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  • 标题:Power System Transient Stability Based on Data Mining Theory
  • 本地全文:下载
  • 作者:Zhen Cui ; Jia Shi ; Runsheng Wu
  • 期刊名称:IOP Conference Series: Earth and Environmental Science
  • 印刷版ISSN:1755-1307
  • 电子版ISSN:1755-1315
  • 出版年度:2018
  • 卷号:108
  • 期号:5
  • 页码:052009
  • DOI:10.1088/1755-1315/108/5/052009
  • 语种:English
  • 出版社:IOP Publishing
  • 摘要:In order to study the stability of power system, a power system transient stability based on data mining theory is designed. By introducing association rules analysis in data mining theory, an association classification method for transient stability assessment is presented. A mathematical model of transient stability assessment based on data mining technology is established. Meanwhile, combining rule reasoning with classification prediction, the method of association classification is proposed to perform transient stability assessment. The transient stability index is used to identify the samples that cannot be correctly classified in association classification. Then, according to the critical stability of each sample, the time domain simulation method is used to determine the state, so as to ensure the accuracy of the final results. The results show that this stability assessment system can improve the speed of operation under the premise that the analysis result is completely correct, and the improved algorithm can find out the inherent relation between the change of power system operation mode and the change of transient stability degree.
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