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《Electric Power Construction》 2008-02
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Association Rule Mining for Power System Transient Stability Evaluation

FANG Yi1,WANG Jian2,WANG Xiao-ru1(1.Southwest Jiaotong University,Chengdu 610031,China;2.Tsinghua University,Beijing 100084,China)  
Transient stability simulations are carried out based on IEEE16 system.Firstly,classical k-means algorithm and fuzzy clustering FCM algorithm are compared to determine the number of clustering.The more effective FCM algorithm is selected for clustering and finding candidate discrete breaking points.From information entropy theory,final discrete break points are determined before continuous data are discretized into their own ranges and mapped to continuous numerical identifiers.Association rules among transient characteristics and association rules between transient and steady characteristics are identified.Finally,rules from mining are analyzed to evaluate power system transient stability.
【Fund】: 国家973重点基础研究发展规划资助项目(G1998010301)
【CateGory Index】: TM712
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