local technicians are short staffed and outside technicians are called in for maintenance or malfunction of the digester. Likewise the maintenance cost can vary depending on the exact labor being used. If demand for labor on maintenance increases, the cost may also increase. Studies have shown maintenance cost for a typical 8m3 household biogas digester in China can range from 50 CNY ($8)/year to 125 CNY ($18)/year (Hao et al., 2015; Wang & Zhang, 2013; Kuang et al., 2011; Xia, 2013; Huang, 2010; Fei et al., 2011). For this respect, it is considered an annual maintenance cost of 50 CNY ($8) and 125 CNY ($18) for the sensitivity analysis here. A third variable worth considering is the discount rate. This study assumes a 2.9% discount rate for the economic analysis of household biogas digester. Since this discount rate is the average real discount rate in China regardless of project’s type, it is highly important to differentiate the discount rates according to the types of renewable technologies. For this purpose, a sensitivity analysis carried out for rates of 5% and 1%. This is because for assessment models of renewable energy projects, a discount rate of 5% has been used in several past studies (Liu et al., 2011; Wang & Zhang, 2013; Oxera, 2011; Riahi et al., 2013; Ondraczek et al., 2015). The lower discount rate of 1% is analyzed since several studies argued that for long-term problems with larger risks of irreversible events, a lower discount should be included in the economic cost analysis for renewable technologies (Admiraal et al., 2016; Stern, 2006; Weitzman, 2006; Markandya, 1998). Government subsidies have raised recently and studies have noted that they can heavily influence the competitiveness of household biogas digesters in China (Li

193 et al., 2014; Wang & Zhang, 2013; Peng, 2007; Lin, 2009; Ding & Zheng, 2013; Chou et al., 2013; Tian et al., 2011). Thus it is worth considering the subsidy variation in the economic analysis of biogas digester. Sensitivity analysis is carried out for the subsidy levels at 1,200 CNY ($176)/household and 3,500 CNY ($515)/household comparing to the based case of 2,600 CNY ($382)/household received in Guizhou. This is because the existing literature on subsidies for rural biogas digester across the provinces and counties in China has shown they usually fall into this range (New Energy, 2017; Xia, 2013; Wang & Zhang, 2013; CNWest, 2014). The reason that there is a large variation in subsidies is because digester subsides in China varies based on location. As a result, subsidies from central government for provinces in western China could be double the subsides for provinces in eastern China. The Figure and Table below show the results. It is observed that the LCOE is most sensitive to subsidy level since its line is the steepest. If the current subsidy level in Guizhou reduced to 1,200 CNY per household – the lowest existing level in China so far, then its LCOE will increase by 33% to $0.32/m3. By contrast, when subsidy level reaches 3,500 CNY per household, the LCOE will reduce by 25% to $0.18/m3. This shows the increase of subsidy level is likely to influence biogas economics, but the influence will favorable for the user. The variations of maintenance cost and biogas yields can also significantly impact the cost of using the biogas digester. The results indicate that with a 25 CNY/year increase of maintenance, the LCOE of the digester could potential increase by $0.01/m3. In the case of biogas yields, the LCOE will increase by 8.3% to $0.26/m3 if the biogas production decreased by 10%. However, the LCOE remains unchanged when the biogas production is increased. This is because the calculation in

194 this study is based on the consumption perspective, which means the energy value used in the simulation equals to the user’s annual energy requirement instead of the system’s net production. Regarding the discount rate, either decrease or increase the discount rate has small impacts on the LCOE. Therefore, for future biogas developers or potential users, this parameter could be regarded with modest risk among other variables during the investment decision.

0.33

0.31 Biogas yields

0.29 Maitenance cost Discount rate 0.27 Subsidy level 0.25 Base Case 0.23 Biogas yields =

LCOE ($/kWh) 292m3/year/househ 0.21 old Miantenance cost = 0.19 100 CNY/year Discount rate = 0.17 2.9% Subbsidy level = 0.15 2,600 CNY/household LCOE = $0.24/m3 Value Reative to the Base Case

Figure 6.9 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province.

Table 6.18 Sensitivity Analysis of Household Biogas Digesters in Guizhou Province.

Variables Base case Variation LCOE LCOE ($/m3) ($/m3) After Base case variations

195 Biogas yields 292 m3 +10% 0.24 -10% 0.24 0.26 Maintenance 100 CNY/year -50 CNY/year 0.21 cost ($14.7) (-$7) +25 CNY/year 0.24 0.25 (+4$) Discount rate 2.9% +2.1% 0.26 -1.9% 0.24 0.22 Subsidy level 2,600 -1,400 CNY/household 0.32 CNY/household (-$206) ($382) +900 CNY/household 0.24 0.18 (+$132)

6.5.6 Study Comparison with Previous CEEP Work Many studies have been done in the area of providing cooking services by using household biogas digester systems. For example, CEEP has previously examined the health-ecological-energy-economic impacts of integrated agricultural biodigetser system for rural areas of China (Byrne et al., 2004). Table 6.17 compares the economic performance of household biogas digester analyzed in this dissertation and in CEEP’s previous work. Study regions in the previous work include Liaoning and Yunnan, which are bigger provinces than Guizhou in terms of population size and agricultural production. Additionally, unlike the only individual biogas digester system examined in this dissertation, systems analyzed in previous work are integrated systems which are known as “4-in-1” and “3-in-1” systems. In addition, energy mix in Guizhou province now is more diverse than in previous two provinces of 10 year ago – more people are using modern fuels for cooking now. With technology development, daily biogas yield has been largely increased now. By contrast, the cost of biogas digester only (not including other components such as greenhouse or latrine) has been increased. The cost of a biogas digester is assumed at 4,120 CNY in this study compared to 1,500 CNY in Liaoning and 1,125

196 CNY in Yunnan in previous CEEP work. This is because construction of biogas digester is very labor-intensive and now labor cost has been increased significantly than 10 years ago. Economically, CEEP work shows integrated biodigester systems have much shorter payback periods than conventional systems. Similarly, this dissertation also shows that the levelized cost of biogas digester is only 30% to 70% to the cost of conventional cooking methods. This result is very significant, because it shows that even provinces like Guizhou that has less substantial biomass resources than provinces in previous CEEP work can still consider household biogas digester systems as comparative options.

Table 6.19 Study Comparison between Previous CEEP Work and this Dissertation.

Byrne et al., 2004 Zhu, 2017 Liaoning Yunnan Guizhou Profile of the Case Study Regions Population 42.03 million 43.33 million 34.75 million Rural population 23.15 million 34.90 million 22.99 million Rural households 6.86 million 8.45 million 6.52 million Main agricultural Grain, oil-bearing Grain, oil-bearing Rice, wheat, corn, products plants, beetroots, plants, tobacco, tobacco, potato fruits, hogs hogs, fruits Energy Mix Coal for cooking 5.3% 78% 34.7% Fuelwood for 92.3% 21.7% 45.4% cooking Modern fuels 2.5% 2.5% 19.1% Biogas Digester Digester size 8m3 6m3 8m3 Type of digester “4 in 1” system “3 in 1” system Biodigester biodigester + pig pigs + plat + house + latrine + biodigester greenhouse Biogas production 1.5m3 1m3 0.8 – 2.27m3 per day

197 Cost of biogas Biodigester: 1,500 Biodigester: 1,125 Biogas digester: digester system CNY CNY 4,120 CNY Other components: Other components: 25,610 CNY 3,60 CNY (greenhouse costs 25,000 CNY) O&M For biodigester: 136 For biodigester: 102 100 CNY/year CNY CNY 500 CNY every 5 For other: 9,132 For other: 2,806 years CNY CNY Subsidy Up to 6,539 CNY Up to 1,150 per Up to 2,600 CNY per household household per household Discount rate 6% 6% 2.9% Evaluation period 15 years 15 years 10 years Financial analysis Payback period: 2 Payback period: 3 LCOE: $0.24/m3 results years years v.s. v.s. v.s. LPG LCOE: Conventional Conventional $0.69/m3 system payback system payback Traditional coal years: 4 years years: 11 years stove: $0.41/m3 Advanced coal stove: $0.33/m3

6.6 Social Analysis of Household Biogas Digesters in Guizhou Province

6.6.1 Reduces Expenditure on Fuels In addition to economic benefits, there are a number of social benefits associated with using biogas as a cooking fuel. The most commonly quoted social benefit of biogas used as a substitute fuel for cooking is that it reduces rural household expenditure on fuels. In a survey tried to assess the quantity of fuel used before and after the installation of biogas digester in Danzhai County, Guizhou, all the respondents agreed that biogas produced is sufficient to meet their cooking requirements thus they don’t have to pay for the alternative fuels (Dong & Zheng, 2012).

198 In the case of LPG-based cooking, using biogas for cooking saves a typical rural household in Guizhou about 9 cylinders of LPG per year, and that equals to 900CNY ($132) a year. Considering the increased price of imported fuel will also directly increase that of LPG, which will in turn increase the cost burden on customers. In the case of coal-based cooking, using biogas as substitute can save a household’s fuel expenditures range from 676 CNY ($100) to 526 CNY ($78) depending on the types of coal cook stoves are used. The rural household’s expenditure on energy is not singled out in the official statistics, but comes under the category of “household facilities and articles” (Xia, 2013). According to the latest data available, the per capita expenditure on energy of rural households in Guizhou is about 379.8 CNY ($56) a year (National Bureau of Statistics, 2016; National Academy of Development and Strategy, 2016). And this accounts for 1,340 CNY ($197) annually per rural household in Guizhou (the average number of people per rural household in Guizhou is 3.53). In this sense, if LPG and coal are substituted by biogas as the cooking fuel, then more than half of household’s expenditure on energy will be saved.

