Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm

Cruz, Hector Orellana [UNESP]; Leao, Fabio Bertequini [UNESP]; IEEE

Optimal Placement of Fault Indicators using Adaptive Genetic Algorithm

Date

2017-01-01

Authors

Cruz, Hector Orellana

Leao, Fabio Bertequini

IEEE

Publisher

Ieee

Type

Work presented at event

Access right

Acesso aberto

Abstract

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.