IMPROVED PSO TECHNIQUE & ITS APPLICATION

Abstract

In this report, Improved Particle Swarm Optimization (Improved PSO) method is employed to deal with the reactive power optimization in a power system. The objective is to overcome the drawbacks of the basic PSO method and apply this Improved PSO method to optimize reactive power flow in a Power System by minimizing the Real power losses whilst maintaining acceptable voltage profiles. PSO is a population based stochastic optimization technique developed by James Kennedy and Russell Eberhart in 1995 by observing the behaviour of organisms in a swarm and deals with continuous and discrete variables. The original PSO suffer, from premature convergence i.e., PSO traps in local optima when the function to be optimized is irregular or having multiple local optimum points. To overcome this, basic method is improved to increase the performance in finding global optima. Reactive power optimization by minimizing real power losses in a power system is a kind of Optimal Power Flow (OPF) problem. This report presents Improved PSO algorithm for optimal settings of OPF problem control variables. Incorporation of Improved PSO as a derivative-free optimization technique in solving OPF problem_ significantly relieves the assumptions imposed on the optimized objective function. The proposed approach has been examined and tested on the standard IEEE 30-bus test system. The results of Improved PSO method are compared with .the results obtained by applying basic PSO method and Genetic Algorithm (GA). These results show that the Improved PSO method can get better results within lesser number of iterations with guaranteed convergence