电力系统及其自动化学报2024，Vol.36Issue(1)：99-105,7.DOI:10.19635/j.cnki.csu-epsa.001346
优化模糊C均值聚类的台区用户用电特征分析方法
Optimization of Fuzzy C-means Clustering Method for Analyzing Electricity Consumption Characteristics of Users in Station Area
摘要
Abstract
The accurate analysis method for user characteristics is one of the important foundations for the calculation of distribution network models and devising power service strategies.To overcome the existing difficulty of quantity selec-tion and characteristic selection in the classification of diverse users within distribution station area,an analysis method for user power characteristics based on optimized fuzzy C-means clustering is proposed.The optimized fuzzy C-means al-gorithm is used to realize clustering analysis,and a characteristic model is established through the clustering center,so as to obtain the user characteristics in the distribution station area across various scenarios.During the clustering pro-cess,the initial value of fuzzy C-means clustering is optimized by the honey badger algorithm to deal with the problem of local optimal solutions and find the minimum objective function result.The principle of index adaptive minimum is used to select the optimal clustering number,which makes the clustering center more representative.The power charac-teristics of users are obtained through a typical case in Tianjin area,and the objective function of clustering and the comprehensive evaluation index of results are optimized.关键词
聚类分析/模糊C均值/蜜獾优化/用电特征Key words
cluster analysis/fuzzy C-means/honey badger optimization/power characteristics分类
信息技术与安全科学引用本文复制引用
雷光远,张涛,唐永聪,梁特,舒可心..优化模糊C均值聚类的台区用户用电特征分析方法[J].电力系统及其自动化学报,2024,36(1):99-105,7.基金项目
国网天津市电力公司科技项目(No.KJ22-1-54) （No.KJ22-1-54）
