Implimentation of Evolutionary Particle Swarm Optimization in Distributed Generation Sizing

Received Jan 4, 2012 Revised Feb 12, 2012 Accepted Feb 14, 2012 The size of Distributed Generation (DG) is crucial in order to reduce the impact of installing a DG in the distribution Network. Without proper connection and sizing of DG, it will cause the power loss to increase and also might cause the voltage in the network to operate beyond the acceptable limit. Therefore, many researchers have given concentration on the formulation optimization technique to regulate the DG’s output to compute its optimal size. The distinctions between these techniques were on the ability to acquire the optimal value with hasty computing time for solving the problems. PSO is among the popular optimization methods due to its simplicity and satisfying value. However, the computing time for PSO is dependant to the problem that needs to be solved. In this paper, the concept of Evolutionary Particle Swarm Optimization (EPSO) method is implemented in sizing the DG units. By substituting the concept of Evolutionary Programming (EP) in some part of Particle Swarm Optimization (PSO) algorithm process, it will make the process of convergence become faster. The algorithm has been tested in 33bus distribution system with 3 units of DG that operate in PV mode. Its performance was compared with the performance when using the traditional PSO and without using any optimization method. In terms of power loss reduction and voltage profile, the EPSO can give similar performance as PSO. Moreover, the EPSO requires less number of iteration and computing time to converge. Thus, it can be said that the EPSO is superior in term of speed, while maintaining the same performance. Keyword: