Publicação: Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm
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Data
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Coorientador
Pós-graduação
Curso de graduação
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Editor
Ieee
Tipo
Trabalho apresentado em evento
Direito de acesso
Acesso aberto
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.
Descrição
Palavras-chave
Adaptive genetic algorithm, Fault indicators, Service quality, Electric distribution systems
Idioma
Inglês
Como citar
2017 Ieee Power & Energy Society General Meeting. New York: Ieee, 5 p., 2017.
