<![CDATA[In this paper an Improved Particle Swarm Optimization (IPSO) algorithm is proposed to solve the optimal reactive power Problem. In order to overcome the drawbacks of standard genetic algorithm (GA) and particle swarm optimization (PSO) , some improved mechanisms based on non-linear ranking selection, competition and selection among several crossover offspring and adaptive change of mutation scaling are adopted in the genetic algorithm, & dynamical parameters are adopted in PSO. The new population is produced through three approaches to improve the global optimization performance, which are elitist strategy, PSO strategy and enhanced genetic algorithm strategy. The effectiveness of the proposed algorithm has been compared with Gas and PSO, synthesizing a circular array, a linear array and a base station array. In order to evaluate the efficiency of the proposed algorithm, it has been tested in standard IEEE 118 & practical 191 bus test systems and compared other algorithms. Simulation results show that real power loss considerably reduced and control variables are within the limits.]]>
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