海上风电项目的经济性和风险评价研究

发布时间：2018-01-14 11:39

本文关键词：海上风电项目的经济性和风险评价研究　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：目前各国都争相将新能源产业作为新的经济增长点,其中风力发电以其相对成熟的技术和较低的成本得到世界各国的重视。海上风电因其距离电力负荷中心较近、资源丰富等优势逐渐受到关注。对海上风电项目的经济性和风险评价进行研究,旨在为海上风电发展的政策制定和海上风电项目的规划与管理提供理论依据。本文首先从规模、发展规划、技术水平和政策支持等方面对国外及我国海上风电项目进行对比和分析,在此基础上着重对我国海上风电项目进行SWOT分析,论述了目前具有的优势、劣势、机遇和威胁。其次,从技术学习曲线、CDM清洁发展机制和政策三方面对其成本、收益和综合经济性进行了研究。通过技术学习曲线研究学习效应对海上风电成本发展的影响,并拟合出相应的技术学习曲线对成本进行预测。以CDM项目的具体流程为基础探讨了CDM项目对海上风电收益的影响以及碳价格变化的重要性。再次,分析了财政、电价和并网政策对海上风电长期经济性的影响,构建立了海上风电经济性评价模型,并利用遗传算法改进了的RBF神经网络对经济性进行了评价。最后,以海上风电项目前期资源评估到施工建设再到运营维护的逻辑,从风资源评价、施工安装、自然条件、设备与检修、管理、政策与市场六个方面,分析了海上风电项目所面临的风险,采用遗传算法改进了的RBF神经网络构建了符合其自身特点的风险评价模型,并对该模型进行了验证。
[Abstract]:At present, all countries are scrambling to take the new energy industry as the new economic growth point. Among them, wind power generation is paid more attention by the countries all over the world because of its relatively mature technology and low cost, and offshore wind power is close to the power load center. The economic efficiency and risk assessment of offshore wind power projects are studied in order to provide theoretical basis for the policy formulation of offshore wind power development and the planning and management of offshore wind power projects. In this paper, the scale, development planning, technical level and policy support of offshore wind power projects abroad and China are compared and analyzed. On this basis, the SWOT analysis of offshore wind power projects in China is emphasized, and the advantages, disadvantages, opportunities and threats are discussed. Secondly, the cost of CDM clean development mechanism and policy is discussed from three aspects: technology learning curve and CDM clean development mechanism and policy. The effects of learning effect on the development of offshore wind power cost are studied through the technical learning curve. Based on the specific flow of CDM project, the influence of CDM project on offshore wind power revenue and the importance of carbon price change are discussed. Thirdly, the influence of finance, electricity price and grid connection policy on the long-term economy of offshore wind power is analyzed, and the evaluation model of offshore wind power economy is established. The RBF neural network improved by genetic algorithm is used to evaluate the economy. Finally, from the wind resource evaluation to construction construction to operational maintenance logic, from wind resource evaluation, construction installation, natural conditions, equipment and maintenance, management, policy and market six aspects. The risk of offshore wind power project is analyzed, and the risk evaluation model is constructed by using the improved RBF neural network based on genetic algorithm, and the model is verified.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.61

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