摘要
随着高级测量体系(AMI)在智能电网中的大量使用,电网产生海量的样本信息数据,使用聚类分析方法可以获得详尽的电力系统运行信息。对电力系统中常用的经典型聚类方法和混合型聚类方法进行了概括,并总结了聚类结果的评价指标;对聚类分析在电力系统的负荷预测、电能质量扰动分析、孤岛检测、局部放电和需求响应等领域的应用现状进行了分析;展望了聚类分析技术在电力系统中的研究与发展前景。
With the extensive use of advanced metering infrastructure(AMI)in the smart grid,the power grid produces massive sample information data,and the detailed information of power system operation can be obtained by clustering analysis.In this paper,the classical clustering and hybrid clustering methods commonly used in power system are generalized,and the evaluation index of clustering results is summarized.Besides,the application of cluster analysis in power system load forecasting,power quality disturbance analysis,islanding detection,partial discharge and demand response are analyzed.Finally,the research and development prospect of cluster analysis technology in power system is forecasted.
作者
李君卫
汤亚芳
郝正航
冒国龙
姜有泉
LI Junwei;TANG Yafang;HAO Zhenghang;MAO Guolong;JIANG Youquan(College of Electric Engineering,Guizhou University,Guiyang 550025,China)
出处
《现代电力》
北大核心
2019年第3期1-10,共10页
Modern Electric Power
基金
国家自然科学基金项目(51467003)
关键词
聚类分析
数据挖掘
AMI
负荷预测
电能质量
局部放电
需求响应
clustering analysis
data mining
AMI
load forecasting
power quality
partial discharge
demand response
