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An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Thukaram, D and Khincha, HP and Ravikumar, B (2006) An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems. In: IEEE Power India Conference 2006, Apr 10-12, 2006, New Delhi, India, pp. 307-313.

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Abstract

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Item Type: Conference Paper
Additional Information: Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords: Ault monitoring and identification;Support Vector Machines.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 27 Aug 2010 05:55
Last Modified: 19 Sep 2010 06:12
URI: http://eprints.iisc.ernet.in/id/eprint/30497

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