A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems

A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper to improve power system dynamic stability. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is train...

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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: 1998
الموضوعات:
الوصول للمادة أونلاين:https://eprints.kfupm.edu.sa/id/eprint/14205/1/14205_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14205/2/14205_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 1998-11
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14205/1/14205_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14205/2/14205_2.doc
(1998) A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems. Power Systems, IEEE Transactions on, 13.
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/14205/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper to improve power system dynamic stability. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a single machine infinite bus system and a multimachine power system subject to major disturbances are investigated. The performance of the proposed FBFN PSS is compared with that of conventional (CPSS). The results show the capability of the proposed FBFN PSS to enhance the system damping of local modes of oscillations over a wide range of operating conditions. The decentralized nature of the proposed FBFN PSS makes it easy to install and tune
eu_rights_str_mv openAccess
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identifier_str_mv (1998) A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems. Power Systems, IEEE Transactions on, 13.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14205
publishDate 1998
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling A hybrid neuro-fuzzy power system stabilizer for multimachine powersystemsAbido, M.A.Abdel-Magid, Y.L.unknownComputerA fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper to improve power system dynamic stability. The proposed FBFN based PSS provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed FBFN is trained over a wide range of operating conditions in order to re-tune the PSS parameters in real-time based on machine loading conditions. The orthogonal least squares (OLS) learning algorithm is developed for designing an adequate and parsimonious FBFN model. Time domain simulations of a single machine infinite bus system and a multimachine power system subject to major disturbances are investigated. The performance of the proposed FBFN PSS is compared with that of conventional (CPSS). The results show the capability of the proposed FBFN PSS to enhance the system damping of local modes of oscillations over a wide range of operating conditions. The decentralized nature of the proposed FBFN PSS makes it easy to install and tuneIEEE1998-112020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14205/1/14205_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14205/2/14205_2.doc (1998) A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems. Power Systems, IEEE Transactions on, 13. enenhttps://eprints.kfupm.edu.sa/id/eprint/14205/info:eu-repo/semantics/openAccessoai::142052019-11-01T14:04:43Z
spellingShingle A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
Abido, M.A.
Computer
status_str publishedVersion
title A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
title_full A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
title_fullStr A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
title_full_unstemmed A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
title_short A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
title_sort A hybrid neuro-fuzzy power system stabilizer for multimachine powersystems
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14205/1/14205_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14205/2/14205_2.doc