ANN application techniques for power system stability estimation

Document Type

Article

Publication Date

1-1-2000

Abstract

The implementation of artificial neural networks (ANN) as a power system stability monitoring tool is a viable option, introducing dynamic and intelligent solution to utility operators. This paper examines the performance of two nonlinear multilayer ANN models which are similar in structural topology and training emphasis but different by way of the utilization of their net or basis function. The performance of both models were compared for the estimation of stability index to gauge the stability of a power system network. Although tests were conducted in a simulated environment, loading patterns analyzed in this case study were realistically generated, and hence test results realistically accentuates the potential of ANN for practical on-line dynamic system implementation. © 2000, Taylor & Francis Group, LLC. All rights reserved.

Keywords

Artificial neural network, Linear basis function, Power system, Radial basis function, Stability index, Voltage stability

Publication Title

Electric Machines & Power Systems

ISSN

0731-356X

Divisions

fac_eng

Volume

28

Issue

2

Publisher

Taylor & Francis

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