Power system topological observability analysis using artificial neural networks

Amit Jain, R. Balasubramanian, S. C. Tripathy, Brij N. Singh, Yoshiyuki Kawazoe

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

This paper presents a new method for the power system topological observability analysis using the artificial neural networks. The power system observability problem, related to the power system configuration or network topology, called as the topological observability, is studied utilizing the artificial neural network model, based on multilayer perceptrons using the Back-propagation algorithm as the training algorithm. Another training algorithm, quickprop is also applied for training the similar artificial neural network to further check the suitability of other training algorithm also. The proposed artificial forward neural network model has been tested on sample power systems and results are presented.

本文言語English
ホスト出版物のタイトル2005 IEEE Power Engineering Society General Meeting
ページ497-502
ページ数6
出版ステータスPublished - 2005
イベント2005 IEEE Power Engineering Society General Meeting - San Francisco, CA, United States
継続期間: 2005 6 122005 6 16

出版物シリーズ

名前2005 IEEE Power Engineering Society General Meeting
1

Other

Other2005 IEEE Power Engineering Society General Meeting
CountryUnited States
CitySan Francisco, CA
Period05/6/1205/6/16

ASJC Scopus subject areas

  • Engineering(all)

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