Long-Term Electrification Strategy Scenarios for Nigeria: A Resource Potential and Economic Consideration For A Sustainable Energy System = 나이지리아를 위한 장기 전기화 전략 시나리오:지속 가능한 에너지 시스템을 위한 자원 잠재력과 경제적 고려

다국어 초록 (Multilingual Abstract)

The core of the electricity system expansion analysis in this Study entails using Low Emissions Analysis Platform (LEAP) for optimization of power supply options for Nigeria by minimizing system costs to meet the forecasted demand, hour-by-hour, through the year using realistic resources availability data for wind, solar irradiation, hydrological resources, natural gas availability, coal, nuclear fuels and storage systems. Once the power demand envelope is determined using the Nigerian Energy Calculator (NECAL), the model estimates the least-cost expansion path for meeting that demand, based on a cost minimization basis for all electricity generation technologies that are either available or planned for within Nigeria. The LEAP model automatically accounts for the necessary transmission and distribution infrastructure including losses. 5 scenarios including The Optimized BAU, Emissions Pricing Scenario (EPS), Demand Side Management Scenario (DSM), Reduced Emission Scenario, and Renewable Target Scenarios were explored using an assumed set of thematic policies for each of the scenarios. These scenarios are explored in terms of cost generation, renewables penetration, cost of production and emissions level associated with them between 2019 and 2060. At the end of the optimization period, the DSM scenario comes up with the least capacity requirement at 107.8GW and the Reduced Emissions scenario has the highest capacity requirement of 157GW.
The study also presents a decomposition analysis of the CO2 emissions for each scenario using several factors that represent population size, economic growth, conversion efficiency, carbon intensity and energy intensity. Overall, the positive contributors to increase in emissions are the population and the economic activity effect, whereas the carbon intensity effect, conversion efficiency effect and energy intensity effect are negative contributors to emissions in the NESI given the 5 scenarios. The main contributors to emissions were identified for each scenario across a 5-year grouping. The study notes the responsiveness of the Nigerian Electricity Supply Industry (NESI) to modern electricity market policies and also recommend the adoption of a mix of policies in achieving planned electrification.

목차 (Table of Contents)

• Table of Contents
• Abstract i
• Table of Contents iii
• List of Tables ix
• List of Figures xi
• Chapter I. Overview 1
• 1.1. Introduction 1
• 1.2. Background 3
• 1.2.1 Status of the Nigerian Electricity Sector 3
• 1.2.2 Historical Perspective on the evolution of the power sector 4
• 1.2.3 Structure of the Nigerian Electricity Supply Industry (NESI) 9
• 1.2.4 Motivation for this study 10
• 1.3. Research Question 11
• 1.4. Research Objective 13
• 1.4.1 Description of Reference Energy System 15
• 1.4.2 Research Model Development Overview 16
• Chapter II. Literature Review 19
• 2.1 Energy Planning Models 19
• 2.1.1 Limitations in Electricity Models 21
• 2.1.2 Managing Errors 21
• 2.1.3 Classification of Models 22
• 2.2 Existing Literature using LEAP for Energy studies 25
• 2.2.1 Applications of LEAP in Academic Literature. 25
• 2.3 Literature Review on Decomposition studies 29
• 2.4 Application areas for LMDI approach 30
• 2.5 Popular Decomposition approaches 31
• 2.6 Review studies utilizing the LMDI approach 32
• 2.7 Kaya-LMDI Model 35
• 2.8 Logarithmic Mean Divisia Index (LMDI) 37
• 2.9 Tapio Decoupling Model 38
• Chapter III. Nigerian Electricity Sector and Resource Potential 41
• 3.1 Overview of the Country’s Landscape and socioeconomic status 41
• 3.2 Structure of the Nigerian Electricity Supply Industry (NESI) 43
• 3.2.1 Generation Capacity 44
• 3.2.2 Power Transmission in Nigeria 48
• 3.2.3 Power Distribution Capacity 51
• 3.3 An Overview of resource potential in Nigeria 52
• 3.4 Levelized Cost of Electricity Analysis 62
• 3.4.1 Comparing Generation Technologies 62
• 3.4.2 Limitations of LCOE approach 64
• 3.4.3 Levelized Cost of Electricity Calculation. 65
• 3.4.4 Sensitivity Analysis 69
• Chapter IV. Simulation Description 78
• 4.1 Model Selection 79
• 4.2 Scenario and Modelling approach 84
• 4.2.1 Scenario Description 87
• 4.3 Algorithm for the Modules 89
• 4.4 Demand side Modelling 92
• 4.5 Description of NECAL2050 92
• 4.4.1. Nigeria Demand Modelling-NECAL 2050. 93
• 4.4.2. Global Assumption 94
• 4.4.3. Drivers of Electricity service demand. 94
• 4.6 Transformation Branch 95
• 4.4.4. Modelling Transformation in LEAP 95
• 4.7 Model Set up 97
• 4.7.1 Time slices 97
• 4.7.2 Load Shape 97
• 4.7.3 Maximum Availability 99
• 4.7.4 Reserve Margin (RM) 99
• 4.7.5 Capacity Credit 101
• 4.7.6 Dispatch Rule 101
• 4.7.7 Power Generation 101
• 4.7.8 Battery Storage 102
• 4.7.9 Cost Data 107
• Chapter V. Simulation Results 110
• 5.1 Demand Projection 110
• 5.2 Supply Side Results 112
• 5.2.1 Optimized BAU scenario 112
• 5.2.2 Demand Side Management Scenario 115
• 5.2.3 Renewables Target Scenario 118
• 5.2.4 Emission Pricing Scenario-EPS 121
• 5.2.5 Reduced Emission Scenario 125
• 5.3 Discussions 128
• 5.3.1 Optimized BAU 128
• 5.3.2 Demand Side Management 129
• 5.3.3 Renewables Target Scenario 131
• 5.3.4 Emission Pricing Scenario 132
• 5.3.5 Reduced Emission Scenario 134
• 5.4 Summary of Scenario attribute 135
• 5.4.1 Energy Diversity Assessment of Modelled Scenarios 138
• 5.4.2 Results for Energy Diversity Analysis 141
• 5.4.3 Discussion on Energy Diversity Analysis of modelled Scenarios 143
• 5.5 Chapter Summary 145
• Chapter VI. Decomposition Analysis 146
• 6.1 Decomposition of On-Grid Emissions 146
• 6.2 Nigeria’s Electricity Sector emissions 149
• 6.3 Current Emissions Profile 150
• 6.4 Data and Methodology for decomposition 152
• 6.4.1 Driving factors and decomposition analysis model 154
• 6.5 Results for Decomposition 156
• 6.5.1 Discussions 158
• 6.6 Implication of decomposition results 166
• 6.7 Decoupling Analysis Results 170
• 6.8 Discussions on Decoupling 172
• 6.9 Conclusion 174
• Chapter VII. 175
• 7.1 Overall Conclusion 175
• 7.2 Policy Implications 177
• 7.3 Limitations of the study 179
• List of Abbreviations 198
• Appendices 201
• Appendix A: Results on Optimization Model 201
• Appendix B: Results on Decomposition 213
• Appendix C: Existing power generating plants in Nigeria 216
• Acknowledgments 221