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Power system topological observability analysis using artificial neural networks

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5 Author(s)
Jain, A. ; Inst. for Mater. Res., Tohoku Univ., Sendai, Japan ; Balasubramanian, R. ; Tripathy, S.C. ; Singh, B.N.
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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.

Published in:

Power Engineering Society General Meeting, 2005. IEEE

Date of Conference:

12-16 June 2005