Distributed generator sizing: an iteration particle swarm optimization approach

Different types of optimization method have been used in many applications for solving the complex system. Particle Swarm Optimization (PSO) is one of the most popular optimization methods that have been widely used. However, the original PSO have its own limitation. Thus, many researchers have introduced the modification on PSO to improve the performance and efficiency. In this paper, the concept of Iterative Particle Swarm Optimization (IPSO) method is implemented in sizing the DG units and the performance compared with two others optimization methods which are Evolutionary Programming (EP) and Artificial Immune System (AIS). By applying the extra parameter in new velocity of each particle before updating the position, IPSO gave the superior results compared to EP and AIS for achieving the global optimal values. The performance of IPSO in DG sizing has been tested on 69 bus distribution system with 4 units of DG that operate in PV mode. In terms of power loss reduction and voltage profile, the IPSO gives superior results than EP and AIS obtained