6.6.2 Reduces Time Spent on Collecting Fuels for Cooking Although rely on traditional energy sources such as firewood for cooking is not expensive, such cooking method is very time-consuming. Past studies have clear indications of time saved by biogas as a substitute cooking fuel. For example, Singh and Maharjan evaluated the time impacts from biogas digester in Nepal and found that this technology saves time in cooking and fuel collection therefore gives people chances to participate in the income generating actives (Siegel & Rahamn, 2011). Gwavuya et al. observed that by investing in a biogas digester, households in Ethiopia could save quite a lot of time compared with their previous cooking methods (Gwavuy

199 et al., 2012). And a World Bank paper examining 2,7000 households in five provinces showed that biogas digester can reduce fuel collection time significantly particularly to women (World Bank, 2012). The time taken for cooking a meal is also considered as an important factor that influences people’s choice of cooking fuel. Numerous evidences have shown that biogas digesters can save people time on cooking, mostly women and children’s time. This is not only because turning on a biogas digester is much easier and faster than starting an fire on the woods or coal, but it is also because biogas has higher heat efficiency. In addition, people report that they spend less time on cleaning kitchen and utensils after cooking. This is because unlike coal or biomass, biogas is clean. 98% of the digester users who interviewed in the World Bank’s study reported biogas saved them time in cooking (World Bank, 2012). And in another study on in rural Shaanxi, women interviewed in the study said that cooking a meal now takes only 0.5 hour, compared to over 2 hours with traditional fuels (Shaanxi Mothers Environmental Protection Volunteer Association, 2009). It is found that a household biogas digester can save an average of 1 – 3 hours per day in time for fuel wood collection in addition to reduce the time in cooking (World Bank, 2012; FAO, 2014; Garfi et al., 2012). Suppose average household in Guizhou province cooks 5 days a week, then biogas-based cooking can save the household ranging from 260 to 780 hours per year. The time spent on collecting fuels and preparing for cooking has a significant “opportunity cost”, because the household members can utilize the saved time for income generating activities such as livestock raising, home gardening, grocery, and growing cash crops like tobacco and tea. At an opportunity cost with fuel wood of 3.14 CNY/hour/person in rural China, the benefits

200 can amount to 2,881CNY ($424) – 8,645 CNY ($1,271) for each rural household in Guizhou (Feng et al., 2009).

6.6.3 Improves Gender Equity Given the cultural roles of men and women in the communities, women and girls are more likely responsible for fuel wood collection and cooking. The average fuel load is around 20kg and the travel distance for fuel collection can be up to 12km (WLPGA, 2014). And in some areas, women have to spend 40% of their waking time on collecting fuel or in cooking (Dutta et al., 2017). Collection time limits the opportunity for women and children to improve their education and to participate in income-generating activities. Many children, especially girls have to drop out from school in order to help the household activities. Thus, as a modern energy service, biogas provides not only an efficient way of cooking, but it also promotes gender equity for children and girls. With saved time, women and girls now can go to school and participate in income-generating activities, social works, etc. In addition, women now have more time to care for their children, or spend time with friends and relatives. In China, it is estimated that 80% of women and children in biogas digester households used their saved time for income-generating activities, which accounts for up to 24% of monthly household income (Ho, 2005). In Indonesia, women adopting biogas digester expressed that they have the desire to become entrepreneurs and gain economic independence to some degree (WOCAN, 2015). And in Nepal, a study found that women and girls’ access to education increased noticeably as a result of a biogas digester program (The Ashden Awards for Sustainable Energy, 2005).

201 6.6.4 Provides Valuable Byproducts (Fertilizer) During the anaerobic fermentation process, not only biogas is produced but also some byproducts such as liquid bio-slurry and sedimentary sludge. Both bio- slurry and sludge are valuable fertilizers that are rich in nutrients, minerals, and biologically active compounds. Unlike chemical fertilizers that are harmful to the soil, water quality and global climate change, bio-slurry and sludge are organic matter so they don’t damage the environment. Moreover, now the pries of chemical fertilizers are rising and many rural household members can't afford the fertilizers since the prices are increasing at a higher rate than the household’s income is increasing (Warnars & Oppenoorth, 2014). In this sense, avoiding using high price and contaminant chemical fertilizers by using bio-slurry and sludge can increase the income level of a rural household. Numerous studies have been conducted on the economic value of bio-slurry and sludge as fertilizers. For example, in China, according to Liang et al., a typical fixed dome 8m3 household biogas digester could produce 12,000 kg of digested bio-slurry and sludge per year at a value of 300 CNY ($44) (Liang et al., 2011). Similarly, in Xiyang township in Gansu province, a typical 8m3 household biogas digester could produce 20,000kg of bio-slurry and 8,000kg of sludge per household per year (Ding et al., 2012). If sold as fertilizers to the market, they can create about a value of 231.57 CNY ($35) for a household in the township per year (Ding et al., 2012). Consider that the annual cost spent on energy for an average rural household in Guizhou is about 1,340 CNY ($197), if digested bioslurry is sold to the market, it can save the household’s energy cost about 20% (National Bureau of Statistics, 2016; National Academy of Development and Strategy, 2016). In addition, outside China, in Pakistan, an average family can save over $50 per year by replacing chemical fertilizers with bio-slurry (Muhmood et al., 2014).

202 Utilized as fertilizers, digested bio-slurry and sludge can improve overall soil conditions and crop yields. For example, field experiments carried in China showed that application of digested bio-slurry increased the rice, barley, and rice yields by 44.3%, 79.8% and 31% respectively (Lam & Heegde, 2011). In Tongren County in Guizhou Province, researchers have found bio-slurry can increase annual corn yields by 16.9% in the area (Guo et al., 2005). Outside China, in Thai Nguyen province in Vietnam, farmers applied bio-slurry to their tea, and tea production increased 66.8kg/ha in summer and 44kg/ha in winter (Thu, 2015). Moreover, use of bio-slurry results in higher tea prices than tea with chemical fertilizers – $0.03/kg higher in the summer and $0.2/kg higher in the winter (Thu, 2015). As a combined effect of savings on fertilizer and increased tea price, the total income generation effect of using bio- slurry in tea production in Thai Nguyen province is about $6,371 per hector per year (Thu, 2015). Similarly in Tanzania, famers can increase their crop revenues with an average of 25% by actively using bio-slurry as a fertilizer (Warnars, 2012). At such, household biogas digesters can provide great social benefits to rural households in Guizhou. These benefits include reducing the household’s expenditures on fuels, reducing household members’ time spent on collecting fuels and cooking particularly to women and girls, and increasing household members’ activities for income-generating and social network. In addition, the digested byproducts have significant economic values thus can improve household income level. Thus, it is a more viable cooking solution compared to other alternative cooking methods.

203 6.7 Environmental Analysis of Household Biogas Digesters in Guizhou Province

6.7.1 Reduces Indoor Air Pollution Burning coal or firewood for cooking creates a lot of smoke and particular matter. In Guizhou province today, still 80% of the rural households rely on traditional fuels for cooking, with 35% and 45%, respectively, using coal or biomass as their main fuel (National Bureau of Statistics, 2011). Studies have been conducted on the indoor air pollutants from cooking in rural homes in Guizhou province. In general, wood burning has the highest concentration of particular matters (PM2.5 and PM10) and CO followed by coal combustion. For example, high PM2.5 and PM10 concentrations in Guizhou were observed in Zhang et al.’s study, and the values were 220 μg /m3 and 260 μg /m3 from wood burning, and 110 μg and 180 μg from coal combustion, respectively (Zhang, 2014). Similarly, Wang et al. monitored PM10 and PM2.5 concentration at households in Guizhou from different cooking fuels. They observed that firewood-based cooking caused the most serious indoor air pollution with the highest concentration of PM10 and PM2.5 of 218 - 418 μg/m3 and 201 - 304 μg/m3 (Wang et al., 2010). Though 30% lower than the firewood, coal-based cooking also resulted in high concentrations of PM2.5 and PM10 (Wang et al., 2010). In a more recent study that investigates indoor concentration of particular matters and CO for 179 rural homes in Guizhou, researchers have found the highest air pollution levels were found among users who use wood fire for cooking (Alnes et al., 2014). And these households far exceeded the PM10 Chinese indoor air pollution standard (Alnes, et al., 2014). In contrast, biogas is a clean fuel compared to biomass or coal combustion. The use of biogas for cooking would reduce smoke exposure in the indoor

204 environment when burning coal or raw biomass. An increasing number of epidemiological studies are linking use of biogas with improved indoor air pollution and emerging evidences suggest that burning biogas also improves health conditions such as diminished respiratory infections of women and children, improved infant mortality rates, reduced eye infections and reduced dental and skeleton fluorosis. In terms of indoor air pollutions, biogas is the cleanest fuel of all (Wang et al., 2010). Compared to firewood and coal, biogas combustion has almost no effects on pollution levels of particulate matters (PM10 and PM2.5), and its pollution levels are similar to indoor non-combustion case (Wang, et al., 2010). For volatile organic compounds levels, combustions of coals and woods cause high concentrations of VOC species; biogas combustion, on the other hand, has little influences on VOC (Wang et al., 2010). As a result, biogas is the cleanest fuel and it is worth being promoted in Guizhou province and other more areas.

Table 6.20 Pollutants for Various Types of Fuels Burned at Households in Guizhou Province.

Firewood Coal Biogas PM10 218 – 418 μg/m3 220 – 225 μg/m3 104 ± 11.57 μg/m3 (= indoor case of non-combustion) PM2.5 201 – 304 μg/m3 170 – 200 μg/m3 89 ± 6.57 μg/m3 (= indoor case of non-combustion) CO 10.8 ± 0.8 mg/m3 14.5 ± 3.7 mg/m3 NA Volatile organic 466.7 ± 337.9 170 – 700 μg/m3 34 ± 19.4 μg/m3 compounds (VOCs) μg/m3 Source: Wang et al., 2010.

205 6.7.2 Improves Health Conditions Indoor air pollutants from solid fuels burned in households cause severe health risks. Some of the health impacts linked with indoor air pollutants including respiratory diseases, respiratory infections and dental and skeletal fluorosis. According to World Health Organization, over 4 million people die prematurely from illness attributable to household air pollution from cooking with solid fuels (WHO, 2016). And in China, more than 420,000 premature deaths occurred annually due to indoor air pollution, which is 40% more than the 300,000 premature deaths due to the outdoor air pollution in Chinese cities with populations of more than 100,000 (Zhang & Smith, 2007). And most of the pollution is due to inefficient combustion of fuels for cooking. In China, a study in Anhui province shows women living in homes with coal burning have higher chances of getting chest illness, cough, and shortness of breath (Pope & Xu, 1993). Another survey study of 5,051 students of Wuhan, China found that coal burning for cooking increased the risk of wheezing with colds (Salo et al., 2004). Also correlations between coal burning and lung cancer and diseases have been found in numerous studies conducted in China. For example, in a study in Shanxi province of China, researchers found women utilizing coal for cooking had lower lung function values than those using gas for cooking (Wang et al., 2004). The most common diseases from indoor air pollution in Guizhou are dental and skeletal fluorosis. In Guizhou province alone, It is estimated that over the past couple of years, there were more than 10 million dental fluorosis patients and 640,000 skeletal fluorosis patients attributed to the use of fluoride-rich coal as an indoor fuel source for cooking (Wilson Center, 2006; Zhang & Smith, 2005). Because children are more likely to be diagnosed with skeleton fluorosis than adults, in Guizhou and surrounding areas, almost all elementary and junior high school students had dental

206 fluorosis and osteosclerosis (Qin et al., 2009; Ando et al., 1998; Watanabe et al., 1997). Therefore efforts to reduce fluorosis exposure to children in areas where coal is burned as cooking fuel at home are urgently needed. In the past, the government of Guizhou has tried hard to reduce levels of dental and skeletal fluorosis in the province. The major efforts include converting open-fire stoves into closed stoves with an addition of a chimney. However, recent studies have shown that this type of stove only achieves a minor reduction in fluoride exposure, still households in Guizhou suffer from high exposure of indoor air pollution and adverse effects of overexposing to fluoride from coal combustion as cooking fuel (Qin et al., 2009). By contrast, an increasing number of studies realize that new fuel sources would have a greater impact on indoor air pollutant levels and people’s health, and studies have showed correlations between utilization of biogas and reduction of dental and skeletal fluorosis in Guizhou. There are large health benefits from upgrading cooking fuels to biogas in rural areas in Guizhou province and in other provinces. In a case study of dental fluorosis in school age children living in four counties in Guizhou, researchers found Baiyun district has the lowest rate of dental fluorosis (45.45%) among all (Sun et al., 2003). This is due to the reduction of coal burning for cooking in the households because the local government has been investing and promoting biogas digester in the region since 1991 (Sun et al., 2003). And in recent years, promoting biogas digester has been the key strategy for the government of Guizhou province to combat endemic fluorosis in the region (Guizhou Center for Disease Control and Prevention, 2010). Outside China, in Kenya for instance, most women reported improved respiratory health and improved children’s health since biogas digester installation (Dohoo et al., 2012). And

207 in Odisha, India, researchers have found in addition to reduction of firewood use and indoor air pollution, biogas stove reduces household members’ time and money spent in the hospital for respiratory infections (Lewis et al., 2017).

