The Research Of Multi-Objective Reactive Power Optimization Of Power System Base On Hybrid Particle Swarm Algorithm

As Chinses economic development, power industry play an increasingly important role in the national economy. The safety,reliability and economy of Power system are the direction of its development, and are currently subject to more and more people’s attention.Whether reasonable distribution of reactive power in power system determines the voltage quality, for the safety of power grid and the economy will also be a direct impact.Power system reactive power optimization can realize reasonable distribution of reactive power current, thereby reducing reactive power in power transmission, improve the transmission efficiency of active power, reduce the loss of active network, and then realize the economic operation of power system.In addition, the power system reactive power optimization can effectively improve the voltage level, improve power quality, which can enhance the reliability and stability of power system..In this paper, particle swarm optimization algorithm and its application in power system reactive power optimization of in-depth research, we proposed a net loss, the offset voltage and the voltage stability of the power system as the objective function, using hybrid particle swarm intelligence algorithm power system reactive power optimization model. Research with the convergence speed, strong global search capability features by hybrid particle swarm intelligence algorithms to improve the standard particle swarm algorithm.So this paper choiced the algorithm to establishthe mathematical model of reactive power optimization.In the specific research work, this paper takes IEEE 14 nodes network and IEEE30 nodes network as the test system, by changing the transformer turns ratio and PV node voltages, adding reactive power compensation device in the ground branch points to change the system reactive power distribution and simulation experiments in Matlab2013 environment. To the Multi-objective problem, we use constraint method for processing, in which the network losses as the main objective, and then the offset voltage and voltage stability as the secondary objective.Experimental results show that the power system which has finished reactive power optimization by hybrid particle swarm algorithm become better than before on all the goads. This experiment has proved that the reactive power optimization can make the stability and economy of power system better, and taking particle swarm algorithm to solve the power system reactive power optimization problem is feasible.