PSO Embedded Artificial Bee Colony Algorithm for Optimal Shunt Capacitor Allocation and Sizing in Radial Distribution Networks with Voltage Dependent Load Models

Abstract

This paper attempts to reduce power loss in radial distribution network and facilitates improvement in bus voltage profile by determining optimal locations and optimal sized shunt capacitors. Particle swarm optimization algorithm (PSO) is embedded with Artificial Bee Colony algorithm (ABC) to balance exploration and exploitation ability to improve the solution accuracy and the convergence rate of the ABC algorithm as Particle-ABC (PABC) algorithm. In the first formulation, the capacitor placement is based on loss sensitivity factors (LSF) and thereafter decides on the optimal rating of capacitors through the use of proposed hybrid algorithm (PABC).The second approach encircles the role of PABC algorithm to search for the optimal candidate nodes within the nodes nominated by LSF and the optimal sizing of shunt capacitors simultaneously in the pursuit of enhancing the performance of radial distribution network with the former approach. The procedure travels to examine the robustness of the strategy on 41 and 69 nodes test systems with different load models at different load conditions and the simulation results are compared with the heuristic techniques existing in the literature. The simulation results reveal the efficiency and robustness of the PABC to find the optimal solution for capacitor placement problem.