6.7.3 Improves Sanitation The most obvious sanitary benefit of a biogas digester can offer is that it can improve toilets in rural China. In rural Guizhou and other places, there is no former toilet or sewer system at home. Unlike the flush toilet that is in use in the urban areas, it is common that people from rural Guizhou use the pit toilets. This type of toilet generally has no roof, but only mud bricks around a pit. The slurry in the pit often moves with insects larvae, and in all cases the toilets are smelly and dirty. Because of this reason, toilets are usually built outdoors and they are cold in winter and full of maggots in the summer. It is neither convenient nor sanitary. And this already becomes a public health issue in rural China and around the world. According to World Toilet Organization, 60% of all rural diseases are caused by hygiene and sanitation condition (WTO, 2011). By comparison, when installing a biogas digester at home, slurries of the toilet could be automatically fed into digester tanks. The anaerobic digestion process is very effective at killing a wide range of pathogens. In this way, toilets are odorless and fly- less, and they are as clean as the one that are connected to sewer systems. In addition, because toilet slurries need to be fed into the digester tank, they will be built near the household, often adjacent to the kitchen. And this makes they are more convenient to people especially during wintertime. In a similar way, biogas digesters also function well on animal wastes. At present, animal wastes from livestock are commonly left untreated either in animal

208 pens or just on ground in rural China. When the untreated animal wastes are discharged into river and lakes, major pollutions occur as well as water-borne infectious diseases. By collecting animal wastes for inputs of biogas digesters, this greatly reduces ground and seawater pollution after rainfall that would otherwise wash the wastes into rivers, lakes or the sea. In this sense, biogas digesters can provide a better sanitation for rural households in Guizhou province and in China. For example, in villages along the Yangtze River Basin, toilet renovation with connected to the biogas digester has been proved to be an effective measure in sanitizing human and animal wastes, reducing the incidence of schistosomiasis, fluorosis and swine streptococcosis epidemics in the region (UNDP, 2011). And in Ziyang County of Sichuan province, during the 2005 outbreak of human streptococcus suis, no biogas-using households were affected (Zheng, 2005).

6.7.4 Reduces Greenhouse Gas Emissions and Deforestation The environmental impact, especially impact on climate change, is probably not a direct factor in the choice of cooking fuel for a rural household, however, it is certainly an important one for any government who wants to promote clean cooking technologies. As a modern fuel for cooking, biogas digester eases environmental pressure of greenhouse gas emission and fuelwood collection. Studies have reported that adaptation of biogas digester is a very efficient way to mitigate global greenhouse gas (GHG) emissions. The below table lists GHG emission factors by types of fuel, and biogas is estimated to be much lower than other cooking fuels such as fuelwood, LPG and coal (Bhattacharya et al., 2002; Bhattacharya et al., 2005; Zhang, 2000). It is estimated that, on average, rural households in China consume around 1,000kg of coal

209 and 190kg of biomass for cooking per year (Liao et al., 2017). By adopting biogas digesters, quantity of firewood and coal consumed for cooking reduces, which leads to a further reduction of deforestration and greenhouse gas emissions. It is found that, a typical Chinese fixed dome 8m3 biogas digester can reduce greenhouse gas emissions by 1.517 to 2 tons of CO2 per year compared to coal combustion (Hao & Shen, 2006; Liu et al., 2006). Considering today there are still 2.25 million rural households in Guizhou province still rely on coal for cooking, if biogas is used as substituted cooking fuel in those households, this can save around 3.53 to 4.5 million tons of CO2 per year in the province (National Bureau of Statistics, 2011).

Table 6.21 GHG Emission Factors by Fuels.

CO2 (g/kg) CH4 (g/kg) N2O (g/TJ) Biogas 748 0.023 Straw 1,130 4.56 4 Fuelwood 1,450 2.7 4.83 Coal 2,280 2.92 1.4 Refined oil 3,130 0.0248 4.18 LPG 3,075 0.137 1.88 Natural gas 117,500 kg/TJ 1.24 kg/TJ 1.84 Source: Bhattacharya et al., 2002; Bhattacharya et al., 2005; Zhang et al., 2000.

Beyond cooking, if biogas is substituted with other energy sources consumed in the household, greater GHG reduction will be achieved. The below table presents the study by Yu et al., which is an overview of greenhouse gas emission mitigation (in CO2 equivalent) from energy substitution with biogas in China from 1991 to 2005 (Yu et al., 2008). During the period, if all types of energy sources used in rural China (straw, fuelwood, coal, electricity, LPG, refined oil, natural gas and coal gas) are

210 substituted by biogas, the total gross emission reduction from biogas utilization are 88,064.03 Gg CO2-eq (Yu et al., 2008). The GHG emission reduction from coal is the largest one due to its high emission factor and high quantity of consumption. Besides the energy substitution effect shown in the table, Yu et al. also measure the emission reduction from better manure management with biogas digester, and the total reductions are 21,468.81 Gg CO2-eq during the period (Yu et al., 2008). Adding together emission reductions from biogas substitution and manure management, but subtracting GHG emitted from burning biogas (36,372.43 Gg CO2-eq), they arrive at a sum of net GHG emission reduction of 73,160 Gg of CO2-eq from 1990 to 2005 by the employment of biogas digesters (Yu et al., 2008). And this equals to an average of a 5,077 Gg of CO2-eq net mitigation in rural China per year.

Table 6.22 GHG Emission Reduction by Energy Substitution of Biogas in Rural China, 1991 – 2005 (Gg CO2-eq).

Year Straw Fuelwoo Coal Electrici LPG Refined Natural Coal Total d ty oil gas gas 1991 650.46 497.7 845.08 418.15 13.49 36.57 0.66 0.28 2462.39 1992 675.46 516.83 877.57 434.22 14.01 37.98 0.69 0.29 2557.04 1993 692.12 529.57 899.2 446.45 14.35 38.91 0.71 0.30 2621.61 1994 787.81 602.79 1023.53 500.64 16.34 44.29 0.8 0.34 2976.54 1995 861.76 659.38 1119.6 543.83 17.87 48.45 0.88 0.37 3252.14 1996 1014.75 752.72 1137.46 696.27 9.43 35.51 0.66 0.62 3647.43 1997 1039.55 795.41 1350.59 669.5 21.56 58.45 1.06 0.44 3936.57 1998 1182.66 867.64 1496.58 808.00 23.56 55.41 0.99 0.52 4435.36 1999 1408.99 941.51 1650.38 880.48 31.54 77.98 0.92 0.62 4992.42 2000 1529.99 1068.71 1944.86 1217.89 35.8 83.52 1.69 0.60 5883.06 2001 1665.79 1332.46 2336.36 1013.56 35.99 147.96 2.38 0.75 6535.25 2002 2041.76 1764.45 3023.63 1005.06 45.93 109.13 2.92 0.59 7993.47 2003 2509.28 2191.63 3579.64 1515.67 68.34 157.82 2.86 0.88 10026.1 2004 3256.94 2492.04 423.42 2098.62 67.54 183.12 3.32 1.39 12334.4 2005 3801.97 2909.08 4939.55 2461.54 78.84 213.77 3.88 1.62 14410.3 Total 23119.3 17921.9 30455.5 14709.9 494.58 1328.87 24.42 9.59 88064.0 Source: Yu et al., 2008.

211 Beside GHG emission reductions, studies also show that biogas digesters are helpful in reducing deforestation in several ways (Ali et al., 2013). When a biogas digester is implemented, biogas produced is substituted with firewood in the household, which has a positive impact on forest, environment and ecosystem. In addition, during the fermentation process, the digested slurries used as fertilizers can improve the soil quality, giving better crop yields and thereby reduce the need for new agricultural land which also has a positive impact on deforestation (Bajgain & Shakya, 2005). According to Hao & Shen, a typical Chinese fixed-dome 8m3 biogas digester can save up to 1.5 tons of fuelwood per year (Hao & Shen, 2006). Considering today there are still 2.97 million rural households in Guizhou province still rely on firewood for cooking, if biogas is used as substituted cooking fuel in those households, this can save around 4.455 million tons of firewood per year in the province (National Bureau of Statistics, 2011).

6.8 Potential Challenges Facing Household Biogas Digester Development in Guizhou Province The above sustainability analysis has clearly showed that household biogas digester is a viable solution to provide cooking services for rural households in Guizhou in a sustainable manner. However, the analysis also shows that biogas development in Guizhou still faces a variety of challenges.

