Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm

Detalhes bibliográficos
Autor(a) principal: Peñaloza, John
Data de Publicação: 2019
Outros Autores: Yumbla, Jairo, López, Julio, Padilha-Feltrin, Antonio [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ISGT-LA.2019.8895354
http://hdl.handle.net/11449/232941
Resumo: This paper presents the develop of a computational tool for solve the distribution network reconfiguration problem considering the power losses minimization and distributed generation. The proposed tool satisfies the operational constraints of systems, e.g., voltage limits in nodes and the current capacity of lines. The use of a MINLP and a Genetic Algorithm guarantees convergence to good quality solutions. This is a searching adaptive method - based on natural selection and natural genetic. It improves the solutions in combinatorial problems, in each iteration through their operators (selection, crossover and mutation). 14-Bus, 33-Bus and 69-bus test systems and 880-Bus real system were employed to show the effectiveness and satisfactory results of the proposed tool.
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spelling Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic AlgorithmDistribution systemsfeedersgenetic algorithmsMINLPoptimizationreconfigurationsubstationsThis paper presents the develop of a computational tool for solve the distribution network reconfiguration problem considering the power losses minimization and distributed generation. The proposed tool satisfies the operational constraints of systems, e.g., voltage limits in nodes and the current capacity of lines. The use of a MINLP and a Genetic Algorithm guarantees convergence to good quality solutions. This is a searching adaptive method - based on natural selection and natural genetic. It improves the solutions in combinatorial problems, in each iteration through their operators (selection, crossover and mutation). 14-Bus, 33-Bus and 69-bus test systems and 880-Bus real system were employed to show the effectiveness and satisfactory results of the proposed tool.University of Cuenca School of Electrical EngineeringSao Paulo State University Faculty of Engineering of Ilha SolteiraSao Paulo State University Faculty of Engineering of Ilha SolteiraSchool of Electrical EngineeringUniversidade Estadual Paulista (UNESP)Peñaloza, JohnYumbla, JairoLópez, JulioPadilha-Feltrin, Antonio [UNESP]2022-04-30T21:05:47Z2022-04-30T21:05:47Z2019-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ISGT-LA.2019.88953542019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019.http://hdl.handle.net/11449/23294110.1109/ISGT-LA.2019.88953542-s2.0-85075715343Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019info:eu-repo/semantics/openAccess2022-04-30T21:05:47Zoai:repositorio.unesp.br:11449/232941Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462022-04-30T21:05:47Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
title Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
spellingShingle Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
Peñaloza, John
Distribution systems
feeders
genetic algorithms
MINLP
optimization
reconfiguration
substations
title_short Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
title_full Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
title_fullStr Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
title_full_unstemmed Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
title_sort Optimal Distribution Network Reconfiguration with Distributed Generation using a Genetic Algorithm
author Peñaloza, John
author_facet Peñaloza, John
Yumbla, Jairo
López, Julio
Padilha-Feltrin, Antonio [UNESP]
author_role author
author2 Yumbla, Jairo
López, Julio
Padilha-Feltrin, Antonio [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv School of Electrical Engineering
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Peñaloza, John
Yumbla, Jairo
López, Julio
Padilha-Feltrin, Antonio [UNESP]
dc.subject.por.fl_str_mv Distribution systems
feeders
genetic algorithms
MINLP
optimization
reconfiguration
substations
topic Distribution systems
feeders
genetic algorithms
MINLP
optimization
reconfiguration
substations
description This paper presents the develop of a computational tool for solve the distribution network reconfiguration problem considering the power losses minimization and distributed generation. The proposed tool satisfies the operational constraints of systems, e.g., voltage limits in nodes and the current capacity of lines. The use of a MINLP and a Genetic Algorithm guarantees convergence to good quality solutions. This is a searching adaptive method - based on natural selection and natural genetic. It improves the solutions in combinatorial problems, in each iteration through their operators (selection, crossover and mutation). 14-Bus, 33-Bus and 69-bus test systems and 880-Bus real system were employed to show the effectiveness and satisfactory results of the proposed tool.
publishDate 2019
dc.date.none.fl_str_mv 2019-09-01
2022-04-30T21:05:47Z
2022-04-30T21:05:47Z
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/ISGT-LA.2019.8895354
2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019.
http://hdl.handle.net/11449/232941
10.1109/ISGT-LA.2019.8895354
2-s2.0-85075715343
url http://dx.doi.org/10.1109/ISGT-LA.2019.8895354
http://hdl.handle.net/11449/232941
identifier_str_mv 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019.
10.1109/ISGT-LA.2019.8895354
2-s2.0-85075715343
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019
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
_version_ 1803047253073461248

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