Extended complex kalman filter artificial neural network for bad-data detection in power system state estimation

Chien Hung Huang, Chien Hsing Lee, Kuang Rong Shih, Yaw Juen Wang

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

This paper presents an extended complex Kalman filter artificial neural network for bad-data detection in a power system. The proposed method not only can improve one-by-one detection using the traditional approach as well as enhance its performances. It uses complex-type state variables as the link weighting to largely reduce nodes number and converging speed. In other words, it not only can largely reduce the number of neurons, but also can search out the suitable and available trained variables which do not heuristically need to adjust the link weighting in the learning stage by itself. A 6-bus and IEEE standard of 30-bus power systems are used to verify the feasibility of the proposed method. The results show the convergent behavior of bad-data detection using the proposed method is better than the conventional method.

原文English
主出版物標題2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP
DOIs
出版狀態Published - 2007 12月 1

出版系列

名字2007 International Conference on Intelligent Systems Applications to Power Systems, ISAP

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 能源工程與電力技術
  • 控制與系統工程

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