6.8.1 Lagged Development From the above analysis, it is clear that both Chinese central government and local governments have made great efforts to facilitate the development of biogas digesters in rural areas, however, unlike PV adoption, biogas development in rural China has been slow and many biogas systems are left idle. Many reasons are

212 accountable to this phenomenon. First, building a household biogas digester is way more complicated than building a solar home system at home. To construct a digester, it requires various materials and extensive labors. Unlike solar PV systems that are familiar technology to rural households, biogas digesters are still something new to them. Considering the complexity of building the digester and lack of knowledge about the technology, rural households often feel reluctant to adopt one at home. Second, biogas digester systems require extensive maintenance. Unlike solar home systems, once installed, they require very minimum maintenances; biogas digesters require regular small maintenance that occurs every year and major maintenance that occurs every five years. Maintenances of biogas digester include feeding and discharging the slurries and they are usually performed by professional workers. Historically, many rural households have treated biogas digesters as self- maintenance systems. But in reality, if the biogas tank is filled up with slurries and the slurries are not discharged in time, the digester won’t be able to produce biogas and will be treated as “broken”. Additionally, rural households need to pay for the professional maintenance services, and in recent years, maintenance costs have increased due to shortage of labor and they become a burden for many rural households. Without adequate maintenance, many biogas digesters are left idle or abundant after a few years of operation. Third, cultural awareness is also a major reason for the slow development of biogas digesters. Considering the cultural roles of women and men in the communities, women and girls are more likely to be responsible for the cooking at home. In Guizhou, people that stay in the rural areas are elderly men and women with their kids. By contrast, young men nowadays are leaving their hometown and moving

213 to the capital city or more developed cities for opportunities of earning money. Because men don’t cook, they don’t know the negative impacts of traditional cooking fuels such as fuel wood and coal on women. Additionally, since men are the main economic sources, they usually have the decision power when making a decision at home such as buying a household biogas digester. Therefore, even women know how significantly a biogas digester can improve their lives, it won’t be adopted unless their husbands are agreed.

6.8.2 Energy Challenge Although the energy analysis shows that a typical 8m3 biogas digester is sufficient in providing cooking energy for households in the 56 potential counties, still, the digester’s energy performance could be influenced by many factors. The availability of crop residues and animal manures, ground temperature, digester efficiency, etc. can potentially increase or lower the available biogas produced from the digester. The sensitivity analysis has also demonstrated that biogas yield can significantly impact the cost of using the system. If the available biogas produced from the system is decreased, some potential biogas counties will no longer be able to provide the sufficient cooking energy for their households. Thus energy shortfall occurs. In addition, the LCOE will be increased accordingly, which means the system users’ financial burden will be increased. The less biogas production will decrease the affordability of biogas users in the near term and further prevents biogas development in Guizhou in the long run. However this provides the opportunity that if biogas technology advancement achieved in future, greater development of biogas will be likely achieved in Guizhou.

214 6.8.3 Financing Challenge Financing methods are usually used to reduce the cost of renewable technologies and to make them affordable options for rural households. Depending on the circumstances, financing can come in the forms of loans, mortgage, third party financing or the government subsidies of either installation-based (a direct reduction of capital costs) or performance-based (subsidies based on energy produced). Today in Guizhou province, the main financing method for household biogas digester is direct subsidies from national, provincial and county levels. All together, rural household in Guizhou now could receive a total of 2,600 CNY ($382) for adopting a biogas digester at their homes, which is about 63% of the system’s initial capital cost. The sensitivity analysis shows that the biogas digester is most sensitive to subsidy level, which means increase or decrease the amount of available subsidy will influence the development of biogas digester in the province significantly. If the current subsidy level in Guizhou reduced to 1,200 CNY per household – the lowest existing level in China so far, then its LCOE will increase by 33% to $0.32/m3. As a result, to further develop the biogas technology in Guizhou, biogas policy makers need make sure subsidy is available in the province and to make sure that subsidy is allocated on time. However, in fact, there are many uncertainties exist for subsidies to biogas digester in both Guizhou and China. From the national level, it is not clear how long the subsidy from the central government will be available. And from provincial level, it is also uncertain if the subsidy from Guizhou government will be increased or decreased in future. These uncertainties will inevitably affect the sustainable development of biogas technology in Guizhou in the long term. In addition, the current subsidy is an installation-based subsidy that allocated based on the approved biogas digester of each household. Once approved, the subsidy

215 will be given to the household. Whether the installed digesters work well or not will not affect the eligibility of the subsidy. In this sense, many households don’t care about how digesters work. As a result, some digesters have not constructed or left unused after subsidy is allocated. In other cases, many households wish to install the digester at home just for the sake of receiving subsidies from the national and local governments. The anticipation of the governmental subsidies may disincentivise some households from investing in biogas digester at their own costs. And this further puts a strain on the scaling-up of biogas development in the province. Furthermore, biogas digesters now are mainly cash-sold in Guizhou today. Except for the direct subsidies from the governments, no other financing options available for households who want to adopt a system at home. Although the existing subsidies have helped reducing the digester’s initial cost substantially, still, households need to pay for the rest. In this case, some poorer households are excluded from acquiring the system unless greater subsides are provided. And in future, if subsidy level is reduced in the province, more potential buyers will be excluded. Studies have noted that diversifying financing options, such as access to loan, fee-for- services, etc. in addition to subsidy could improve the affordability of rural renewable emery system buyers. However, none of these methods have been practiced in Guizhou so far. This is either because of lack of institutional support or lack of the financing environment. In future, if greater biogas development want to be achieved in Guizhou, this area should not be missed.

6.8.4 Maintenance Challenge Unlike solar home system that requires minimum maintenances, household biogas digester needs frequent services to make sure the system have a good

216 performance for biogas production. The major maintenance of a biogas digester requires feeding and discharging that is usually performed by the professional technicians. Therefore, biogas users have to pay for the services. For a typical household biogas digester in China, the cost of regular maintenance including feeding and discharging the slurry is around 100 CNY ($15) per year (Hao & Shen, 2006). And for the major repair and maintenance that occurs every 5 year, the cost is around 500 CNY ($74) (Hao & Shen, 2006). Past studies have reported that maintenance is a key consideration for the economic analysis of household biogas digester (Liu & Yu, 2009; Wang, 1999; Peng, 2009; Hao & Shen, 2006). And the sensitivity analysis has shown the maintenance cost can significantly influence the digester’s LCOE. With a 25 CNY/year increase of maintenance, the LCOE of the digester could potential increase by $0.01/m3. Since labor costs are increasing rapidly in recent years in rural China, it is very likely the maintenance cost of biogas digester will increase in the near future. Since the increase of maintenance cost is associated with increase cost of using the system, as a result, the quality of the maintenance services is affected. In fact, the lack of adequate maintenance has been recognized as the major challenge to the adequate use of biogas digesters in many rural areas of China. The inadequate feeding and discharging of digesters result in a lower rate of digester utilization rate. For example, the normal utilization rates of household biogas digester in Guizhou province are between 37% and 69% across various villages due to lack of maintenances (Ding & Zheng, 2013). Thus, measures ensuring proper maintenance services for the households should be adopted.

217 6.8.5 Awareness Challenge In additional to economic benefits, social and environmental analysis of household biogas digester have shown the system is able to provide non-economic benefits to the rural households in Guizhou. These non-economic benefits include reduced time on collecting fuels, improved gender equity, reduced indoor air pollution, better health conditions and improved sanitations. However, in reality, biogas users are far more concerned with economic than non-economic benefits when deciding whether or not to invest in a household biogas digester at home. This requires the renewable energy users’ full acknowledgment of both economic and non- economic benefits that renewable resources possess. Therefore, the ignorance of the non-economic benefits of biogas raises issues of adequate education and training which in future should be paid with attentions.

6.8.6 Policy Challenge Although, biogas technology has been demonstrated to offer a cost-effective source of energy for rural cooking in Guizhou, its long-term sustainability has to be relied on the supporting national and provincial policies. Today, renewable energy has been integrated into China’s overall national energy development plan. Especially in recent years, decentralized renewable technologies, such as distributed solar and household biogas digester has been recognized as strategic options for energy provision in a sustainable way. During the 13th Five-Year Plan period, China intends to carry out the “Energy Transformation Demonstration Project” by encouraging biogas digester for cooking and heating in rural China. At the provincial level, biogas development has not been integrated into Guizhou’s overall energy plan yet. In this sense, biogas is not regarded as the priority

218 in the province that will in the long-term hurt its sustainable development. Although subsidies are available for digester users from both provincial and county levels, these policies are not provided with a time frame. In other words, people are afraid that if governments tend to cut or lower the subsides in future. If this happens, poorer households will be excluded from purchasing the system due to the increased cost of using the system. In addition, some rural households argue that they are not paid with the subsidies on time. And they express that to pay the subsidies in a timely manner has become a key consideration when they decide to invest in a household biogas digester.

6.9 Conclusion of Household Biogas Digesters in Guizhou Province The sustainability analysis of household biogas digester in this chapter shows that this system provides a cost-effective source of cooking fuel for rural households who are still rely on the solid biomass for cooking. An important aspect to highlight here is that a typical Chinese fix-domed 8m3 digester is sufficient in providing daily cooking needs for rural households in 56 counties in Guizhou. One of the main benefits of biogas digester is its LCOE is 65% cheaper than LPG-based cooking, and 30% to 45% cheaper than coal-based cooking. Additionally, the biogas digester has social benefits such as it saves household’s annual expenditure on energy by more than 50%, and it saves an average 1 -3 hours per day in time for cooking compared to traditional methods of cooking. Furthermore, using biogas digester for cooking reduces indoor PM10 and PM2.5 by more than 50% than firewood and biomass for cooking in Guizhou. And it has additional environmental benefits including improving health and sanitation conditions, reducing greenhouse gas emissions and protecting forests.

219 Though the household biogas digester is attractive in terms of its economic, social and environmental benefits, there may be constraints such as uncertainty of biogas yields, rising cost of maintenance, lack of financing options, lack of public awareness of non-economic benefits of biogas, and uncertainty of political environment. In the final chapter, policy options for stimulating development of household biogas digester in Guizhou province will be discussed.

220 Chapter 7

BUILDING AN INTEGRATED RENEWABLE ENERGY SYSTEM IN GUIZHOU PROVINCE

The access to electricity and clean cooking facilities are the two key parameters for the magnitude of energy poverty. Like other developing area in the world, Guizhou province of China is highly dependent on solid fuels for cooking, and still large amount of population lack access to electricity or stable electrical services. The previous two chapters examine the potential of solar and biogas energies in Guizhou and they have clearly proved that solar home systems and household biogas digesters are cost-effective ways to improve rural household’s modern energy access through the provision of effective lighting and clean cooking. In addition, those systems bring enormous social and environmental benefits to Guizhou’s rural sustainable development. Since solar and biogas technologies can only meet household’s electricity and cooking demands separately, the next step is to figure out a way that household’s various energy needs could be met at the same time. In fact, an integrated configuration of these two technologies combined can accomplish this task (Rahman et al., 2014; Kanase-Patil & Saini, 2010). Quite a lot of past studies have been conduced on the individual applications of solar home system and household biogas digester, but none of them have examined the performance of an integrated configuration of these two renewable resources. Therefore, this chapter proposes building an integrated system configuration that incorporates solar and biogas to sever both cooking and electricity needs of the rural households. In addition, this chapter

221 performs a techno-economic evaluation of this integrated system to see how the system can meet household’s electricity and cooking demands simultaneously in the context of rural Guizhou.

