ANN application techniques for power system stability estimation

Moghavvemi, M. and Yang, S.S. (2000) ANN application techniques for power system stability estimation. Electric Machines and Power Systems, 28 (2). pp. 167-178. ISSN 0731356X

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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.

Item Type: Article
Uncontrolled Keywords: Artificial neural network; Linear basis function; Power system; Radial basis function; Stability index; Voltage stability; Algorithms; Electric network topology; Monitoring; Radial basis function networks; Voltage stabilizing circuits; Stability index; Electric power systems
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Ms. Norhamizah Tamizi
Date Deposited: 24 Mar 2014 08:17
Last Modified: 23 Nov 2017 03:05
URI: http://eprints.um.edu.my/id/eprint/9691

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