Metaheuristic optimization algorithms for the optimal coordination of plug-in electric vehicle charging in distribution systems with distributed generation

Detalhes bibliográficos
Autor(a) principal: Arias, Nataly Bañol [UNESP]
Data de Publicação: 2017
Outros Autores: Franco, John F. [UNESP], Lavorato, Marina, Romero, Rubén [UNESP]
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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spelling 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