Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.epsr.2016.09.018 http://hdl.handle.net/11449/173664 |
Resumo: | This paper proposes three metaheuristic optimization techniques to solve the plug-in electric vehicle (PEV) charging coordination problem in electrical distribution systems (EDSs). Optimization algorithms based on tabu search, greedy randomized adaptive search procedure, and a novel hybrid optimization algorithm are developed with the objective of minimizing the total operational costs of the EDS, considering the impact of charging the electric vehicle batteries during a specific time period. The proposed methodologies determine a charging schedule for the electric vehicle batteries considering priorities according to the PEV owners charging preferences. A 449-node system with two distributed generation units was used to demonstrate the efficiency of the proposed methodologies, taking into account different PEV penetration levels. The results show that the charging schedule found makes the economic operation of the EDS possible, while satisfying operational and priority constraints. |
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Repositório Institucional da UNESP |
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Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generationElectrical distribution systemHybrid algorithmMetaheuristicPlug-in electric vehicle charging coordinationThis paper proposes three metaheuristic optimization techniques to solve the plug-in electric vehicle (PEV) charging coordination problem in electrical distribution systems (EDSs). Optimization algorithms based on tabu search, greedy randomized adaptive search procedure, and a novel hybrid optimization algorithm are developed with the objective of minimizing the total operational costs of the EDS, considering the impact of charging the electric vehicle batteries during a specific time period. The proposed methodologies determine a charging schedule for the electric vehicle batteries considering priorities according to the PEV owners charging preferences. A 449-node system with two distributed generation units was used to demonstrate the efficiency of the proposed methodologies, taking into account different PEV penetration levels. The results show that the charging schedule found makes the economic operation of the EDS possible, while satisfying operational and priority constraints.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)UNESP – Universidade Estadual Paulista Faculdade de Engenharia de Ilha Solteira Departamento de Engenharia Elétrica Ilha SolteiraPUC -Campinas - Pontifícia Universidade Católica de Campinas Faculdade de Engenharia ElétricaUNESP – Universidade Estadual Paulista Faculdade de Engenharia de Ilha Solteira Departamento de Engenharia Elétrica Ilha SolteiraUniversidade Estadual Paulista (Unesp)Faculdade de Engenharia ElétricaArias, Nataly Bañol [UNESP]Franco, John F. [UNESP]Lavorato, MarinaRomero, Rubén [UNESP]2018-12-11T17:07:09Z2018-12-11T17:07:09Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article351-361application/pdfhttp://dx.doi.org/10.1016/j.epsr.2016.09.018Electric Power Systems Research, v. 142, p. 351-361.0378-7796http://hdl.handle.net/11449/17366410.1016/j.epsr.2016.09.0182-s2.0-849921660582-s2.0-84992166058.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengElectric Power Systems Research1,048info:eu-repo/semantics/openAccess2024-07-04T19:06:47Zoai:repositorio.unesp.br:11449/173664Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:34:41.344521Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
title |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
spellingShingle |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation Arias, Nataly Bañol [UNESP] Electrical distribution system Hybrid algorithm Metaheuristic Plug-in electric vehicle charging coordination |
title_short |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
title_full |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
title_fullStr |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
title_full_unstemmed |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
title_sort |
Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation |
author |
Arias, Nataly Bañol [UNESP] |
author_facet |
Arias, Nataly Bañol [UNESP] Franco, John F. [UNESP] Lavorato, Marina Romero, Rubén [UNESP] |
author_role |
author |
author2 |
Franco, John F. [UNESP] Lavorato, Marina Romero, Rubén [UNESP] |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Faculdade de Engenharia Elétrica |
dc.contributor.author.fl_str_mv |
Arias, Nataly Bañol [UNESP] Franco, John F. [UNESP] Lavorato, Marina Romero, Rubén [UNESP] |
dc.subject.por.fl_str_mv |
Electrical distribution system Hybrid algorithm Metaheuristic Plug-in electric vehicle charging coordination |
topic |
Electrical distribution system Hybrid algorithm Metaheuristic Plug-in electric vehicle charging coordination |
description |
This paper proposes three metaheuristic optimization techniques to solve the plug-in electric vehicle (PEV) charging coordination problem in electrical distribution systems (EDSs). Optimization algorithms based on tabu search, greedy randomized adaptive search procedure, and a novel hybrid optimization algorithm are developed with the objective of minimizing the total operational costs of the EDS, considering the impact of charging the electric vehicle batteries during a specific time period. The proposed methodologies determine a charging schedule for the electric vehicle batteries considering priorities according to the PEV owners charging preferences. A 449-node system with two distributed generation units was used to demonstrate the efficiency of the proposed methodologies, taking into account different PEV penetration levels. The results show that the charging schedule found makes the economic operation of the EDS possible, while satisfying operational and priority constraints. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2018-12-11T17:07:09Z 2018-12-11T17:07:09Z |
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/10.1016/j.epsr.2016.09.018 Electric Power Systems Research, v. 142, p. 351-361. 0378-7796 http://hdl.handle.net/11449/173664 10.1016/j.epsr.2016.09.018 2-s2.0-84992166058 2-s2.0-84992166058.pdf |
url |
http://dx.doi.org/10.1016/j.epsr.2016.09.018 http://hdl.handle.net/11449/173664 |
identifier_str_mv |
Electric Power Systems Research, v. 142, p. 351-361. 0378-7796 10.1016/j.epsr.2016.09.018 2-s2.0-84992166058 2-s2.0-84992166058.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Electric Power Systems Research 1,048 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
351-361 application/pdf |
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_ |
1808129440203407360 |