Optimal reconfiguration of unbalanced distribution systems using a new hybrid Big Bang-Big Crunch algorithm for loss reduction

Distribution systems reconfiguration is a simple and low-cost method which without adding additional equipment in the network optimizes the utilization of distribution systems. In this paper, a new hybrid Big Bang-Big Crunch optimization (HBB-BC) algorithm is proposed to solve the optimal reconfiguration of unbalanced distribution systems for loss reduction. During the reconfiguration, constraints like being radial, avoiding load isolation as well as voltage/current limitations must be taken into consideration. Taking these constraints into account makes reconfiguration an optimization problem. The HBB-BC algorithm is an effective and powerful method that has high accuracy and fast convergence as well as its implementation is easy. This algorithm using the Particle Swarm Optimization (PSO) capacities improves the capability of the Big Bang-Big Crunch (BB-BC) algorithm for better exploration. In addition, the HBB-BC uses a mutation operator after position updating to avoid local optimum and to explore new search areas. The effectiveness of the proposed algorithm is demonstrated on two unbalanced distribution systems.

کلیدواژه ها:

Big Bang-Big Crunch ، Particle Swarm Optimization ، Unbalanced distribution system ، Optimal reconfiguration ، Loss reduction