Application Of Particle Swarm Optimization Algorithms In Reactive Power Optimization

Power system voltage and reactive power control is an effective measure to keeppower system safety and economic,and an important method to improve voltageequlity. The purpose of reactive power optimization is to determine the optimalcontrol strategy and optimize sizes and locations of Var sources.It is important to distribute the reactive power in reason. Reactive poweroptimization is an effective measure to reduce network losses. It can gain the ends ofreducing active power loss by adjusting devices of power network and changing thepower float distributing in network. So the Reactive power optimization is not onlyeconomical but also secure.Psrticle Swarm Optimization(PSO) is an optimal technique based on population,which is the same to other evolutionary computations. It is a stochastic globaloptimization technique.The particle swarm algorithms find optimal regions ofcomplex search spaces through the interaction of individuals in a population ofparticles. Particle swarm optimization has become the hotspot of evolutionarycomputation because of its excellent performance and simple for implement.Thealgorithm is reliable and applicable to almost all of problems in multiple-dimensions,nonlinear, complex constrained programming. In this paper, classical particle swarmoptimizer algorithm and its several variants and some applications of the algorithmsare introduced, and briefly describes the application of some late-model algorithms onreactive power optimization. Finally, the research and application of PSO in thefuture are pointed out.The paper analyses the condition about power systems in the petro-chemicalenterprise. Exerting the PSO algorithms optimizes the power systems to compute therational compensation capacitance. The calculation shows the power systems aregreatly improved via reactive power optimization. The enterprise gains the economicbenefit .