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Feature extraction methods for neural network-based transmission line fault discrimination

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5 Author(s)
Websper, S. ; Sch. of Electron. & Electr. Eng., Bath Univ., UK ; Dunn, R.W. ; Aggarwal, R.K. ; Johns, A.T.
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The suitability of conventional distance relays to operate correctly under variations in such factors as source impedance, prefault load and fault resistance is still a problem. This paper describes an alternative approach to nonunit protection of transmission lines using artificial neural networks (ANNs). Particular emphasis is placed on describing a methodology whereby the extraction of the input features (from the measured voltage and current signals) to the ANNs is near optimal; with this approach, the results presented clearly demonstrate that the protection technique gives satisfactory performance under a wide variation in practically encountered system operating and fault conditions

Published in:

Generation, Transmission and Distribution, IEE Proceedings-  (Volume:146 ,  Issue: 3 )

Date of Publication:

May 1999

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