Optimal placement of fault indicators using adaptive genetic algorithm

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorCruz, Hector Orellana-
Autor(es): dc.creatorBertequini Leao, Fabio-
Data de aceite: dc.date.accessioned2025-08-21T22:14:52Z-
Data de disponibilização: dc.date.available2025-08-21T22:14:52Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2018-01-29-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/PESGM.2017.8273897-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/228540-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/228540-
Descrição: dc.descriptionThis 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.-
Descrição: dc.descriptionDepartment of Electrical Engineering FEIS Sao Paulo State University Ilha-
Descrição: dc.descriptionDepartment of Electrical Engineering FEIS Sao Paulo State University Ilha-
Formato: dc.format1-5-
Idioma: dc.languageen-
Relação: dc.relationIEEE Power and Energy Society General Meeting-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAdaptive genetic algorithm-
Palavras-chave: dc.subjectElectric distribution systems-
Palavras-chave: dc.subjectFault indicators-
Palavras-chave: dc.subjectService quality-
Título: dc.titleOptimal placement of fault indicators using adaptive genetic algorithm-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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