基于粗糙集和模糊C均值聚类算法的可再生能源投资风险评价  

Investment risk evaluation model of renewable energy project based on rough set theory and fuzzy C-means clustering

作　　者：谭忠富[1] 张会娟[1] 宋艺航[1] 刘珂[1] 

机构地区：[1]华北电力大学能源经济与环境研究所,北京102206

出　　处：《可再生能源》2014年第2期179-184,共6页Renewable Energy Resources

基　　金：国家自然科学基金项目(71273090;71201056)

摘　　要：针对可再生能源发电项目投资风险评价问题,提出了基于粗糙集理论与模糊C均值聚类算法的可再生能源投资风险评价模型。基于全寿命周期理论,在构建可再生能源共性风险指标体系的基础上,建立可再生能源投资风险评价信息系统;分别利用模糊C均值聚类算法和粗糙集对评价指标进行离散化处理和属性约简,确定项目投资评价的关键风险指标及其权重;最后得出各类可再生能源投资项目的综合评价值。以风电投资项目为例进行了实证分析,结果表明,该方法以评价对象的客观数据为依据来确定其综合评价值,评价结果准确合理,可为可再生能源发电项目的投资选择提供一定的参考。An investment risk evaluation model based on rough set theory and fuzzy C-means clustering was established to evaluate renewable energy projects. Based on the life cycle theory, general risk index system of renewable energy project was built, then an investment risk evaluation information system of renewable energy was set up. Fuzzy C-means clustering method and rough set were used to discretize the data and reduce the numbers of evaluation indexes,the key risk indexes were identified. Finally, the weight of key risk indexes and comprehensive evaluation value of various renewable energy projects were calculated. Taking wind power projects as examples, the results of case study indicate that the method can improve accuracy and rationality of evaluation due to the comprehensive evaluation value determined by objective data of evaluated object, which provide reference for the investment decision-making of renewable energy projects.

关 键 词：可再生能源 投资风险 评价模型 粗糙集 模糊C均值聚类 

分 类 号：TK81[动力工程及工程热物理—流体机械及工程]