Moghavvemi, Mahmoud and Yang, S.S. (2000) ANN application techniques for power system stability estimation. Electric Machines & Power Systems, 28 (2). pp. 167-178. ISSN 0731-356X, DOI https://doi.org/10.1080/073135600268441.
Full text not available from this repository.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.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Artificial neural network; Linear basis function; Power system; Radial basis function; Stability index; Voltage stability |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering |
| Depositing User: | Ms. Norhamizah Tamizi |
| Date Deposited: | 24 Mar 2014 08:17 |
| Last Modified: | 20 Oct 2021 01:15 |
| URI: | http://eprints.um.edu.my/id/eprint/9691 |
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