7.1 Overview of Integrated Renewable Energy Systems Integrated or hybrid energy systems are becoming popular in recent years as they represent an efficient way of handling different energy sources. The implementation of such energy systems can optimize energy supply particularly in remote rural areas where modern energy access is limited. An integrated or hybrid renewable system usually consists one or more renewable energy sources and one or more conventional energy sources or even without conventional energy sources to provide multiple energy services as well as greater balance in energy supply (Fhamy et al., 2014; Abdullah et al., 2017; Kham & Martin, 2015). The system usually incorporates different energy resources that can complement each other (Gonzalez et al., 2015). The most frequently used integrated/hybrid systems in rural areas include wind and PV system, PV and diesel generator, wind and diesel generator, and wind, PV and diesel generator (Borges Neto, 2010). Such systems need storage capacity to manage the intermittent renewable energy resources, thus integrated systems usually include batteries. Although there are also combinations of other sources such as biogas, small hydro, etc., such configurations are paid with fewer attentions and they are identified as minors. Until very recently, solar-biogas systems have started to gain attentions as a viable solution for rural households to meet their cooking and electricity needs at the same time (Borges Neto, 2010; Kumaravel & Ashok, 2012; Eziyi & Krothapalli, 2014). There is a growing body of literature on how solar-biogas systems are efficient

222 at utilizing solar and biogas resources at the same time for promoting the rural sustainable development. For example, Borges Neto et al. (2010) modeled a PV- biogas system for a rural community of the northeast region of Brazil, and pointed out that this type of system is capable to improve the household income level in the region. Similarly, Mizanur Rahman et al. (2014) examined the techno-economic performance of an integrated system combining of solar and biogas, and they concluded that household in rural Bangladesh can achieve savings more than the cost of installing the system. In addition, Gonzalez-Gonzalez et al. (2014) have designed an integrated system of biogas and solar for a pig slaughterhouse in Bdajz, Spain, they demonstrated that this system is a solution to both the energy supply problem and environmental problem of waste biomass (Gonzalez-Gonzalez et al., 2014). There is always confusion between hybrid and integrated energy systems. From technical perspective, these two systems are similar: both two types of systems incorporate two or more energy resources in order to provide a more flexible and reliable supply of energy. However, integrated systems possess additional values from sustainability perspective. Such systems not only show a combination of technologies, but also quantities and qualitative benefits that a system might have. This study proposes building an integrated solar-biomass system in Guizhou province. Therefore, this system will not only be reviewed from technical aspect, but its economic and non- economic benefits will also be analyzed.

7.2 Solar-Biogas Integrated System Architecture in Guizhou Province This chapter proposes an integrated system configuration that incorporates solar and biogas to sever both cooking and electricity needs of the rural households in Guizhou province. The motivations are: first, this integrated system can solve rural

223 households’ electricity and cooking needs at the same time; and second, this system could be compared to the stand-alone solar PV and biogas digester that analyzed in the previous chapters in terms of its economic, social and environmental performances. Obviously, the proposed integrated system is made up with two parts: one with a solar home system and the other with a household biogas digester system. However, it must be noted that just by putting these two different energy systems together is not enough to implement an integrated solar-biogas renewable energy system. The implementation of an integrated system must depend on the nature of the energy sources, the nature of electric charge, and how the produced energy flows to meet the household’s energy requirements. Bearing these in mind, the components of the proposed integrated system include a PV module, a controller (as part of the PV array), a converter, a battery, a biogas digester and a gas engine connected to the digester so that extra biogas could be converted to electricity. Solar electricity produced from the PV module is DC power. The converter converts the DC power into AC, to be used by the loads. Batteries are used to store energy produced during times of resource availability and then supply the excess energy to electrical loads as needed such as during the nights. To protect the batteries from being over-charged and to keep it from being over-discharged, a battery charge controllers is used to reduce or stop the charging current when the battery reach its charge or discharge limits. The cooking energy demand is supplied by the combustion of biogas. Biogas is produced from the digester which is fed with crop residues and animal manures. Although the energy demand for cooking could be also supplied by electricity, considering the resource and facility availability, cooking demand will be only met by biogas in this study. Unlike the individual biogas digester discussed in Chapter 6, in this integrated

224 system, the digester is connected to a gas engine thus the extra biogas can fuel the engine to generate electricity. In this way, electricity from both the gas engine and PV module can be applied to the household’s loads. The schematic diagram of this proposed solar-biogas integrated system in Guizhou is shown as below. In Figure 7.1, the green cells represent the energy resources, while the red colored cells represent the loads. The blue cells represent the electricity storage, and the white cells represent all the components in the proposed integrated energy system. The arrows represent the flows of energy. Thus, in this proposed system, the input energy resources will follow different routes to the use of produced energy. Also the produced energy can be used in different ways according to household’s energy demands thus giving the system flexibility.

PV module with AC/DC Solar Electrical loads insolation controller converter

Battery

Manure Biogas digester Gas engine Crop residues

Cooking loads

225 Figure 7.1 Schematic Diagram of Solar-Biogas Integrated Systems.

7.3 Technical Specification of Solar-Biogas Integrated Systems in Guizhou Province There are two sub-systems within the solar-biogas integrated system, one is a solar home system and the other is a biogas digester gas engine system. For a better comparison, the configurations of these two systems are remaining the same as ones of the stand-alone systems.

7.3.1 Solar Home System The solar home system in the proposed integrated system is the same as one talked about in the Chapter 5. It comprises a PV module, a rechargeable battery, a charge controller and an inverter. The solar PV module is installed on the rooftop or other open places that are exposed to the sunlight, while the remaining components are kept inside the house. The battery stores solar electricity and meets demand whenever a shortage occurs. And the inverter converts DC power into AC, to be used by the loads. As discussed in the Chapter 5, to meet the rural household’s daily electricity needs in Guizhou province, a 520W PV module is needed. The battery chosen for this study is of 12V, 111.11 Ah, and 6 sets are needed. And the sizes for inverter and controller are 600W.

Table 7.1 Technical Specifications of Solar Home System in the Solar-Biogas Integrated System in Guizhou Province.

Required PV module 520W Type of PV module Polycrystalline Manufacturer Trina Solar

226 Module areas 3.3 m2 Module efficiency 15% Module lifetime 15 years Battery type Lead-acid Battery Voltage 12V Battery efficiency 75% Required battery capacity 1,111.11 Ah Numbers of battery required 6 Battery lifetime 4 years Charge controller size 600W Charge controller lifetime 10 years Inverter size 600W Inverter efficiency 90% Inverter lifetime 10 years

7.3.2 Biogas Digester Gas Engine System Unlike the stand-alone household biogas digester discussed in the Chapter 6, the biogas digester sub-system in an integrated energy system consists of two components – a typical stand-alone household biogas digester for producing biogas and a biogas engine for converting the extra biogas into electricity. For the biogas digester, it is a typical Chinese fixed dome household biogas plant. The size of the digester is 8m3, which is enough to meet a typical rural household’s cooking demand in Guizhou province. The digester is fed with crop residues and animal manures. During the digestion phase, the digester produces biogas and slurry. The digested slurry could be used as bio-fertilizer to increase the productivity of crops and thus to increase the income level of the rural household. Through the biogas pipe, the produced biogas is connected to the stove and a gas engine. In this way, the biogas could be used as a direct cooking fuel or an indirect fuel to generate electricity. A biogas engine is similar to a conventional diesel engine. It is connected to the digester’s gas tank through the biogas pipe and converts biogas into electricity.

227 The rated power of the biogas engine should be equal to the household’s loads, thus in this study, a 600 W biogas engine is needed.

Table 7.2 Technical Specifications of Biogas Digester Gas Engine System in the Solar-Biogas Integrated System in Guizhou Province.

Biogas digester type Fixed dome Lifetime 10 years Digester size 8m3 Feedstock Crop residues and animal manures Biogas engine 600 W Engine type AC Engine lifetime 10 years

7.4 Market Potential and Energy Performance of Solar-Biogas Integrated Systems in Guizhou Province

7.4.1 Market Potential of Solar-Biogas Integrated Systems in Guizhou Province Chapter 5 and 6 analyze the energy performances of a 520W solar home system with battery storage and an 8m3 household biogas digester in each counties of Guizhou province. As a result, 42 counties are considered as potential markets to develop solar home system (annual solar hours > 1,250 hours) and they can produce annual solar electricity ranging from 525.7 kWh to 647 kWh per household. And 56 counties are considered as potential markets to develop household biogas digester (daily modified gas production > 0.8m3 per household), and their annual gas production range from 292m3 to 990m3 per household. In this chapter, the potential markets to develop an integrated system are identified from these potential solar and biogas counties. The steps of identifying the counties are shown in the Figure 7.2. First, the 42 potential solar home system

228 counties and the 56 potential household biogas digester counties are categorized into 3 categories respectively in terms of their annual energy production from high to low. Second, the potential solar counties and the biogas counties from the same category are matched to see if there are same counties fall into the same category. Finally, if there are counties successfully matched, then these counties are considered as the candidate counties in this study for promoting solar-biogas integrated system in the regions. The reasons for categorizing and matching the renewable energy potential counties are: first, the matched counties show the capability to meet households’ electricity and cooking demands at the same time; and second, since matched counties are from different categories, it will be able to compare the cost-effectiveness of the system under different energy potential scenarios.

229

Figure 7.2 Steps for Identifying the Candidate Counties for Integrated Solar-Biogas Systems in Guizhou Province.

It should be noted that the selected 9 counties don’t mean they are the representatives for developing integrated systems in Guizhou province. The logic behind the selection is to set ranges for analyzing the energy performance and sustainability performance of integrated systems. Since selected counties are from different categories of renewable energy output potential from high to low, this will enable us to see from which category that integrated systems will have the best

230 performances. Or in other words, this will enable us to compare the cost-effectiveness of integrated systems under different energy potential scenarios.

7.4.2 Energy Performance of Solar-Biogas Integrated Systems in Guizhou Province The table below lists the successful matched counties and their energy production from the integrated system of solar electricity and biogas respectively (calculations are done in Chapter 5 and 6). In total, there are 9 counties could be considered as candidates to develop an integrated system, and they are Anlong, Ziyun, Liuzhi, Liupanshui, Sinan, Yingjiang, Dushan, Libo, and Jiangkou. These 9 counties fall into 3 categories based on their renewable energy production from high to low. In other words, counties from category I have the highest solar electricity and biogas production from the system, followed by counties from category II and III. Due to the moderate solar insolation in Guizhou province, though solar home system can meet majority of the household’s electrical load requirement for the 9 counties, still some portion of the loads need to be met by other means. And category I has the fewest unmet loads followed by the category II and III. By contrast, because Guizhou province has abundant biomass resources (crop residues and animal manures), biogas produced from the digester could not only meet household’s cooking demand but the extra could be used elsewhere for other purposes. Counties from category I have the highest excess biogas produced (the excess biogas produced equals to annual total biogas produced minus annual biogas demand for cooking), while ones from category III have the lowest amount of extra biogas. Since all those 9 candidate counties have excess biogas produced that could be used other than cooking, then under the

231 integrated system scenario, these excess biogas could be converted into electricity via the gas engine to meet the unmet electrical loads.

