Load flow method using genetic algorithm

Genetic algorithms (GAs) are search methods based on the natural selection and natural genetics, while power flow studies, commonly known as load flow, form an important part of power system analysis. This paper presents the implemention of the simple genetic algorithm and constrained genetic algori...

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Main Authors: Lok, C. W., Zin, A. A. M., Mustafa, M. W., Lo, Kueiming Lun
Format: Conference or Workshop Item
Published: 2003
Subjects:
Online Access:http://eprints.utm.my/7523/
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author Lok, C. W.
Zin, A. A. M.
Mustafa, M. W.
Lo, Kueiming Lun
author_facet Lok, C. W.
Zin, A. A. M.
Mustafa, M. W.
Lo, Kueiming Lun
author_sort Lok, C. W.
building UTM Library
collection Institutional Repository
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
continent Asia
country Malaysia
description Genetic algorithms (GAs) are search methods based on the natural selection and natural genetics, while power flow studies, commonly known as load flow, form an important part of power system analysis. This paper presents the implemention of the simple genetic algorithm and constrained genetic algorithm to solve the load flow problem. It compares the performance of the simple genetic algorithm (SGA) and the constrained genetic algorithm (CGA) to solve the load flow problem. Numerical results on two test systems are presented.
format Conference or Workshop Item
id my.utm.eprints-7523
institution Universiti Teknologi Malaysia
publishDate 2003
record_format eprints
spelling my.utm.eprints-75232017-08-29T08:36:22Z http://eprints.utm.my/7523/ Load flow method using genetic algorithm Lok, C. W. Zin, A. A. M. Mustafa, M. W. Lo, Kueiming Lun TK Electrical engineering. Electronics Nuclear engineering Genetic algorithms (GAs) are search methods based on the natural selection and natural genetics, while power flow studies, commonly known as load flow, form an important part of power system analysis. This paper presents the implemention of the simple genetic algorithm and constrained genetic algorithm to solve the load flow problem. It compares the performance of the simple genetic algorithm (SGA) and the constrained genetic algorithm (CGA) to solve the load flow problem. Numerical results on two test systems are presented. 2003 Conference or Workshop Item PeerReviewed Lok, C. W. and Zin, A. A. M. and Mustafa, M. W. and Lo, Kueiming Lun (2003) Load flow method using genetic algorithm. In: IPEC 2003-6th International Power Engineering Conference.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Lok, C. W.
Zin, A. A. M.
Mustafa, M. W.
Lo, Kueiming Lun
Load flow method using genetic algorithm
title Load flow method using genetic algorithm
title_full Load flow method using genetic algorithm
title_fullStr Load flow method using genetic algorithm
title_full_unstemmed Load flow method using genetic algorithm
title_short Load flow method using genetic algorithm
title_sort load flow method using genetic algorithm
topic TK Electrical engineering. Electronics Nuclear engineering
url http://eprints.utm.my/7523/
url_provider http://eprints.utm.my/