Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm

Detalhes bibliográficos
Autor(a) principal: Cruz, Hector Orellana [UNESP]
Data de Publicação: 2017
Outros Autores: Leao, Fabio Bertequini [UNESP], IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/163964
Resumo: This work proposes the Adaptive Genetic Algorithm (AGA) to solve the problem of Fault Indicator (FI) placement in electric distribution systems to improve customer service quality. The AGA is developed to obtain the best configuration for the placement of FIs in the system reducing the annual cost of energy not supplied (CENS) and the annual FI placement investment cost (CINV). The AGA uses dynamically calibrated crossover and mutation rates based on the diversity of each population in the generation. The algorithm is tested using three electric distribution systems and the results shown that AGA is efficient, robust and adequate to placement of FI for improving the service quality in electric distribution systems.
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spelling Optimal Placement of Fault Indicators using Adaptive Genetic AlgorithmAdaptive genetic algorithmFault indicatorsService qualityElectric distribution systemsThis work proposes the Adaptive Genetic Algorithm (AGA) to solve the problem of Fault Indicator (FI) placement in electric distribution systems to improve customer service quality. The AGA is developed to obtain the best configuration for the placement of FIs in the system reducing the annual cost of energy not supplied (CENS) and the annual FI placement investment cost (CINV). The AGA uses dynamically calibrated crossover and mutation rates based on the diversity of each population in the generation. The algorithm is tested using three electric distribution systems and the results shown that AGA is efficient, robust and adequate to placement of FI for improving the service quality in electric distribution systems.Sao Paulo State Univ, FEIS, Dept Elect Engn, Ilha Solteria, BrazilSao Paulo State Univ, FEIS, Dept Elect Engn, Ilha Solteria, BrazilIeeeUniversidade Estadual Paulista (Unesp)Cruz, Hector Orellana [UNESP]Leao, Fabio Bertequini [UNESP]IEEE2018-11-26T17:48:35Z2018-11-26T17:48:35Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject52017 Ieee Power & Energy Society General Meeting. New York: Ieee, 5 p., 2017.1944-9925http://hdl.handle.net/11449/163964WOS:000426921800154Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2017 Ieee Power & Energy Society General Meetinginfo:eu-repo/semantics/openAccess2021-10-23T21:44:23Zoai:repositorio.unesp.br:11449/163964Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-23T21:44:23Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
title Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
spellingShingle Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
Cruz, Hector Orellana [UNESP]
Adaptive genetic algorithm
Fault indicators
Service quality
Electric distribution systems
title_short Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
title_full Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
title_fullStr Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
title_full_unstemmed Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
title_sort Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
author Cruz, Hector Orellana [UNESP]
author_facet Cruz, Hector Orellana [UNESP]
Leao, Fabio Bertequini [UNESP]
IEEE
author_role author
author2 Leao, Fabio Bertequini [UNESP]
IEEE
author2_role author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Cruz, Hector Orellana [UNESP]
Leao, Fabio Bertequini [UNESP]
IEEE
dc.subject.por.fl_str_mv Adaptive genetic algorithm
Fault indicators
Service quality
Electric distribution systems
topic Adaptive genetic algorithm
Fault indicators
Service quality
Electric distribution systems
description This work proposes the Adaptive Genetic Algorithm (AGA) to solve the problem of Fault Indicator (FI) placement in electric distribution systems to improve customer service quality. The AGA is developed to obtain the best configuration for the placement of FIs in the system reducing the annual cost of energy not supplied (CENS) and the annual FI placement investment cost (CINV). The AGA uses dynamically calibrated crossover and mutation rates based on the diversity of each population in the generation. The algorithm is tested using three electric distribution systems and the results shown that AGA is efficient, robust and adequate to placement of FI for improving the service quality in electric distribution systems.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
2018-11-26T17:48:35Z
2018-11-26T17:48:35Z
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 2017 Ieee Power & Energy Society General Meeting. New York: Ieee, 5 p., 2017.
1944-9925
http://hdl.handle.net/11449/163964
WOS:000426921800154
identifier_str_mv 2017 Ieee Power & Energy Society General Meeting. New York: Ieee, 5 p., 2017.
1944-9925
WOS:000426921800154
url http://hdl.handle.net/11449/163964
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2017 Ieee Power & Energy Society General Meeting
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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