省际可再生能源发电项目开发水平评价研究
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摘要
为评估不同省域可再生能源发电项目的综合开发水平,基于全产业链视角,文章从可再生能源资源开发水平、可再生能源电力生产水平和可再生能源电力消纳水平三个维度,建立了区域可再生能源发电项目开发评价指标体系。根据最小信息鉴别原理,综合不同类型定性和定量赋权方法的优点,提出组合权重赋权法,构建了基于理想点法的区域可再生能源发电项目开发水平评价模型。将模型有效应用于东南沿海5省和"三北"地区5省区的数据分析,测评得出不同省份可再生能源发电项目开发总体表现和各项指标差异,用以科学确定各区域发展水平和特征,帮助优化区域可再生能源电力可持续发展。
For to evaluate the comprehensive development levels of renewable energy power generation(REPG) projects in different provinces, a multi-index evaluation system is proposed from perspectives of all-industry chain: renewable energy source utilization, renewable energy power production, and renewable energy power consumption. According to the principle of minimum information discrimination, combining the advantages of both qualitative and quantitative weighting methods, a combined weighting determination method is proposed, and an evaluation model of development level for regional REPG projects based on TOPSIS is constructed. The overall performance and indicator differences of REPG projects in five provinces selected from the southeastern coast of China and five provinces selected from the North China are assessed by applying the model. The results help to scientifically evaluate the development level and characteristics of REPG projects, as well as to optimize the sustainability of REPG for different regions.
For to evaluate the comprehensive development levels of renewable energy power generation(REPG) projects in different provinces, a multi-index evaluation system is proposed from perspectives of all-industry chain: renewable energy source utilization, renewable energy power production, and renewable energy power consumption. According to the principle of minimum information discrimination, combining the advantages of both qualitative and quantitative weighting methods, a combined weighting determination method is proposed, and an evaluation model of development level for regional REPG projects based on TOPSIS is constructed. The overall performance and indicator differences of REPG projects in five provinces selected from the southeastern coast of China and five provinces selected from the North China are assessed by applying the model. The results help to scientifically evaluate the development level and characteristics of REPG projects, as well as to optimize the sustainability of REPG for different regions.
引文
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[16]许辉云,伍蕾,陈祖龙.湖北省旅游产业-交通运输-区域经济耦合协调度[J].湖北民族学院学报(自然科学版),2017,35(4):463-470,476.
[2]赵枫.在新形势下我国光伏产业持续发展的思考[J].可再生能源,2017,35(8):1181-1187.
[3]耿琎.基于因子分析的沿海可再生能源开发结构优化研究[D].大连:大连理工大学,2015.
[4]周鹏飞,陈栋.海上可再生能源开发评价指标体系与实证研究[J].可再生能源,2012,30(8):95-101.
[5]Shi R J,Fan X C,He Y.Comprehensive evaluation index system for wind power utilization levels in wind farms in China[J].Renewable and Sustainable Energy Reviews,2017,69:461-471.
[6]He L,Li C L,Nie Q Y,et al.Core abilities evaluation index system exploration and empirical study on distributed PV-generation projects[J].Energies,2017,10(2):1-18.
[7]胡殿刚,张雪佼,陈乃仕,等.新能源发电项目多维度后评价方法体系研究[J].电力系统保护与控制,2015,43(4):10-17.
[8]张龙.可再生能源开发利用绩效评价[D].武汉:中国地质大学,2017.
[9]李春华.北京可再生能源区位发展优势评价[J].辽宁工程技术大学学报(社会科学版),2015,17(5):516-522.
[10]Zhao Zhenyu,Chen Yulong.Critical factors affecting the development of renewable energy power generation:Evidence from China[J].Journal of Cleaner Production,2018,184:466-480.
[11]陈玉龙,赵振宇.区域可再生能源发电项目开发影响因素改进解释结构模型研究[J].电网与清洁能源,2018,34(2):149-156.
[12]鲍学英,李海连,王起才.基于灰色关联分析和主成分分析组合权重的确定方法研究[J].数学的实践与认识,2016,46(9):129-134.
[13]周才英,杨俊.改进的加速遗传算法在课程评价体系中的应用[J].江西理工大学学报,2010,31(3):48-50,68.
[14]陈红玉.专利技术价值评估中层次分析法的改进及实例研究[D].重庆:重庆理工大学,2016.
[15]牛东晓,宋宗耘.基于熵值法和物元可拓模型的核电站安全运行状态评价[J].安全与环境学报,2015,15(5):25-29.
[16]许辉云,伍蕾,陈祖龙.湖北省旅游产业-交通运输-区域经济耦合协调度[J].湖北民族学院学报(自然科学版),2017,35(4):463-470,476.