Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems

Detalhes bibliográficos
Autor(a) principal: Vargas, Rommel [UNESP]
Data de Publicação: 2018
Outros Autores: Romero, Ruben [UNESP], Franco, John F. [UNESP], IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/196648
Resumo: The optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.
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spelling Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution SystemsBiased random-key genetic algorithmelectrical distribution systemspower lossesreconfigurationThe optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.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)Sao Paulo State Univ, UNESP, Dept Elect Engn, BR-15385000 Ilha Solteira, BrazilSao Paulo State Univ, UNESP, Sch Energy Engn, BR-19274000 Rosana, BrazilSao Paulo State Univ, UNESP, Dept Elect Engn, BR-15385000 Ilha Solteira, BrazilSao Paulo State Univ, UNESP, Sch Energy Engn, BR-19274000 Rosana, BrazilFAPESP: 2015/21972-6FAPESP: 2017/02831-8IeeeUniversidade Estadual Paulista (Unesp)Vargas, Rommel [UNESP]Romero, Ruben [UNESP]Franco, John F. [UNESP]IEEE2020-12-10T19:51:41Z2020-12-10T19:51:41Z2018-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject5Proceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la). New York: Ieee, 5 p., 2018.2381-3571http://hdl.handle.net/11449/196648WOS:000518200300055Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la)info:eu-repo/semantics/openAccess2021-10-23T08:59:31Zoai:repositorio.unesp.br:11449/196648Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T08:59:31Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
title Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
spellingShingle Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
Vargas, Rommel [UNESP]
Biased random-key genetic algorithm
electrical distribution systems
power losses
reconfiguration
title_short Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
title_full Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
title_fullStr Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
title_full_unstemmed Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
title_sort Biased Random-Key Genetic Algorithm Applied to the Optimal Reconfiguration of Radial Distribution Systems
author Vargas, Rommel [UNESP]
author_facet Vargas, Rommel [UNESP]
Romero, Ruben [UNESP]
Franco, John F. [UNESP]
IEEE
author_role author
author2 Romero, Ruben [UNESP]
Franco, John F. [UNESP]
IEEE
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Vargas, Rommel [UNESP]
Romero, Ruben [UNESP]
Franco, John F. [UNESP]
IEEE
dc.subject.por.fl_str_mv Biased random-key genetic algorithm
electrical distribution systems
power losses
reconfiguration
topic Biased random-key genetic algorithm
electrical distribution systems
power losses
reconfiguration
description The optimal reconfiguration of radial Electrical Distribution Systems (EDSs) is a classical optimization problem that deals with the operation of the system and is of great interest to the electricity sector. Although there is a large number of approaches in the specialized literature to solve this problem, the solution of the reconfiguration problem for large-scale EDSs is still difficult. This paper proposes a method to solve the reconfiguration problem of EDSs that is based on the specialized metaheuristic Biased Random-Key Genetic Algorithm, which showed excellent performance on the solution of complex problems in operational research. Tests carried out using a wellknown EDS demonstrate the efficiency of the proposed method.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
2020-12-10T19:51:41Z
2020-12-10T19:51:41Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv Proceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la). New York: Ieee, 5 p., 2018.
2381-3571
http://hdl.handle.net/11449/196648
WOS:000518200300055
identifier_str_mv Proceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la). New York: Ieee, 5 p., 2018.
2381-3571
WOS:000518200300055
url http://hdl.handle.net/11449/196648
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings Of The 2018 Ieee Pes Transmission & Distribution Conference And Exhibition - Latin America (t&d-la)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 5
dc.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
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
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