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

Detalhes bibliográficos
Autor(a) principal: Fortes, Elenilson V.
Data de Publicação: 2022
Outros Autores: Martins, Luís Fabiano Barone, Miotto, Ednei Luiz, Araujo, Percival Bueno [UNESP], Macedo, Leonardo H. [UNESP], Romero, Rubén [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/243833
Resumo: The 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.
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spelling Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systemsArtificial bee colonyCurrent sensitivity modelFirefly algorithmPODPSSUPFCThe 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.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)PostprintUniversidade Estadual PaulistaInstituto Federal de GoiásInstituto Federal do ParanáUniversidade Tecnológica Federal do ParanáFAPESP: 2015/21972-6FAPESP: 2018/20355-1CAPES: 001CNPq: 305852/2017-5SpringerUniversidade Estadual Paulista (Unesp)Fortes, Elenilson V.Martins, Luís Fabiano BaroneMiotto, Ednei LuizAraujo, Percival Bueno [UNESP]Macedo, Leonardo H. [UNESP]Romero, Rubén [UNESP]2023-05-31T18:01:04Z2023-05-31T18:01:04Z2022-09-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf2195-38992195-3880http://hdl.handle.net/11449/24383310.1007/s40313-022-00942-x8132630603219451204096218915304073033007471842650000-0002-2491-62540000-0001-9178-06010000-0002-7744-254XengJournal of Control, Automation and Electrical Systemsinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESP2024-07-04T19:06:57Zoai:repositorio.unesp.br:11449/243833Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:04:59.053760Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
title Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
spellingShingle Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
Fortes, Elenilson V.
Artificial bee colony
Current sensitivity model
Firefly algorithm
POD
PSS
UPFC
title_short Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
title_full Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
title_fullStr Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
title_full_unstemmed Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
title_sort Bio-inspired metaheuristics applied to the parametrization of PI, PSS, and UPFC–POD controllers for small-signal stability improvement in power systems
author Fortes, Elenilson V.
author_facet Fortes, Elenilson V.
Martins, Luís Fabiano Barone
Miotto, Ednei Luiz
Araujo, Percival Bueno [UNESP]
Macedo, Leonardo H. [UNESP]
Romero, Rubén [UNESP]
author_role author
author2 Martins, Luís Fabiano Barone
Miotto, Ednei Luiz
Araujo, Percival Bueno [UNESP]
Macedo, Leonardo H. [UNESP]
Romero, Rubén [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Fortes, Elenilson V.
Martins, Luís Fabiano Barone
Miotto, Ednei Luiz
Araujo, Percival Bueno [UNESP]
Macedo, Leonardo H. [UNESP]
Romero, Rubén [UNESP]
dc.subject.por.fl_str_mv Artificial bee colony
Current sensitivity model
Firefly algorithm
POD
PSS
UPFC
topic Artificial bee colony
Current sensitivity model
Firefly algorithm
POD
PSS
UPFC
description The 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-16
2023-05-31T18:01:04Z
2023-05-31T18:01:04Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv 2195-3899
2195-3880
http://hdl.handle.net/11449/243833
10.1007/s40313-022-00942-x
8132630603219451
2040962189153040
7303300747184265
0000-0002-2491-6254
0000-0001-9178-0601
0000-0002-7744-254X
identifier_str_mv 2195-3899
2195-3880
10.1007/s40313-022-00942-x
8132630603219451
2040962189153040
7303300747184265
0000-0002-2491-6254
0000-0001-9178-0601
0000-0002-7744-254X
url http://hdl.handle.net/11449/243833
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Control, Automation and Electrical Systems
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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