A New Hybrid Evolutionary Algorithm for Reliable Multi-Objective Distribution Feeder Reconfiguration

Reducing electricity losses is the main objective indistribution feeder reconfiguration (DFR) problem.Distribution feeder reconfiguration is an optimization problemin power system which is performed through changingswitching state. In this study, distribution feederreconfiguration is optimized in the presence of distributedgenerators (DGs). In common DFR problems, reliabilityconstraint is not satisfied and power losses or voltage deviationof buses is selected as the objective function. In this study,multi-objective problem is considered as a combination ofreliability index, power losses and operation cost. By addingreliability index, the problem becomes more complex andrequires an accurate method for solving multi-objectiveoptimization problem. For this purpose, in this paper proposeda new hybrid evolutionary algorithm for solving the DFRproblem. The proposed hybrid evolutionary algorithm is thecombination of Particle Swarm Optimization (PSO) andModified Shuffled Frog Leaping Algorithm (MSFLA,) called(PSO-MSFLA). In order to investigate efficiency of theproposed method, 70-bus test system is tested and the resultsare compared with SFLA and PSO algorithms.

Keywords:

distribution feeder reconfiguration (DFR) , distributed generators (DGs) , Improved particle swarm optimization (IPSO) , multi-objective optimization , Energy not supplied (ENS)