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Sectionalized ANN approach in predicting voltage stability in power systems

In recent years artificial neural networks (ANNs) have been proposed as an alternative method for solving certain difficult power system problems for which conventional techniques have not achieved the desired speed, accuracy, or efficiency. ANN methodology allows complex relationships between an in...

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Main Author: Moghavvemi, M.
Format: Article
Published: ACTA Press 1999
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.um.edu.my/9680/
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spelling my.um.eprints.96802017-11-23T03:04:22Z http://eprints.um.edu.my/9680/ Sectionalized ANN approach in predicting voltage stability in power systems Moghavvemi, M. TA Engineering (General). Civil engineering (General) In recent years artificial neural networks (ANNs) have been proposed as an alternative method for solving certain difficult power system problems for which conventional techniques have not achieved the desired speed, accuracy, or efficiency. ANN methodology allows complex relationships between an initial state and a final state to be determined by an iterative mathematical algorithm, instead of by an expert. A properly trained ANN can classify the security of a previously unencountered input pattern with good accuracy. As systems grow in size and complexity, the mapping to be learned become increasingly complicated. In this paper the use of a sectionalized ANN approach is proposed for predicting the voltage stability index of a large-scale power system. ACTA Press 1999 Article PeerReviewed Moghavvemi, M. (1999) Sectionalized ANN approach in predicting voltage stability in power systems. International Journal of Power and Energy Systems, 19 (1). pp. 66-70. ISSN 10783466
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.
Sectionalized ANN approach in predicting voltage stability in power systems
description In recent years artificial neural networks (ANNs) have been proposed as an alternative method for solving certain difficult power system problems for which conventional techniques have not achieved the desired speed, accuracy, or efficiency. ANN methodology allows complex relationships between an initial state and a final state to be determined by an iterative mathematical algorithm, instead of by an expert. A properly trained ANN can classify the security of a previously unencountered input pattern with good accuracy. As systems grow in size and complexity, the mapping to be learned become increasingly complicated. In this paper the use of a sectionalized ANN approach is proposed for predicting the voltage stability index of a large-scale power system.
format Article
author Moghavvemi, M.
author_facet Moghavvemi, M.
author_sort Moghavvemi, M.
title Sectionalized ANN approach in predicting voltage stability in power systems
title_short Sectionalized ANN approach in predicting voltage stability in power systems
title_full Sectionalized ANN approach in predicting voltage stability in power systems
title_fullStr Sectionalized ANN approach in predicting voltage stability in power systems
title_full_unstemmed Sectionalized ANN approach in predicting voltage stability in power systems
title_sort sectionalized ann approach in predicting voltage stability in power systems
publisher ACTA Press
publishDate 1999
url http://eprints.um.edu.my/9680/
_version_ 1643688626800820224
score 13.160551

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