Multiobjective optimal power flow using strength Pareto evolutionary algorithm
In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new s...
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| Format: | article |
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2004
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| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc |
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| _version_ | 1864513394222039040 |
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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 | 2004-09 2020 |
| dc.format.none.fl_str_mv | application/pdf application/msword |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc (2004) Multiobjective optimal power flow using strength Pareto evolutionary algorithm. Universities Power Engineering Conference, 2004. UPEC 2004. 39th International, 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/14605/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective OPF problem. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_b5791e38f657f3e691cdea4b076869be |
| identifier_str_mv | (2004) Multiobjective optimal power flow using strength Pareto evolutionary algorithm. Universities Power Engineering Conference, 2004. UPEC 2004. 39th International, 1. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::14605 |
| publishDate | 2004 |
| publisher.none.fl_str_mv | IEEE |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Multiobjective optimal power flow using strength Pareto evolutionary algorithmAbido, M.A.unknownComputerIn this paper, a novel multiobjective evolutionary algorithm for optimal power flow (OPF) problem is presented. The OPF problem is formulated as a nonlinear constrained multiobjective optimization problem where the fuel cost and the voltage stability index are to be minimized simultaneously. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. A hierarchical clustering algorithm is imposed to provide the decision maker with a representative and manageable Pareto-optimal set. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal nondominated solutions in one single run. The results also show the superiority of the proposed approach and confirm its potential to solve the multiobjective OPF problem.IEEE2004-092020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc (2004) Multiobjective optimal power flow using strength Pareto evolutionary algorithm. Universities Power Engineering Conference, 2004. UPEC 2004. 39th International, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14605/info:eu-repo/semantics/openAccessoai::146052019-11-01T14:06:35Z |
| spellingShingle | Multiobjective optimal power flow using strength Pareto evolutionary algorithm Abido, M.A. Computer |
| status_str | publishedVersion |
| title | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| title_full | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| title_fullStr | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| title_full_unstemmed | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| title_short | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| title_sort | Multiobjective optimal power flow using strength Pareto evolutionary algorithm |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/14605/1/14605_1.pdf https://eprints.kfupm.edu.sa/id/eprint/14605/2/14605_2.doc |