A genetic-based fuzzy logic power system stabilizer formultimachine power systems

This paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. Incorporation of GA in fuzzy logic power system stabilizers (FLPSSs) design will significantly reduc...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abido, M.A. (author)
مؤلفون آخرون: Abdel-Magid, Y.L. (author), unknown (author)
التنسيق: article
منشور في: 1997
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/14800/1/14800_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14800/2/14800_2.doc
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author Abido, M.A.
author2 Abdel-Magid, Y.L.
unknown
author2_role author
author
author_facet Abido, M.A.
Abdel-Magid, Y.L.
unknown
author_role author
dc.creator.none.fl_str_mv Abido, M.A.
Abdel-Magid, Y.L.
unknown
dc.date.none.fl_str_mv 1997-10
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14800/1/14800_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14800/2/14800_2.doc
(1997) A genetic-based fuzzy logic power system stabilizer formultimachine power systems. Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation'., 1997 IEEE International conference, 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/14800/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv A genetic-based fuzzy logic power system stabilizer formultimachine power systems
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description This paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. Incorporation of GA in fuzzy logic power system stabilizers (FLPSSs) design will significantly reduce the time consumed in the design process of FLPSSs. It is shown in this paper that the performance of FLPSS can be improved significantly by incorporating a genetic-based learning mechanism. The performance of the proposed GFLPSS under different disturbances is investigated. The results show the superiority of the proposed GFLPSS as compared to the classical PSS and its capability to enhance system damping to local as well as interarea modes of oscillations. The capability of the proposed GFLPSS to work cooperatively with the existing classical PSSs is also demonstrated
eu_rights_str_mv openAccess
format article
id KFUPM_b102ffb9a2589a570e43108380b747eb
identifier_str_mv (1997) A genetic-based fuzzy logic power system stabilizer formultimachine power systems. Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation'., 1997 IEEE International conference, 1.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14800
publishDate 1997
publisher.none.fl_str_mv IEEE
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repository.name.fl_str_mv
repository_id_str
spelling A genetic-based fuzzy logic power system stabilizer formultimachine power systemsAbido, M.A.Abdel-Magid, Y.L.unknownComputerThis paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. Incorporation of GA in fuzzy logic power system stabilizers (FLPSSs) design will significantly reduce the time consumed in the design process of FLPSSs. It is shown in this paper that the performance of FLPSS can be improved significantly by incorporating a genetic-based learning mechanism. The performance of the proposed GFLPSS under different disturbances is investigated. The results show the superiority of the proposed GFLPSS as compared to the classical PSS and its capability to enhance system damping to local as well as interarea modes of oscillations. The capability of the proposed GFLPSS to work cooperatively with the existing classical PSSs is also demonstratedIEEE1997-102020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14800/1/14800_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14800/2/14800_2.doc (1997) A genetic-based fuzzy logic power system stabilizer formultimachine power systems. Systems, Man, and Cybernetics, 1997. 'Computational Cybernetics and Simulation'., 1997 IEEE International conference, 1. enenhttps://eprints.kfupm.edu.sa/id/eprint/14800/info:eu-repo/semantics/openAccessoai::148002019-11-01T14:07:33Z
spellingShingle A genetic-based fuzzy logic power system stabilizer formultimachine power systems
Abido, M.A.
Computer
status_str publishedVersion
title A genetic-based fuzzy logic power system stabilizer formultimachine power systems
title_full A genetic-based fuzzy logic power system stabilizer formultimachine power systems
title_fullStr A genetic-based fuzzy logic power system stabilizer formultimachine power systems
title_full_unstemmed A genetic-based fuzzy logic power system stabilizer formultimachine power systems
title_short A genetic-based fuzzy logic power system stabilizer formultimachine power systems
title_sort A genetic-based fuzzy logic power system stabilizer formultimachine power systems
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14800/1/14800_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14800/2/14800_2.doc