Table 7:3 Renewable Energy Production from the Candidate Solar-Biogas Integrated System Counties in Guizhou Province.

Integrate Counties Electricity Unmet Biogas Excess d system production loads generatio biogas by solar (kWh/year n by (m3/year part ) biogas ) (kWh/year part ) (m3/year) Categor 520W PV Anlong 617 40 494 202 y I + Ziyun 566 91 785 493 8m3 Liuzhi 565 92 522 230 Digester Categor 520W PV Liupanshu 561 96 392 100 y II + i 8m3 Sinan 550 107 442 150 Digester Yingjiang 543 114 398 106 Categor 520W PV Dushan 539 118 390 98 y III + Libo 530 127 353 61 8m3 Jiangkou 527 130 379 87 Digester

Under the solar-biogas integrated system scenario, the biogas digester can complement the solar home system by converting the excess biogas into electricity. This shows the significance of implementing an integrated system in Guizhou – it can not only meet households’ cooking and electricity demands at the same time, but can also fill the energy gap exists from the stand-alone renewable energy system. It is estimated that 1m3 of biogas could be converted to around 1.7kWh of electricity, when all energy losses happened in the conversion process are considered (Dimpl,

232 2010). Therefore, the amount of electricity produced from the excess biogas in the 9 matched counties could be obtained based on this conversion factor. Biogas generated from the digester will first meet the cooking needs of the households (292m3/year/household), and then the excess production will be converted to electricity to meet the unmet electrical loads. Therefore, the adjusted electricity production will be from two parts: one is from solar home system and the other is from biogas digester. The table below lists the adjusted energy production for the 9 candidate counties. Now 8 counties are able to fill their electricity load gaps from electricity converted from the biogas digester. In addition, those counties now have extra electricity produced (the extra electricity produced equals to annual electricity production from solar home system and digester system minus annual household electricity demand) that could be used elsewhere. Counties from category I have the highest adjusted electricity produced thus the most extra electricity, followed by ones from category II and III. Libo is the only county that still has electrical loads unmet even after receiving the converted electricity from the excess biogas produced. However it should be noted that now the electricity gap in Libo has been substantially reduced. From this point of view, an integrated solar-biogas system is effective in providing energy services to rural households in Guizhou province – 8 out of 9 cadidate counties now can fully meet their household’s basic energy needs for electricity and cooking. In addition, those counties now have extra electricity that could be for other purposes. The integrated system is most efficient in category I, counties within this category will have the largest amount of excess electricity to be used for purposes other than the basic lighting and cooking which will bring their households with greater economic, social and environmental benefits.

233 Table 7.4 Adjusted Renewable Energy Production from the Candidate Solar-Biogas Integrated System Counties in Guizhou Province.

Integrated Counties Electricity Extra Biogas System generation electricity generation for (kWh/year) cooking (m3/year) 520W PV Anlong PV: 617 303 292 + 8m3 Digester: 343 Category I digester Ziyun PV: 566 747 292 Digester: 838 Liuzhi PV: 565 299 292 Digester: 391 520W PV Liupanshui PV: 561 74 292 + 8m3 Digester: 170 Category digester Sinan PV: 550 148 292 II Digester: 255 Yingjiang PV: 543 66 292 Digester: 180 520W PV Dushan PV: 539 48 292 + 8m3 Digester: 166 Category digester Libo PV: 530 -23 292 III Digester: 104 Jiangkou PV: 527 18 292 Digester: 148

7.5 Economic Analysis of Solar-Biogas Integrated Energy Systems in Guizhou Province

7.5.1 Preparation of Cost Stream The economic analysis of integrated solar-biogas systems mainly focuses on the unit cost of electricity produced from the system. Similar to the economic analysis of individual solar and biogas systems, RREAD is again used as the main tool for this economic analysis. To evaluate the economic performance of the system, several cost parameters need to be determined. In addition to cost parameters considered in Chapter 5 and 6,

234 the cost of biogas engine should also be included. This is because in an integrated system, a biogas engine is an extra part that added to the system in order to convert the extra biogas produced into electricity. A biogas engine is similar to the diesel engine, so the price of a small biogas engine is about the same as the diesel engine discussed in previous chapter. The engine is good for 10 years, and the annual maintenance cost is about $15. The table below lists the parameters considered for the cost analysis of the system. Along with those parameters are some economic information such as discount rate, evaluation period and currency conversion rate. For a better comparison with the stand-alone renewable energy system, these financial terms remain the same as ones discussed in the previous chapters.

Table 7.5 Cost Parameters for Solar-Biogas Integrated Systems.

Solar Components Total module costs 2,080 CNY ($306) Module lifetime 15 years Total battery cost 900 CNY ($132.4) Battery lifetime 4 years Charge controller cost (CNY/controller) 200 CNY ($29.4) Charge controller lifetime 10 years Inverter cost (CNY/inverter) 630 CNY ($92.6) Inverter lifetime 10 years Annual operation and maintenance 40 CNY ($5.9) Biogas Components Biogas digester costs (after subsidies) 1,520 CNY ($224) Digester lifetime 10 years Biogas engine cost 1,650 CNY ($243) Engine lifetime 10 years Annual operation and maintenance 100 CNY ($15) Other Basic Economic Information Discount rate (%) 2.9 Evaluation period (year) 10 Currency conversion rate (CNY/US$) 6.8

235 7.5.2 Estimation of Net Present Value (NPV) and Levelized Energy Costs (LCOE) Once the cost stream is prepared, the costs are discounted in order to calculate the net present values over the evaluation period. RREAD is used to discount each of the future costs to their present values in the 10-year period. Once the yearly discounted future costs are determined, RREAD sums up all values to arrive at a total NPV costs. The total net present value costs could be standardized over its evaluation years which is called the levelized annual NPV cost. In this study, the levelized annual NPV cost refers to the yearly constant cash payment should be made for an integrated solar-biogas system over the evaluation time. Again, RREAD is utilized to calculate the levelized NPV cost of the system. The levelized costs of electricity and biogas in the 9 candidate counties are shown in the below table. Also the able lists their LCOEs from stand-alone renewable energy systems calculated in Chapter 5 and 6 for a clearer cost comparison. The levelized costs of biogas are the same regardless of which system is applied, since all the assuming cost parameters to calculate the biogas from both systems keep the same. By contrast, the levelized costs of electricity are different from the integrated systems to individual solar PV systems, since the analysis now takes into account the costs from PV system and biogas engine, as well as electricity produced from solar and biogas.

Table 7.6 Levelized Energy Costs (LCOE) Comparison.

Counties LCOE LCOE LCOE LCOE (electricity) (electricity) (biogas) (biogas) integrated, individual, integrated, individual, $/kWh $/kWh $/m3 $/m3 Anlong 0.12 0.14 0.24 0.24

236 Category I Ziyun 0.08 0.15 0.24 0.24 Liuzhi 0.12 0.15 0.24 0.24 Liupanshui 0.16 0.16 0.24 0.24 Category II Sinan 0.14 0.16 0.24 0.24 Yingjiang 0.16 0.16 0.24 0.24 Dushan 0.16 0.16 0.24 0.24 Category III Libo 0.18 0.16 0.24 0.24 Jiangkou 0.17 0.17 0.24 0.24

From the supply perspective, counties in category I have the lowest levelized cost of electricity. This is because solar and biogas resources are the most abundant in this category, thus the counties have highest level of electricity produced from both resources. As a result, the three counties, Anlong, Ziyun, and Liushui now have much lower levelized cost of electricity from the integrated system than from the stand-alone solar home system. For example, the levelized cost of electricity in Ziyun county is $0.08/kWh compared to $0.15/kWh from the single solar PV system. For counties in category II and III, most of them have the calculated levelized costs of electricity as the same or slightly lower than from the single solar PV system. Libo county is the only exception, this is mainly because its electricity produced from solar and biogas is the lowest among all candidate counties. From cost perspective view, the levelized cost of electricity don’t seem to have huge difference between the integrated and the single renewable systems in category II and III, however it should be noted that under the integrated scenario, those counties’ unmet electricity is now filled up. In addition, the counties now have extra produced electricity to be used for purposes other than basic lighting, TV, radio, etc. In other words, the households are now able to enjoy greater electrical services that can maximize their living standards. Since the electricity produced from biogas engine is not an intermittent resource like solar energy, which means, in the future analysis,

237 number and size of battery (used in the solar PV system) considered in this cost analysis could be reduced. This will in turn reduce the levelized cost of electricity from the integrated system, and will make the integrated system more cost-effective in Guizhou province.

7.6 Non-economic Benefits of Solar-Biogas Integrated Energy Systems in Guizhou Province In addition to economic benefits discussed in the previous section, integrated solar-biogas systems also have non-economic benefits that individual systems could not match. First, unlike individual renewable energy systems that can only provide electricity or cooking fuels once a time, integrated systems can provide these two types of modern energy services simultaneously to rural households who are still lacking them – providing rural household with greater convenience and flexibility. Second, integrated renewable energy systems are more reliable and stable since biogas digester may offset the variations in solar home systems’ output mutually. Solar resource is intermittent, thus PV systems may not be productive during the rainy days or during the night. Since biogas digester is not limited by sunlight, when extra biogas is produced, it could be converted to electricity by the biogas engine. Third, an integrated solar-biogas system is designed to maximize the use of solar and biogas, resulting in a system with better efficiency. For example, the 9 identified counties in the previous sections have electricity gaps if only individual solar home systems are adopted. Since extra biogas produced can be converted to electricity by the gas engine with an integrated solar-biogas system, the gaps could be filled. As a result, 8 of 9 counties will not have electricity gaps if an integrated system is implemented, and additionally, they now have extra electricity that rural households could use to

238 improve their living standards. Forth, integrated systems require smaller battery banks. It is possible for the integrated systems to operate with smaller energy storage than for the stand-alone PV system designed for the same application, since some portion of electricity generation could be come from biogas digester. Batteries are also subject to a less aggressive charge/discharge cycle, increasing their service life. And this will also decrease the overall economics of using systems since battery is a major cost parameter considered when calculating the levelized cost of electricity. Additionally, integrated solar-biogas systems can take full advantages of social and environmental benefits of individual renewable technologies. For example, households with an integrated system can have the highest fuel cost reduction since both electricity and cooking fuels are provided by renewable technologies at the same time. In addition, households with integrated systems can also have the largest emission reduction since more energy is produced from renewables.

