Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques

In order to assess the reliability of distribution systems, more and more researchers are directing their attention to the artificial intelligent method, and several reliability indices have been proposed, such as basic load point indices and system performance indices. Artificial neural network is...

Full description

Bibliographic Details
Main Authors: Mohammoud M. Hadow, Ahmed N. Abd Allah, Sazali P. Abdul karim
Format: Article
Language:English
Published: Hindawi Limited 2012-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2012/560541
id doaj-cfacb3a5b2b84c96ae41b90b781c6bb2
record_format Article
spelling doaj-cfacb3a5b2b84c96ae41b90b781c6bb22021-07-02T09:26:12ZengHindawi LimitedJournal of Electrical and Computer Engineering2090-01472090-01552012-01-01201210.1155/2012/560541560541Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network TechniquesMohammoud M. Hadow0Ahmed N. Abd Allah1Sazali P. Abdul karim2Faculty of Electrical and Electronics Engineering, University of Malaysia, Pahang, Lebuhraya Tun Razak, Kuantan Pahang, 26300 Gambang, MalaysiaFaculty of Electrical and Electronics Engineering, University of Malaysia, Pahang, Lebuhraya Tun Razak, Kuantan Pahang, 26300 Gambang, MalaysiaNational Company, Engineering, Transmission Division TNB, Kuala Lumpur, MalaysiaIn order to assess the reliability of distribution systems, more and more researchers are directing their attention to the artificial intelligent method, and several reliability indices have been proposed, such as basic load point indices and system performance indices. Artificial neural network is recently established as a useful and much promising too, applied to variety of power systems engineering. This paper presents ANN version for evaluating the reliability of distribution power systems (DPSs), in the proposed algorithm, the ANN used to predicted (RPS) using historical data method constructed according to the backpropagation learning rule. At the same time, System indices such as SAIFI and SAIDI of real distribution system are computed and compared with results generated by network method. The result obtained by proposed method gives acceptable reliability indices and can also found that the deviation of computed values by the proposed method is less than 1% and needs running time on ASUN network environment of less than 2 s. The ANN approach demonstrates advantage over the network method.http://dx.doi.org/10.1155/2012/560541
collection DOAJ
language English
format Article
sources DOAJ
author Mohammoud M. Hadow
Ahmed N. Abd Allah
Sazali P. Abdul karim
spellingShingle Mohammoud M. Hadow
Ahmed N. Abd Allah
Sazali P. Abdul karim
Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
Journal of Electrical and Computer Engineering
author_facet Mohammoud M. Hadow
Ahmed N. Abd Allah
Sazali P. Abdul karim
author_sort Mohammoud M. Hadow
title Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
title_short Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
title_full Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
title_fullStr Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
title_full_unstemmed Reliability Evaluation of Distribution Power Systems Based on Artificial Neural Network Techniques
title_sort reliability evaluation of distribution power systems based on artificial neural network techniques
publisher Hindawi Limited
series Journal of Electrical and Computer Engineering
issn 2090-0147
2090-0155
publishDate 2012-01-01
description In order to assess the reliability of distribution systems, more and more researchers are directing their attention to the artificial intelligent method, and several reliability indices have been proposed, such as basic load point indices and system performance indices. Artificial neural network is recently established as a useful and much promising too, applied to variety of power systems engineering. This paper presents ANN version for evaluating the reliability of distribution power systems (DPSs), in the proposed algorithm, the ANN used to predicted (RPS) using historical data method constructed according to the backpropagation learning rule. At the same time, System indices such as SAIFI and SAIDI of real distribution system are computed and compared with results generated by network method. The result obtained by proposed method gives acceptable reliability indices and can also found that the deviation of computed values by the proposed method is less than 1% and needs running time on ASUN network environment of less than 2 s. The ANN approach demonstrates advantage over the network method.
url http://dx.doi.org/10.1155/2012/560541
work_keys_str_mv AT mohammoudmhadow reliabilityevaluationofdistributionpowersystemsbasedonartificialneuralnetworktechniques
AT ahmednabdallah reliabilityevaluationofdistributionpowersystemsbasedonartificialneuralnetworktechniques
AT sazalipabdulkarim reliabilityevaluationofdistributionpowersystemsbasedonartificialneuralnetworktechniques
_version_ 1721333229702610944