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Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems

dc.contributor.authorFortes, Elenilson V.
dc.contributor.authorMartins, Luís Fabiano Barone
dc.contributor.authorMiotto, Ednei Luiz
dc.contributor.authorAraujo, Percival Bueno [UNESP]
dc.contributor.authorMacedo, Leonardo H. [UNESP]
dc.contributor.authorRomero, Rubén [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2023-05-31T18:01:04Z
dc.date.available2023-05-31T18:01:04Z
dc.date.issued2022-09-16
dc.description.abstractThe firefly algorithm (FA) and the artificial bee colony (ABC) algorithm are used in this study to perform a coordinated parametrization of the proportional-integral and supplementary damping controllers, i.e., power system stabilizers (PSSs) and the unified power flow controller (UPFC)–power oscillation damping set. The parametrization obtained for the controllers should allow them to damp the low-frequency oscillatory modes in the power system for different loading scenarios. The power system dynamics is represented using a model based on current injections, known as the current sensitivity model, which implies that a formulation by current injections for the UPFC should be formulated. To validate the proposed optimization techniques and the current injection model for the UPFC for small-signal stability, simulations are carried out under two distinct perspectives, namely, static and dynamic analysis, using the New England system. The results demonstrated the effectiveness of the UPFC’s current injection model. Moreover, it was possible to verify that the FA performed better than the ABC algorithm to solve the discussed problem, accrediting both the UPFC current injection model and the FA algorithm as new tools for small-signal stability analysis in electrical power systems.en
dc.description.affiliationUniversidade Estadual Paulista
dc.description.affiliationInstituto Federal de Goiás
dc.description.affiliationInstituto Federal do Paraná
dc.description.affiliationUniversidade Tecnológica Federal do Paraná
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIdFAPESP: 2015/21972-6
dc.description.sponsorshipIdFAPESP: 2018/20355-1
dc.description.sponsorshipIdCAPES: 001
dc.description.sponsorshipIdCNPq: 305852/2017-5
dc.description.versionPostprinten
dc.identifier.doi10.1007/s40313-022-00942-x
dc.identifier.issn2195-3899
dc.identifier.issn2195-3880
dc.identifier.lattes8132630603219451
dc.identifier.lattes2040962189153040
dc.identifier.lattes7303300747184265
dc.identifier.orcid0000-0002-2491-6254
dc.identifier.orcid0000-0001-9178-0601
dc.identifier.orcid0000-0002-7744-254X
dc.identifier.urihttp://hdl.handle.net/11449/243833
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofJournal of Control, Automation and Electrical Systemsen
dc.rights.accessRightsAcesso abertopt
dc.subjectArtificial bee colonyen
dc.subjectCurrent sensitivity modelen
dc.subjectFirefly algorithmen
dc.subjectPODen
dc.subjectPSSen
dc.subjectUPFCen
dc.titleBio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systemsen
dc.typeArtigopt
dspace.entity.typePublication
relation.isOrgUnitOfPublication85b724f4-c5d4-4984-9caf-8f0f0d076a19
relation.isOrgUnitOfPublication.latestForDiscovery85b724f4-c5d4-4984-9caf-8f0f0d076a19
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Engenharia, Ilha Solteirapt
unesp.departmentEngenharia Elétrica - FEISpt

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