Optimal switch placement in distribution power system using linear fragmented particle swarm optimization algorithm preprocessed by GA

In recent years, Distributed Generation (DG) has become an efficient alternative to traditional distribution systems, therefore new algorithms should be able to solve problems in presence of DGs. Reliability improvement and cost reduction are two important goals of utilities which are usually in opposite of each other. The Islanding operation scheme is dynamically formed when fault occurs, which is based on the location of the fault, location of switches and the actual status of distribution network operation before fault occurs. Optimal allocation of switches in distribution power systems can improve reliability of a power system by reducing the total time of fault detection, isolation and restoration. In this paper, a three-state approach inspired from the discrete version of a powerful Particle swarm optimization (PSO) algorithm is developed and presented to determine the optimum number and locations of two types of switches (sectionalizing and breaker switches) in radial distribution systems. The novelty of the proposed algorithm is a new linear method for fragmentation particles and probability calculation of switch type offer for each candidate locations. Genetic preprocessing algorithm is used in proposed algorithm for generating suitable first population. It enhances the PSO algorithm and decreases time of optimization. RBTS-BUS4 test system indicates advantages of the algorithm.