Active power loss minimization based hybrid Particle Swarm Optimization-Artificial Bee Colony (PSO-ABC) in large scale power systems (case study: 14 IEEE and 118 IEEE bus systems)

Abstract

Many decades ago researchers in different fields of science and engineering have been conducting the research on optimization to solve various constrained and unconstrained optimization problems using Particle Swarm Optimization (PSO). This pertinent optimization algorithm has been used in reactive power optimization as well. However, it suffers from premature convergence because it can be easily trapped into local optimum solutions. To improve both the exploration and the exploitation abilities of PSO, this research implements a new algorithm called “Hybrid Particle Swarm Optimization- Artificial Bee colony (PSO-ABC)” which is the hybrid algorithm that combines both Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms. The standard Particle Swarm Optimization (PSO) has better exploration ability but its exploitation ability is very poor. To address these crucial issues, two important modifications will be applied on the standard PSO. The first modification will be to improve the generation of particles in order to allow them to be well spread in search space; then for the second modification all particles which are idle (lazy) during the search process will be replaced by new ones (insertion of scout phase of Artificial Bee Colony Algorithm). The main objective of this research is to minimize the losses within the electric power system by not only satisfying various constraints but also by adjusting control variables (control the voltage at all generator buses, control the tap setting position for all transformers and control the size of shunt capacitors). This new algorithm is applied on both IEEE 14 Bus System and IEEE 118 Bus System to show its better performance in comparison with other cited in the literature review. The algorithm and simulation were developed in MATLAB 2015a and their have shown that the active power optimization using Hybrid PSO-ABC optimizes better than PSO does and gives accurate results comparing with the results obtained using PSO Algorithm. The algorithm base PSO has been test on IEEE 118-bus test system for reactive power optimization and it reduced the active power losses from 133.694MW up to 112.4116MW while by applying the Hybrid PSO-ABC the active power losses reduced up to 108.5942MW.