A new hybrid PSOGSA algorithm for optimal allocation and sizing of capacitor banks in RDS

Abstract

In this paper, a novel hybrid population-based algorithm (PSOGSA) is implemented with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) for optimal placement and sizing of capacitor banks in Radial Distribution Systems (RDS). The proposed methodology is provided in two stages. First, the most critical buses for installing capacitors are evaluated using Loss Sensitivity Factors (LSF). Then the new approach PSOGSA is proposed to evaluate the optimal sitings of capacitors and their sizing from the selected buses. In order to validate the proposed approach, the evaluated results have been compared with other algorithms such as, Genetic Algorithm (GA), Plant Growth Simulation Algorithm (PGSA), Fuzzy-Genetic Algorithm (Fuzzy-GA), Gravitational Search Algorithm (GSA), Simulated Annealing (SA), Particle Swarm Optimization (PSO), Direct Search Algorithm (DSA), Teaching Learning Based Optimization (TLBO), Flower Pollination Algorithm (FPA), and Cuckoo Search Algorithm (CSA). The proposed algorithm has been tested on different test systems as 33-bus, and 69-bus IEEE standard radial distribution systems. The numerical results show that the effectiveness and capability with high performance of the proposed scheme to estimate the optimal solutions for minimizing the system power losses, enhancing the voltage profile and maximizing the net savings as compared as other techniques. The system results have been obtained by Matlab package.