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: | |
---|---|
Data de Publicação: | 2022 |
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/11449/237971 |
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. |
id |
UNSP_ed9476ededd7b61e69de078f17affb6e |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/237971 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
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.Goias Fed Inst Educ Sci & Technol, Av Presidente Juscelino Kubitschek 775, BR-75804714 Jatai, Go, BrazilParana Fed Inst Educ Sci & Technol, Av Doutor Tito Sn, BR-86400000 Jacarezinho, PR, BrazilFed Technol Univ Parana, R Cristo Rei 19, BR-85902490 Toledo, PR, BrazilSao Paulo State Univ, Ave Brasil 56, BR-15385000 Ilha Solteira, SP, BrazilSao Paulo State Univ, Ave Brasil 56, BR-15385000 Ilha Solteira, SP, BrazilSpringerGoias Fed Inst Educ Sci & TechnolParana Fed Inst Educ Sci & TechnolFed Technol Univ ParanaUniversidade Estadual Paulista (UNESP)Fortes, ElenilsonMartins, Luis Fabiano BaroneMiotto, Ednei LuizAraujo, Percival Bueno [UNESP]Macedo, Leonardo H. [UNESP]Romero, Ruben [UNESP]2022-11-30T16:20:58Z2022-11-30T16:20:58Z2022-09-16info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article16http://dx.doi.org/10.1007/s40313-022-00942-xJournal Of Control Automation And Electrical Systems. New York: Springer, 16 p., 2022.2195-3880http://hdl.handle.net/11449/23797110.1007/s40313-022-00942-xWOS:000854441300001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal Of Control Automation And Electrical Systemsinfo:eu-repo/semantics/openAccess2024-07-04T19:06:47Zoai:repositorio.unesp.br:11449/237971Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:39:42.196638Repositório 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 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 |
author_facet |
Fortes, Elenilson Martins, Luis Fabiano Barone Miotto, Ednei Luiz Araujo, Percival Bueno [UNESP] Macedo, Leonardo H. [UNESP] Romero, Ruben [UNESP] |
author_role |
author |
author2 |
Martins, Luis Fabiano Barone Miotto, Ednei Luiz Araujo, Percival Bueno [UNESP] Macedo, Leonardo H. [UNESP] Romero, Ruben [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Goias Fed Inst Educ Sci & Technol Parana Fed Inst Educ Sci & Technol Fed Technol Univ Parana Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Fortes, Elenilson Martins, Luis Fabiano Barone Miotto, Ednei Luiz Araujo, Percival Bueno [UNESP] Macedo, Leonardo H. [UNESP] Romero, Ruben [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 |
2022-11-30T16:20:58Z 2022-11-30T16:20:58Z 2022-09-16 |
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. New York: Springer, 16 p., 2022. 2195-3880 http://hdl.handle.net/11449/237971 10.1007/s40313-022-00942-x WOS:000854441300001 |
url |
http://dx.doi.org/10.1007/s40313-022-00942-x http://hdl.handle.net/11449/237971 |
identifier_str_mv |
Journal Of Control Automation And Electrical Systems. New York: Springer, 16 p., 2022. 2195-3880 10.1007/s40313-022-00942-x WOS:000854441300001 |
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 |
16 |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
Web of Science 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_ |
1808129448015298560 |