Optimal Allocation of Distributed Energy Resources in a Distribution System

Abstract

Power loss reduction is one the main reasons for placing distributed energy resources in distribution systems. In addition, improvement in voltage profile is another advantage which the distributed energy resources offers. Heuristic optimization techniques are robust and provide near optimal solutions. In this paper, two different heuristic optimization techniques namely differential evolution (DE) and teaching learning combined with harmony search (TLCHS) have been used for placement of distributed generation units at appropriate locations in a radial distribution system (RDS) with an objective to minimize power losses and to improve bus voltage profiles. TCLHS optimization technique is a combination of two well-known techniques namely teaching learning (TL) and harmony search (HS). The (DE) is an evolutionary algorithm, which is a powerful global optimizer for solving continuous optimization problem. In DE only three input parameters are needed to control the search process, namely the size of population (N), the mutation parameter (F) and the crossover rate (CR). The TLCHS and DE optimization algorithms have been applied on IEEE 33-bus and 69-bus systems. The results exhibit the effectiveness and feasibility of the two algorithms along with the considerable reduction in power losses.