Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
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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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 |
|
_version_ |
1803047231931023360 |