A Comparative Study on Particle Swarm Optimization for Optimal Steady-State Performance of Power Systems

Abstract—In this paper, three new particle swarm optimization (PSO) algorithms are compared with the state of the art PSO al-gorithms for the optimal steady-state performance of power sys-tems, namely, the reactive power and voltage control. Two of the three introduced, the enhanced GPAC PSO and LPAC PSO, are based on the global and local-neighborhood variant PSOs, respec-tively. They are hybridized with the constriction factor approach together with a new operator, reflecting the physical force of pas-sive congregation observed in swarms. The third one is based on a new concept of coordinated aggregation (CA) and simulates how the achievements of particles can be distributed in the swarm af-fecting its manipulation. Specifically, each particle in the swarm is attracted only by particles with better achievements than its own, with the exception of the particle with the best achievement, which moves randomly as a “crazy ” agent. The obtained results by the enhanced general passive congregation (GPAC), local passive con-gregation (LPAC), and CA on the IEEE 30-bus and IEEE 118-bus systems are compared with an interior point (IP)-based OPF al-gorithm, a conventional PSO algorithm, and an evolutionary algo-rithm (EA), demonstrating the excellent performance of the pro-posed PSO algorithms. Index Terms—Coordinated aggregation (CA), particle swarm optimization (PSO), passive congregation, reactive power control, voltage control. I