Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study

A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto genetic algorithm (NPGA), nondominated sorting genetic algorithm (NSGA), a...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abido, M.A. (author)
مؤلفون آخرون: unknown (author)
التنسيق: article
منشور في: 2003
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/14759/1/14759_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14759/2/14759_2.doc
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author Abido, M.A.
author2 unknown
author2_role author
author_facet Abido, M.A.
unknown
author_role author
dc.creator.none.fl_str_mv Abido, M.A.
unknown
dc.date.none.fl_str_mv 2003-07
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14759/1/14759_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14759/2/14759_2.doc
(2003) Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study. Power Engineering Society General Meeting, 2003, IEEE, 1.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14759/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description A comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto genetic algorithm (NPGA), nondominated sorting genetic algorithm (NSGA), and strength Pareto evolutionary algorithm (SPEA) have been developed and successfully applied to environmental/economic electric power dispatch (EED) problem. These multiobjective evolutionary algorithms have been individually examined and applied to the standard IEEE 30-bus test system. A feasibility check procedure has been developed and superimposed on MOEA to restrict the search to the feasible region of the problem space. The results of MOEA have been compared to those reported in the literature. The comparison shows the superiority of MOEA to the traditional multiobjective optimization techniques and confirms their potential to handle power system multiobjective optimization problems.
eu_rights_str_mv openAccess
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identifier_str_mv (2003) Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study. Power Engineering Society General Meeting, 2003, IEEE, 1.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14759
publishDate 2003
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative studyAbido, M.A.unknownComputerA comparative study of newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) applied to a nonlinear power system multiobjective optimization problem is presented in this paper. Specifically, Niched Pareto genetic algorithm (NPGA), nondominated sorting genetic algorithm (NSGA), and strength Pareto evolutionary algorithm (SPEA) have been developed and successfully applied to environmental/economic electric power dispatch (EED) problem. These multiobjective evolutionary algorithms have been individually examined and applied to the standard IEEE 30-bus test system. A feasibility check procedure has been developed and superimposed on MOEA to restrict the search to the feasible region of the problem space. The results of MOEA have been compared to those reported in the literature. The comparison shows the superiority of MOEA to the traditional multiobjective optimization techniques and confirms their potential to handle power system multiobjective optimization problems.IEEE2003-072020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14759/1/14759_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14759/2/14759_2.doc (2003) Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study. Power Engineering Society General Meeting, 2003, IEEE, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14759/info:eu-repo/semantics/openAccessoai::147592019-11-01T14:07:20Z
spellingShingle Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
Abido, M.A.
Computer
status_str publishedVersion
title Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
title_full Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
title_fullStr Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
title_full_unstemmed Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
title_short Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
title_sort Environmental/economic power dispatch using multiobjective evolutionary algorithms: a comparative study
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14759/1/14759_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14759/2/14759_2.doc