Optimal placement of fault indicators using adaptive genetic algorithm
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Data
2018-01-29
Autores
Cruz, Hector Orellana [UNESP]
Bertequini Leao, Fabio [UNESP]
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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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Adaptive genetic algorithm, Electric distribution systems, Fault indicators, Service quality
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IEEE Power and Energy Society General Meeting, v. 2018-January, p. 1-5.