Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios

Detalhes bibliográficos
Autor(a) principal: Souza, Simone S.F. [UNESP]
Data de Publicação: 2015
Outros Autores: Romero, Ruben [UNESP], Pereira, Jorge, Saraiva, J. T.
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/PTC.2015.7232298
http://hdl.handle.net/11449/177670
Resumo: This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.
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spelling Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenariosDemand scenariosDistribution System ReconfigurationMixed-Integer Nonlinear Programming ProblemSpecialized Genetic Algorithm of Chu-BeasleyThis paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.Electrical Engineering Department UNESP - Univ. Estadual PaulistaINESC TEC Faculty of Economics University of PortoElectrical Engineering Department UNESP - Univ. Estadual PaulistaUniversidade Estadual Paulista (Unesp)University of PortoSouza, Simone S.F. [UNESP]Romero, Ruben [UNESP]Pereira, JorgeSaraiva, J. T.2018-12-11T17:26:34Z2018-12-11T17:26:34Z2015-08-31info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/PTC.2015.72322982015 IEEE Eindhoven PowerTech, PowerTech 2015.http://hdl.handle.net/11449/17767010.1109/PTC.2015.72322982-s2.0-84951325450Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2015 IEEE Eindhoven PowerTech, PowerTech 2015info:eu-repo/semantics/openAccess2024-07-04T19:11:50Zoai:repositorio.unesp.br:11449/177670Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:54:19.995744Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
title Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
spellingShingle Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
Souza, Simone S.F. [UNESP]
Demand scenarios
Distribution System Reconfiguration
Mixed-Integer Nonlinear Programming Problem
Specialized Genetic Algorithm of Chu-Beasley
title_short Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
title_full Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
title_fullStr Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
title_full_unstemmed Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
title_sort Specialized genetic algorithm of Chu-Beasley applied to the Distribution System Reconfiguration problem considering several demand scenarios
author Souza, Simone S.F. [UNESP]
author_facet Souza, Simone S.F. [UNESP]
Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
author_role author
author2 Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
University of Porto
dc.contributor.author.fl_str_mv Souza, Simone S.F. [UNESP]
Romero, Ruben [UNESP]
Pereira, Jorge
Saraiva, J. T.
dc.subject.por.fl_str_mv Demand scenarios
Distribution System Reconfiguration
Mixed-Integer Nonlinear Programming Problem
Specialized Genetic Algorithm of Chu-Beasley
topic Demand scenarios
Distribution System Reconfiguration
Mixed-Integer Nonlinear Programming Problem
Specialized Genetic Algorithm of Chu-Beasley
description This paper describes the application of the specialized genetic algorithm of Chu-Beasley to solve the Distribution System Reconfiguration, DSR, problem considering different demand scenarios. This algorithm is an approach inspired in the natural selection and evolution of species. The reconfiguration problem of distribution networks taking into account different demand scenarios aims at identifying the most adequate radial topology of a distribution system assuming that this topology is used for all demand scenarios under study. This search is driven by the minimization of the cost of energy losses in the network along a full operation year. The performance of the algorithm is evaluated considering test systems having 33, 70, 84 and 136 buses and a real system with 417 buses. The obtained results confirm the robustness and efficiency of the developed approach and its potential to be used in distribution control centers.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-31
2018-12-11T17:26:34Z
2018-12-11T17:26:34Z
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 http://dx.doi.org/10.1109/PTC.2015.7232298
2015 IEEE Eindhoven PowerTech, PowerTech 2015.
http://hdl.handle.net/11449/177670
10.1109/PTC.2015.7232298
2-s2.0-84951325450
url http://dx.doi.org/10.1109/PTC.2015.7232298
http://hdl.handle.net/11449/177670
identifier_str_mv 2015 IEEE Eindhoven PowerTech, PowerTech 2015.
10.1109/PTC.2015.7232298
2-s2.0-84951325450
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2015 IEEE Eindhoven PowerTech, PowerTech 2015
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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
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