Abstract

In this paper, optimal reconfiguration of a distribution systems is investigated as a low-cost method for optimized operation of these systems by using a multi-objective approach. The proposed approach considers minimization of power loss and interruption costs and switching numbers. In order to solve the optimization problem, the Hybrid Big Bang-Big Crunch algorithm (HBB-BC) is employed. The HBB-BC algorithm is one of the most recent powerful and efficient heuristic tools which despite its high precision and easy implementation, has a quit well convergence rate. For this purpose, in this paper the Big Bang-Big Crunch (BB-BC) algorithm is modified by introducing a mutation operator to enhance its exploration capability. Therefore optimization capacities of Particle Swam Optimization (PSO) algorithm are used to improve the exploration ability of the BB-BC algorithm and avoid the trapping into the local optimums. Hence the new approach using HBB-BC is introduced. Finally, the performance of the proposed approach is verified by simulation of the algorithm on two different test distribution systems and simulation results are compared to other methods. According to the results, the proposed approach has better performance in finding the global optimum and convergence rate and also in the system's optimal reconfiguration and restoration.

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