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卢旺达清洁能源技术发展影响因素与策略评估模型分析

发布时间:2024-03-24 20:18
  撒哈拉以南非洲地区仍有高比例的人口仍无法获得现代能源,面临着更为严峻的缺乏电力及清洁能源供应的全球性挑战,且使用传统和非清洁能源进行照明和烹饪会对健康、经济和气候变化产生不利影响。全球正在努力实现可持续发展目标,要在2030年实现普遍获得可负担的、可靠的、可持续的清洁能源,增加可再生能源的份额并提高能源效率。该目标的实现需要通过促进清洁能源技术研发、基础设施建设和技术升级,为所有人提供现代和可持续的能源服务。从实现可持续发展目标的进展评估情况看,迫切需要改进当前的能源政策和战略以实现全球能源目标。卢旺达作为撒哈拉以南非洲国家的一员,尽管拥有丰富的能源资源,但也面临着清洁能源短缺的挑战。该国制定了提供清洁、可靠和可负担能源的政策和战略目标,并到2035年成为中等收入国家,到2050年成为高收入国家。根据这一目标,需要探讨分析该国清洁能源技术发展的挑战和机遇。本文主要对卢旺达清洁能源技术发展的影响因素和策略进行综合评价和建模,旨在为能源项目开发商的投资决策和政府能源部门制定合适的激励政策提供参考。本文的主要研究内容和成果如下:(1)分析影响卢旺达清洁能源技术发展的因素并制定策略。首先进行了...

【文章页数】:166 页

【学位级别】:博士

【文章目录】:
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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