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Neural network based power system damping controller for SVC

Changaroon, K and Thukaram, D and Chirarattananon, S and Srivastava, SC (1999) Neural network based power system damping controller for SVC. In: IEE proceedings, Part – C, 146 (4). pp. 370-376.

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Abstract

The development of a neural network based power system damping controller (PSDC) for a static VAr compensator (SVC), designed to enhance the damping characteristics of a power system network representing a part of the Electricity Generating Authority of Thailand (EGAT) system is presented. The proposed stabilising controller scheme of the SVC consists of a neuro-identifier and a neuro-controller which have been developed based on a functional link network (FLN) model. A recursive online training algorithm has been utilised to train the two networks. The simulation results have been obtained under various operating conditions and disturbance cases to show that the proposed stabilising controller can provide a better damping to the low frequency oscillations, as compared to the conventional controllers. The effectiveness of the proposed stabilising controller has also been compared with a conventional power system stabiliser provided in the generator excitation system

Item Type: Journal Article
Additional Information: Copyright 1999 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.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 04 Apr 2012 10:16
Last Modified: 04 Apr 2012 10:16
URI: http://eprints.iisc.ernet.in/id/eprint/44222

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