Table 7.7 Non-Economic Benefits of Solar-Biogas Integrated Energy Systems and Individual Renewable Energy Systems.

Integrated Solar- Individual Solar Individual Biogas System Home System Household Biogas Digester System Flexibility Most flexible, can Only provide Only provide provide electricity electricity cooking fuels + cooking fuels at the same time Reliability Most reliable Unreliable, may not Reliable be productive during the day and night Efficiency Most efficient Not efficient, Note efficient, supply can not waste of energy meet the load occurs

239 demand occurs Battery bank Smaller size Large size No requirement

Social benefits Combined social Solar home systems Household biogas benefits from related social digester systems individual benefits related social renewable benefits technologies Environmental Combined Solar home systems Household biogas benefits environmental related digester systems benefits from environmental related individual benefits environmental renewable benefits technologies

7.7 Conclusion of Solar-Biogas integrated Energy Systems in Guizhou Province Based on the above calculations, it can be seen that the integrated solar-biogas energy system is suggested as a feasible energy system in Guizhou province. The configuration of the system includes a 520W solar home system and a typical Chinese fixed dome 8m3 biogas digester. In addition, the system adds a biogas engine so that extra biogas produced could be converted into electricity. Nine counties are selected as the candidates to develop an integrated system in their regions. These counties are fallen into 3 categories based on their energy performances from renewable resources. It has been seen that the proposed integrated system is quite efficient in terms of providing energy services for rural households in the selected counties. If implemented, the integrated system will be able to fill the households’ electricity gaps that are unable to be met by the single renewable systems. The integrated system is the most energy efficient in the category I – it provides households in these counties with extra energy that could be used for purposes other than the basic energy requirements.

240 Based on the cost analysis, it can be seen the integrated system is economic viable. With an integrated system, now electricity costs less than it is from a single solar PV. The integrated system is the most cost-effective in category I counties, where the levelized cost of electricity in those counties are 15% to 40% lower than from the single solar PVs. Though electricity costs in category II and III counties don’t have much difference between the systems, it should be noted that their energy gaps are being filled up by the integrated system. In addition, unlike solar which is an intermittent energy that is only momentary accessible, biogas produced can be stored in the biogas tank until it needs to be used. In this way, a solar-biogas integrated system is able to overcome the intermittence problem that occurred in a single solar PV system. In this sense, in the future research, the configuration of an integrated system presented in this study could be optimized with only smaller size or less quantity of battery needed. And this shows the potential of integrated systems to further reduce the cost paid by the users in Guizhou province. In sum, the techno-economic analysis of the proposed integrated energy system identifies that Guizhou province is a potential candidate for the use of solar and biogas together for energy provision. The system configurations consist of 520W solar home system and 8m3 biogas digester can potentially serve the household’s cooking and electrical loads with extra electricity produced to be used elsewhere. This result is impressive because still large amount of households in Guizhou don’t have access to stable electrical services nor they have clean cooking facilities. In addition, the levelized cost of electricity from the proposed integrated system is lower, which means that households do not incur extra costs if they shift from traditional renewable to new technologies, while they will enjoy the improved services.

241 Chapter 8

CONCLUSIONS, RECOMMENDATIONS, AND SUGGESTIONS FOR FUTURE WORKS

8.1 Conclusions Access to modern energy is the key to a county’s development and prosperity. Especially in a developing country, access to reliable and affordable electricity and clean cooking facilities are fundamental to improving health and reducing poverty, enhancing productivity and promoting economic growth (IEA, 2016). Therefore, the two basic modern energy services – electricity and clean cooking facilities, must be ensured for the population who still lack them. Over the past two decades, China has provided hundreds of millions of rural people with access to these two modern energy services. Despite the accomplishments, still many people in China have no access to electricity, and more than 1/3 of China’s population relies on solid fuels for cooking (NEA, 2016; IEA, 2016). Finding appropriate ways to provide modern energy services to these communities has been a key issue for Chinese government. This dissertation is the first of its kind that uses an integrated approach to examine off-grid renewable energy options for modern energy access in the context of rural China. It is a case study of Guizhou province of China and it performs (1) a resource potential analysis to understand solar and biomass resource availability in Guizhou province; (2) an energy performance analysis to understand how off-grid renewable energy options perform daily, monthly and yearly and how they meet electricity and cooking needs for rural communities in Guizhou; and (3) a

242 sustainability analysis of off-grid renewable energy options in terms of their economic and non-economic impacts on rural households. The following is a summary of the major conclusions of this dissertation:  The resource evaluation shows that Guizhou province has adequate renewable energy resources to develop off-grid renewable energy systems in the province. Of 88 counties in Guizhou, 42 counties have solar potential to develop solar home systems, 56 counties have biomass potential to develop household biogas digester systems, and 9 counties are identified with the potential to develop integrated solar-biogas systems.  The energy performance analyses show that off-grid renewable energy systems can help rural households in Guizhou to meet their electricity and cooking needs. Solar electricity supply from individual solar home system is sufficient for rural households with basic appliances. And biogas supply from individual biogas digester is significant in Guizhou. Additionally, solar and biogas can be complementary in the province, so a more stable annual electricity supply can be obtained through integrated solar-biogas systems, resulting in more productive uses of electricity in rural Guizhou.  Detailed levelized cost analyses of comparable technologies reveal that off- grid renewable energy systems are more economical than typical traditional energy systems available to rural community in Guizhou province. Results of solar home systems show their levelized costs of electricity are at $0.13 – 0.17/kWh, which is about 75% cheaper than serving the electrical loads demand for the households with diesel generator. Results also show that the levelized cost of biogas from households biogas digester system is at

243 $0.24/m3, which is only 1/3 of the cost of LPG-based cooking and ½ of coal- based cooking methods that are widely used in Guizhou. In addition, results show that the levelized cost of integrated solar-home systems is most cost- effective in Guizhou – the 9 identified potential counties have LCOEs (electricity) ranging from $0.08/kWh to $0.18/kWh, which fall well below the costs from the individual solar home system (the only exception is Libo county).  The social and environmental performance analyses show that off-grid renewable energy systems could bring substantial non-economic benefits to Guizhou rural households. Utilization of solar home systems and biogas digester systems can reduce households’ expenditures on fuels, increasing households’ income level and productivities, improving gender equity, improving rural households’ health conditions and sanitations, and reducing greenhouse gas emissions and deforestation. Integrated systems can have additional benefits such as they are more flexible, reliable and energy efficient than the individual systems, and they require smaller battery banks. Additionally, integrated systems can have combined social and environmental benefits of individual technologies. In this sense, off-grid renewable energy options do not only provide modern energy services to rural households in a cost-effective manner, they also maximize households’ social and environmental welfare. They can help rural counties to become more ecological societies.  The result of this dissertation is quite encouraging: it shows that even for provinces like Guizhou – which have less substantial solar and biomass

244 potential than provinces analyzed in the original CEEP works and in other existing studies, can still consider off-grid rural renewables as competitive options to address rural energy needs. This also shows the necessarily for local focus on off-grid renewable energy systems. Past studies of renewable energy development have been mainly focused on major solar provinces such as Inner Mongolia and Xinjiang and major agricultural provinces such as Yunnan and Hunan, and inevitably these provinces have great potentials to develop renewables. However, provinces or regions such as Guizhou province that have less renewable resources are always excluded from discussion because it is assumed that these places won’t be good. This study shows that these provinces could be still considered as potential regions to develop renewables if looking deep into their energy resource situation locally. Therefore, for any future studies that focus on local renewable development, it should always be open-minded and look at all possibilities. Undoubtedly, modern energy access is now and will remain an essential element for rural development in Guizhou as well as in China. Adoption of effective policies will be required to promote renewable energy development and realize a sustainable future in Guizhou, in China as well as in other countries in the developing world.

8.2 Policy Recommendations for Off-grid Renewable Energy Systems Development To take full advantage of identified economic, social and environmental benefits of off-grid renewable energy technologies in this dissertation, policy options and recommendations are needed. However, no single policy or recommendation is

245 going to make a sustainable rural development happen. Partnership is the key to accelerate the development of off-grid renewable energy in rural China. As illustrated in Figure 8.1, policy options offered here include (1) building an institutional framework; (2) increasing support for renewable energy R&D; (3) investing in renewable energy; (4) accessing to financial options; (5) improving renewable energy services and (6) strengthening cooperation. When these policies come together, development of off-grid renewable energy can be accelerated in a sustainable manner that maximize economic-social-environmental benefits.

Figure 8.1 Key Policy Options for Off-grid Renewable Energy Development in Guizhou Province.

8.2.1 Building An Institutional Framework Guizhou province needs to build an effective institutional framework to promote off-grid renewable energy development in the province, especially in rural

246 areas where household’s basic energy needs could not be met effectively. Off-grid renewable energy options should be integrated into Guizhou government’s overall development plan. Off-grid renewable technologies should be considered as important methods to provide rural households with modern energy services in a sustainable manner. To improve institutional framework for rural renewable energy development in Guizhou, institutional structure reforms are needed. Proposed changes include: (1) the creation of an advisory and coordinating body for renewable energy in Guizhou such as Guizhou Renewable Energy Commission. The Commission will be responsible for the province’s renewable energy development and supervision in general, and it can coordinate major renewable energy issues and all other matters concerning Guizhou’s renewable energy policy. (2) The expansion of existing Guizhou Energy Administration to include county-level offices and to organize renewable energy service providers at county and township levels. Additionally, local governments should make efforts to build a stronger infrastructure for renewable energy development in their own areas. Efforts include: (1) adoption of county specific off-grid renewable energy policies and goals to increase the use of renewable energy in each county; (2) implementation of tracking and verification systems to ensure that renewable energy policies and goals are achieved; (3) cooperation between provincial and county governments to facilitate the development of renewable technologies on both local and provincial levels; (4) collaboration with local research agents to identify local renewable energy opportunities and (5) organization of public campaigns and educational sessions to popularize renewable energy technologies.

