A NOVEL PARTICLE SWARM OPTIMIZATION GUIDED GENETIC TO THE DISTRIBUTION NETWORK RECONFIGURATION PROBLEM WITH AN OBJECTIVE FUNCTION OF MINIMUM OPERATING AND POWER OUTAGE COSTS

Abstract

In operating the distribution network, the problem of reconfiguration distribution network according to the change of load to reduce power loss has partly reduced the operation cost of the distribution network but it can impact the reliability of power supply to the load. Therefore, in this study, we propose a hybrid algorithm that integrates two well established methods, including the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm for the problem of reconfiguration distribution network with the objective function of the with the objective function of reducing power loss considering operating costs and power outage costs on the distribution network. To demonstrate the performance of the proposed PSO-GA Algorithm simulations have implemented through MATLAB 2019ª and PSS/ADEPT software. Utilizing the IEEE 33-bus distribution system for the experiment. The results show that the algorithm provides decision-makers with a range of equivalent options when addressing the challenge of distribution network reconfiguration.