Impacts of the Load Models on Optimal Sizing and Siting of Distributed Generation in Distribution System

This paper presents a novel Butterfly-PSO optimization technique for optimal sizing and siting of the distributed generations (DGs). The validity of the evaluated results is confirmed by comparing with well known Genetic Algorithm (GA) and Standard or Conventional Particle Swarm Optimization (PSO). To exhibit it’s compatibility in terms of load management an impact of different load models on the sizing and siting of DG has also been presented in this work. The fitness evolution function explored in this work is the multi-objective function, which is based on the three significant indexes such as active power loss, reactive power loss and voltage deviation index. The optimal solution is obtained by minimizing the multi-objective fitness function (FMO) using BF-PSO, GA, PSO and optimization technique. The comparison of the different optimization techniques is given for the different type of load models such as constant, industrial, residential and commercial load models. The results clearly show that the BF-PSO technique presents the superior solution in terms of compatibility as well as computation time and efforts both.