Identification of Bad Data of Power System Based improved GSA Judgment

摘要：

The power system security and stability of operation are determined by the accuracy of real-time data. A improvement judgment is made based on bad data detection using GSA(Gap Statistic Algorithm)data mining method,and is applied on bad data detection in power system. The Improvement judgment: elbow judgment was presented,which analyzes the relation between the error measures and the number of clusters k of the data set,then calculates the elbow angle at k and obtain the optimal number of clusters based on the least elbow angle. Combined the criterion with GSA,bad data detection could be implemented efficiently. Through simulation with real-time data from a power company,results show the detective method is accurate and rapid,and has the very good application prospects.

关键词： gap statistic algorithm identification of bad data elbow criterion cluster

作者: Zhang Junfang Ge Liang Zhao Tong Tian Ming Wu Junji

作者单位: School of Power Engineering,Nanjing University of Sci&Tech,Nanjing 210094 China Beijing Sifang Automation Company,LTD Beijing 100085 China Jiangsu Province power company,Nanjing 210024 china

会议类型: 国际会议

会议名称: 2010年中国国际供电会议(CICED 2010)

会议地点: 南京

会议语种:英文

页码: 1613-1617

在线出版日期: 2010-09-13（万方平台首次上网日期，不代表论文的发表时间）