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ANN application techniques for power system stability estimation

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 topolog...

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Main Authors: Moghavvemi, M., Yang, S.S.
Format: Article
Published: Taylor & Francis. 2000
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/9726/
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spelling my.um.eprints.97262017-11-23T03:05:00Z http://eprints.um.edu.my/9726/ ANN application techniques for power system stability estimation Moghavvemi, M. Yang, S.S. TA Engineering (General). Civil engineering (General) 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. Taylor & Francis. 2000 Article PeerReviewed Moghavvemi, M. and Yang, S.S. (2000) ANN application techniques for power system stability estimation. Electric Power Components and Systems, 28 (2). pp. 167-177. ISSN 15325008
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Moghavvemi, M.
Yang, S.S.
ANN application techniques for power system stability estimation
description 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.
format Article
author Moghavvemi, M.
Yang, S.S.
author_facet Moghavvemi, M.
Yang, S.S.
author_sort Moghavvemi, M.
title ANN application techniques for power system stability estimation
title_short ANN application techniques for power system stability estimation
title_full ANN application techniques for power system stability estimation
title_fullStr ANN application techniques for power system stability estimation
title_full_unstemmed ANN application techniques for power system stability estimation
title_sort ann application techniques for power system stability estimation
publisher Taylor & Francis.
publishDate 2000
url http://eprints.um.edu.my/9726/
_version_ 1643688638742003712
score 13.18916

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