Bio-Inspired Metaheuristics Applied to the Parametrization of PI, PSS, and UPFC–POD Controllers for Small-Signal Stability Improvement in Power Systems
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1007/s40313-022-00942-x http://hdl.handle.net/11449/249157 |
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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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.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Goiás Federal Institute of Education Science and Technology, Av. Presidente Juscelino Kubitschek 775, Residencial Flamboyant, GOParaná Federal Institute of Education Science and Technology, Av. Doutor Tito s/n, Jardim Panorama, PRFederal Technological University of Paraná, R. Cristo Rei, 19, Vila Becker, PRSão Paulo State University, Avenida Brasil, 56, Centro, SPSão Paulo State University, Avenida Brasil, 56, Centro, SPCAPES: 001FAPESP: 2015/21972-6FAPESP: 2018/20355-1CNPq: 305852/2017-5and TechnologyFederal Technological University of ParanáUniversidade Estadual Paulista (UNESP)Fortes, Elenilson V.Martins, Luís Fabiano BaroneMiotto, Ednei LuizAraujo, Percival Bueno [UNESP]Macedo, Leonardo H. [UNESP]Romero, Rubén [UNESP]2023-07-29T14:03:57Z2023-07-29T14:03:57Z2023-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article121-136http://dx.doi.org/10.1007/s40313-022-00942-xJournal of Control, Automation and Electrical Systems, v. 34, n. 1, p. 121-136, 2023.2195-38992195-3880http://hdl.handle.net/11449/24915710.1007/s40313-022-00942-x2-s2.0-85138145347Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Control, Automation and Electrical Systemsinfo:eu-repo/semantics/openAccess2024-07-04T19:06:03Zoai:repositorio.unesp.br:11449/249157Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:04:57.128814Repositório 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 |
and Technology Federal Technological University of Paraná 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 |
2023 |
dc.date.none.fl_str_mv |
2023-07-29T14:03:57Z 2023-07-29T14:03:57Z 2023-02-01 |
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 |
http://dx.doi.org/10.1007/s40313-022-00942-x Journal of Control, Automation and Electrical Systems, v. 34, n. 1, p. 121-136, 2023. 2195-3899 2195-3880 http://hdl.handle.net/11449/249157 10.1007/s40313-022-00942-x 2-s2.0-85138145347 |
url |
http://dx.doi.org/10.1007/s40313-022-00942-x http://hdl.handle.net/11449/249157 |
identifier_str_mv |
Journal of Control, Automation and Electrical Systems, v. 34, n. 1, p. 121-136, 2023. 2195-3899 2195-3880 10.1007/s40313-022-00942-x 2-s2.0-85138145347 |
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 |
121-136 |
dc.source.none.fl_str_mv |
Scopus 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 |
|
_version_ |
1808128605972070400 |