摘要
为了督促供电企业切实履行政治、经济和社会责任,并实现对需求侧资源的有效调动和配电资源的高效管理,研究了电力用户对供电可靠性敏感度的评价与分类方法.分析电力用户敏感特性,提出电力用户敏感度定义;从政治、经济和社会3个因素建立电力用户敏感度评价指标体系,建立了评价指标矩阵,并给出定量、定性指标的数据预处理方法;介绍了基于层次分析(AHP)算法和模糊C均值聚类(FCM)算法的电力用户敏感度评价算法以及基于两者的综合评价方法;将该评价算法应用于某省科技核心区,对该区域内的工商业用户、居民用户和公共服务类用户进行敏感度评价.结果表明,此算法可得到各个用户的敏感度等级,为该区域的配电网规划与建设提供参考.
To urge power supply companies to effectively fulfill their political,economic and social responsibilities,and to achieve effective mobilization of demand-side resources and efficient management of power distribution resources,the sensitivity evaluation and the classification of power users were investigated.The sensitivity characteristics of power users were analyzed,and the definition of power user sensitivity was proposed.A power user sensitivity evaluation index system was established based on three factors of politics,economy and society,and the evaluation index matrix was established.The quantitative and qualitative index data preprocessing methods were provided.The power user sensitivity evaluation algorithms were introduced based on analytic hierarchy process(AHP),fuzzy C-means(FCM)clustering algorithm and comprehensive evaluation method combining the two methods.The evaluation algorithm was applied to a provincial science and technology core area,and the sensitivities of industry and commerce in the area users,residents and public service users were evaluated.The results show that the sensitivity levels of each user can be obtained by the proposed method,which can provide reference for the planning and construction of network distribution in the region.
作者
张宇轩
苏娟
贾涛
陈进
刑占礼
ZHANG Yuxuan;SU Juan;JIA Tao;CHEN Jin;XING Zhanli(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;Urumqi Power Supply Company,State Grid Xinjiang Electric Power Co.,Ltd.,Urumqi,Xinjiang 830011,China)
出处
《江苏大学学报(自然科学版)》
CAS
北大核心
2021年第5期575-581,608,共8页
Journal of Jiangsu University:Natural Science Edition
基金
国家电网公司科学技术项目(SGXJWL00YJJS1801742)。
关键词
电力用户分类
用户敏感度
敏感度评价
AHP算法
FCM算法
power user classification
user sensitivity
sensitivity evaluation
analytic hierarchy process
FCM algorithm