Author : Pruthviraja L and Ramesh G B

Since many years power system field existed with solving of one or more non-linear optimization problems. The existing analytical methods suffer from slow convergence, especially with increase in system size and non linearity’s. Particle swarm optimization (PSO) is known to solve large-scale nonlinear optimization problems effectively. This paper presents an overview of PSO and its applications to load flow analysis to minimize the active and reactive power loss with increased speed of convergence and more acceptable results. Several particles in feasible solutions were used to lead swarm’s motion and update. The present new PSO algorithm requires the less memory space required to establish the global optimal solution. Simulation results of standard IEEE 30-bus system have shown that this algorithm can improve the searching of best particles and voltage stability, with a fast convergence. It was proved to be efficient and practical during the active and reactive power loss minimization.

Keywords: Local best, Global best, Power Loss minimization, Evolutionary computation, Particle Swarm Optimization (PSO)

Article published in International Journal of Current Engineering and Technology, Vol.4, No.6 (Dec-2014)