247 8.2.2 Increasing Support for Renewable Energy R&D Particular for solar technology, research and development (R&D) is the backbone to reduce the costs and improve the reliability of off renewable energy technologies. Sensitivity analysis has clearly shown that off-grid renewable energy options, especially solar PV systems are quite sensitive to their costs. If solar PV module unit cost is reduced by 50% of its current level, its LCOE will decrease by 25% accordingly. Since technology provides opportunities for cost reduction, R&D is essential to renewable technologies’ competitive advantage. China has not yet has a national institution that is dedicated to off-grid renewable energy research and related activities. To meet the needs of renewable energy development and to scale up their development, efforts should be made to strengthen both national and provincial R&D. These efforts include (1) establishment of national, provincial and county-level renewable energy research and innovation centers for enhancing the core technology of renewable industry; (2) establishment of a public technology R&D information exchange platform at local level, providing public resources for renewable energy development, providing technical supports and addressing technical problems for local rural renewable energy users, (3) increase of R&D research in domestic solar PV modules and storage technologies to identify the materials that have the highest efficiency but with the lowest cost; (4) subsidy of R&D activities in renewable energy sector in the forms of direct funding, performance- based subsidy, etc.; and (5) creation of special renewable R&D funds from both national and provincial government, such as Special Fund for Solar Generation, Special Fund for Household Biogas Digester, etc. and increase of the current spending on R&D in renewable technologies.

248 8.2.3 Investing in Renewable Energy Development of renewable energy requires increased investment. Although investments for off-grid renewable energy technologies have grown significantly in recent years, they are far from sufficient to reach modern energy access goals in Guizhou and in China. Therefore, China could consider incentive policies to attract investment in renewable energy sector, especially the early investment. These policies include: (1) investment tax credits to renewable manufacturers and developers; (2) tax exemptions or reductions on the revenue earned by manufacturers and developers; (3) tax credits or rebates for renewable energy system buyers. Additionally, China should consider investments from a broader range of sources that include private sector, public or private funds, bilateral and multilateral funding agencies and so on. Particularly, the role of private sector is vital to bring investment for renewable energy development. Therefore, efforts should be made to attract private sector involvement, including: (1) strengthening policies and regulations such as favorable tariff and incentives, providing helps for licenses and permits, etc. to attract private sector investments and to encourage the participation of local enterprises; (2) developing niche markets for private sectors; (3) engaging with experts to conduct renewable market research and conducting workshops for entrepreneurs/investors to identify off-grid renewable opportunities; and (4) engaging with public/private sector stakeholders to encourage adoption of standardized methods in renewable markets.

8.2.4 Accessing to Financial Options Accelerating off-grid renewables in rural China will require improved access to financing options for renewable energy buyers. Currently the only available

249 financing options for off-grid renewables in China are FIT for solar home systems and direct incentives for household biogas digester systems. Drawbacks have been identified with these two options. In terms of the national FIT of 0.42 CNY/kWh for solar home systems, it is argued that this amount is not enough to cover the cost of solar home systems. Additionally, since cost remains a big obstacle for poorer households who want to adopt a system at home, this performance-based subsidy couldn’t solve this problem. In terms of incentives for biogas digester systems, because the incentives are installation-based, some households will feel less incentive to take care of the system once they get their systems installed. Thus, efforts should be made to improve the effectiveness of these current financing options. They include: (1) provision of additional FIT at provincial level for solar home systems to complement the national FIT; (2) provision of installation-based subsidy or rebates for first time solar home system buyers; (3) provision of performance-based subsidy (e.g., FIT) for biogas users; (4) provision of cash rewards if off-grid renewable energy users’ actual usage of renewable energy reaches certain levels; (5) establishment of an oversight board to make sure that subsides are allocated timely and appropriately. Additionally, more financing options should be provided to enhance the ability of rural households to purchase off-grid renewable energy systems and enable companies to develop markets for their products. One option is low-interest loans provided by government or banks. Loans could be released on a standard application for rural households who can meet the requirements. In this way, households will pay only minimum down payment at the beginning and will payoff the outstanding amount and interests installments, similar to monthly expenditure on fuels, thus allowing households to afford renewable energy systems.

250 Another option is called fee-for-service or energy service company (ESCO) model. This option allows customers to enjoy the services of renewable energy systems without actually paying for systems. Under this scheme, renewable energy customers don’t need to pay for the high initial cost of systems but only the affordable monthly fee to service companies. As a more affordable financing option, it can reach to a large base of customers. Additionally, China can think about creating a sustainable energy utility (SEU) model. The SEU model was first developed by Dr. John Byrne at the Center for Energy and Environmental Policy, University of Delaware to provide renewable energy services to households (FREE, 2013). SEU can fill the gap that rural households always lack access to initial capital for renewable technologies by drawing a variety of funding resources. In addition, SEU can assist customers in obtaining renewable energy services by selecting qualified ESCOs. In this way, SEU is a one- stop-shop for energy financing and energy delivery.

8.2.5 Improving Renewable Energy Services It is evident that lack of technical skills and lack of people’s know-how for setting-up and operating renewable systems will affect renewable energy development in Guizhou, thus, efforts are needed for improving this situation. Recommendations include: (1) provision of effective training programs of product information and installation for renewable professionals such as systems sellers, company representatives, and technical workers; (2) provision of effective training programs for households who will be adopting off-grid renewable systems on basic operation and maintenance techniques including appliance connection, battery use, recharging batteries, cleaning solar panels, feeding and discharging biogas digester; (3) creation

251 of educational programs, campaigns and social networks – educating users about off- grid renewable energy options and social and environmental benefits; and (4) establishment of a local rural renewable energy service stations, providing after-sale repair and preventive maintenance services locally. It should be noted that the service stations should be local context: the stations should be owned by local entrepreneur and the technicians should be locally recruited and trained on renewable technologies. This is because local participation makes renewable projects responsive to local needs. Local rural households’ needs need to be considered to ensure that energy services are appropriate, socially acceptable and sustainable. Rural communities, in particular women, must have their opinions heard and addressed if after-sale services are to meet their needs and provide long-term solutions. Local experts, such as engineering students from local universities and colleges, should be involved in carrying out and implementing energy services to address the common technical problems that occur to rural users. In this way, services such as after-sale repair and preventive maintenances will be better informed and reflect local rural people’s needs.

8.2.6 Strengthening Cooperation Guizhou could seek cooperation and supports from other provinces in China as well as international agencies in the area of off-grid renewable energy development. One option is Guizhou province and other provinces in China could establish an information exchange platform to collect, arrange, analyze and report the valuable information regards to local renewable energy development. For example, Guizhou can learn best experiences from provinces such as Xinjiang, Qinghai that have rich solar resources and long history of utilizing solar home systems. Guizhou could also

252 learn best practices from Heilongjiang and Hunan, which are major agricultural provinces and have long experience of utilizing biogas digesters. Additionally, Guizhou can partner with international energy agencies (such as Asian Development Bank, International Energy Agency, International Renewable Energy Agency, etc.) and universities to exchange information on off-grid renewables, to learn other regions and countries’ experiences, and to explore greater off-grid renewable energy development opportunities. For example, the Center for Energy and Environmental Policy (CEEP) at the University of Delaware (UD) is a leading research institute in energy and environmental policy. The Center conducts researches on sustainable development, energy efficiency and renewable energy applications, and comparative energy and environmental policy. The Center conducted a feasibility study of solar home system to address rural electricity needs in western China in 2001 and another assessment on integrated biogas digester system in rural China in 2004. These two studies were the “founding studies” of off-grid renewable energy systems in China, and they have provided valuable insights and inspirations for this dissertation. In future, Guizhou province can also build cooperation with CEEP to foster dissimilation of off-grid renewable technologies in the province.

8.3 Suggestions for Future Works

8.3.1 Update Data Data utilized in this dissertation include socio-economic data and energy utilization data of rural households in Guizhou, and cost data of off-grid reneable energy systems. All these data are found to have inclusive effects on the study’s outcome. One limitation to this study is some official data are not the most recent.

253 This is due to the complexity of Chinese government to gather, measure and present its data. As a result, data published by national and provincial statistic bureaus always lag behind. Another limitation is that some data in this study are absent. For example, Guizhou rural households’ annual energy expenditure data are missing, since they are not in Chinese government’s research areas. Also labor costs for constructing specific types of solar home systems and biogas digesters are missing, because there is not a data system established in China tracking all aspects of off-grid renewable options. Because of data limits, impact evaluations of off-grid renewable options identified in this dissertation might yield a slight difference in calculated result from the actual. Therefore, significant efforts are needed to update and fill the data gaps in this study. This requires a close monitoring of publications from central and provincial governments. It also requires developing an accurate single dataset that can track all necessary aspects of off-grid renewable energy systems in China.

8.3.2 Conduct Field Trip in Guizhou All energy data and cost assumptions in this dissertation are secondary data and they are based on reported data for counties that are studied. They are not actual site data such as household electricity loads and cooking needs, the cost to build a solar home system or biogas digester on site, and the cost for maintaining the systems on site. Secondary data inevitably have limitations, including incomplete information, inaccuracy information, and lack of quality because data originally collected are not specific to another study. Therefore, real economic performance of off-grid renewable options analyzed in this study might yield a slight difference in calculated result form the actual.

254 One way to overcome this limitation is to collect primary data through fieldwork with survey and questionnaire. This approach will be particularly efficient for addressing specific questions in this study such as household energy profiles in individual counties, and actual cost parameters of identified off-grid renewable technologies. In fact, this study has previously planned a field trip in Guizhou, conducting interviews to characterize rural energy users in Guizhou counties. However, due to time unavailability, it is not realized.

8.3.3 Extend Current Research In this dissertation, while analyzing the sustainability performances of off-grid renewable energy technologies, only solar for electricity and biogas for cooking have been taken into account. However, in future, other technologies could also be considered. These technologies include biogas digesters for electricity, integrated biogas digesters such as “3-in-1” or “4-in-1” models that incorporate other components such as greenhouse and pig house, wind turbines, and integrated wind- solar systems. In addition to individual decentralized renewable energy systems, large- scale systems such as community-based solar and biogas digesters could also be good study directions in future. The energy and sustainability performance analysis methods could be further developed (using the same set of indicators) for these technologies (individual, integrated or community-based) to see how they affect rural energy development in Guizhou. In addition, the evaluation of sustainability performance of various renewable technologies could be conducted under different scenarios (such as low cost scenario and high cost scenario) with careful and appropriate adjustment of the parameters.

255 Additionally, this dissertation can be extended to include other factors (such as institutional factor, users’ know-how factor, etc.) and to exam their impacts on rural energy development in China. Another direction for future work is to include other provinces in China as case regions in this study to take account for different renewable energy resource availability of provinces while comparing energy performances of various renewable technologies, observing different impacts of renewable options’ in different provinces.

8.3.4 Expand New Dimensions The dissertation has provided a detailed overview of sustainability performances of various off-grid renewable technologies, however the market potential of renewable energy utilization in Guizhou is not addressed. Undoubtedly, there is a huge market for renewable energy in rural Guizhou as well as in China, however questions like “what are the characters of rural energy users, what are the socio-economic conditions that affect the use of renewable energy options in Guizhou, what is the affordability of rural energy users for renewable energy technologies are not answered. Thus a new dimension for future work is to include a comprehensive socio-economic assessment of renewable energy market in Guizhou.

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