撒哈拉以南非洲地區(qū)仍有高比例的人口仍無法獲得現代能源,面臨著更為嚴峻的缺乏電力及清潔能源供應的全球性挑戰(zhàn),且使用傳統和非清潔能源進行照明和烹飪會對健康、經濟和氣候變化產生不利影響。全球正在努力實現可持續(xù)發(fā)展目標,要在2030年實現普遍獲得可負擔的、可靠的、可持續(xù)的清潔能源,增加可再生能源的份額并提高能源效率。該目標的實現需要通過促進清潔能源技術研發(fā)、基礎設施建設和技術升級,為所有人提供現代和可持續(xù)的能源服務。從實現可持續(xù)發(fā)展目標的進展評估情況看,迫切需要改進當前的能源政策和戰(zhàn)略以實現全球能源目標。盧旺達作為撒哈拉以南非洲國家的一員,盡管擁有豐富的能源資源,但也面臨著清潔能源短缺的挑戰(zhàn)。該國制定了提供清潔、可靠和可負擔能源的政策和戰(zhàn)略目標,并到2035年成為中等收入國家,到2050年成為高收入國家。根據這一目標,需要探討分析該國清潔能源技術發(fā)展的挑戰(zhàn)和機遇。本文主要對盧旺達清潔能源技術發(fā)展的影響因素和策略進行綜合評價和建模,旨在為能源項目開發(fā)商的投資決策和政府能源部門制定合適的激勵政策提供參考。本文的主要研究內容和成果如下:(1)分析影響盧旺達清潔能源技術發(fā)展的因素并制定策略。首先進行了...

【文章頁數】：166 頁

【學位級別】：博士

【文章目錄】：
摘要
Abstract
Chapter 1 Introduction
    1.1 Research Background and significance
        1.1.1 Research background
        1.1.2 Research Significance
    1.2 Research status at home and abroad
        1.2.1 Status of biogas development in developing countries
        1.2.2 Assessing the potential and viability of solar energy technology
        1.2.3 Challenges of African clean cooking energy sector
        1.2.4 Brief comments of related research review
    1.3 Dissertation outline, technical roadmap and key contributions
        1.3.1 Outline of the dissertation
        1.3.2 Technical roadmap
        1.3.3 Key contributions of the dissertation
Chapter 2 Analysis of influencing factors affecting the clean energy development in Rwanda
    2.1. Introduction
    2.2. Research methodology
    2.3. SWOT analysis of factors affecting the clean energy sector
        2.3.1 Analysis of strengths
        2.3.2 Analysis of weaknesses
        2.3.3 Analysis of opportunities
        2.3.4 Analysis of threats
    2.4 Strategies formulation for the development of Rwandan clean energy sector
    2.5 Summary
Chapter 3 Interpretive structural modeling of strategies for the development of clean energy technology
    3.1 Overview of analytical modeling methods for energy planning
    3.2 Research procedure and methodology
    3.3 ISM analysis of the hierarchical structure of the strategies
        3.3.1 Development of Structural Self Interaction Matrix (SSIM)
        3.3.2 Reachability matrix
        3.3.3 Levels partitioning
        3.3.4 ISM digraph model formation of strategies
    3.4 MICMAC analysis
    3.5 Discussions
    3.6 Summary
Chapter 4 Analytical hierarchical modeling of barriers for biogas adoption in Rwandan households
    4.1 Introduction
        4.1.1 Biogas as an alternative solution to biomass for cooking
        4.1.2 Overview of biogas program in Rwanda
    4.2 Research procedure and mcthodology
    4.3 Identification of barriers for biogas adoption in Rwanda
    4.4 AHP modeling of barriers for biogas adoption in Rwanda
        4.4.1 AHP modeling process
        4.4.2 Priority ranking of barriers
    4.5 Discussions and policy recommendations
        4.5.1 Discussions
        4.5.2 Policy recommendations
    4.6 Summary
Chapter 5 Evaluating the influencing factors for the adoption of clean cooking technology
    5.1 Introduction
    5.2. Overview of cooking fuel adoption status in Rwanda
    5.3. Research approach and methodology
    5.4. Logical modeling of LPG supply chain
        5.4.1 Enabling environment
        5.4.2 LPG industry's structure and services
        5.4.3 LPG pricing and costing
        5.4.4 LPG demand and support strategies
        5.4.5 Users' needs and perceptions
    5.5 Survey analysis results of users' cooking energy adoption
        5.5.1 Demographic analysis of respondents
        5.5.2. Socio-economic characteristics
        5.5.3. Household cooking fuel characteristics
        5.5.4. Reasons for choosing primary fuel by the participants
        5.5.5. Barriers for the adoption of LPG
        5.5.6 Needed assistance to scale up LPG adoption
    5.6 Discussions and policy recommendations
        5.6.1 Discussions
        5.6.2 Policy recommendations
    5.7 Summary
Chapter 6 Evaluating the techno-economic viability of solar power technology in Rwandan climatic conditions
    6.1 Introduction
    6.2 Overview of CSP technology
    6.3 Modeling and simulation
        6.3.1 CSP modeling with System Advisor Model
        6.3.2 Locations and weather analysis
        6.3.3 Modeling the performance of PTPP and STPP
    6.4 Results and discussions
        6.4.1 Optimization of the STPP for both sites
        6.4.2 Optimization of the PTPP for both sites
        6.4.3 Performance analysis of the optimized plants
        6.4.4 Sensitivity analysis
        6.4.5 Major barriers and policy implications
    6.5. Summary
Chapter 7 Conclusions and future works
    7.1 Conclusions
    7.2 Future works
References
Appendix
Publications
Acknowledgements
About the author



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