The Reactive Power Optimization Research Of Distribution Network With Distributed Wind Turbines

With the increasing development of conventional energy and the increasing importance of renewable energy, wind power has been widely used in distribution network because of its advantages such as environmental protection, low cost, flexible and so on. But wind energy is random, and it has great influence on the active power loss and voltage quality. If the distribution of reactive power distribution can be reasonably distributed, it can effectively reduce the active power loss, but also can improve the quality of the voltage.Because there are two traditional method of reactive power regulation in distribution network, the one is to control the number of the gear, the other is to switch capacitor of the load voltage regulating transformer, the method has the disadvantage of slow adjustment. So this paper is based on the reactive power of the double fed induction generator, the grid connected doubly fed induction wind turbine generator is studied. The reactive power output of doubly fed induction generator is combined with the traditional reactive power compensation method,participate in reactive power optimization of distribution network.Firstly, the treatment of wind turbine, reactive power optimization model and reactive power optimization algorithm are introduced in this paper. Then, according to the random output of doubly fed induction generator, the scene analysis method is used to deal with the problem, and based on mathematical model of doubly fed induction generator under two phase synchronous rotating coordinate system,the reactive power limit is deduced. Then the calculation method of forward and backward method with doubly fed induction wind generator based on the trend of distribution network is presented. Then, in view of the reactive power optimization using particle swarm optimization algorithm, the algorithm is prone to "premature convergence" problem, the particle swarm optimization is improved. Then, the standard particle swarm optimization algorithm and improved particle swarm optimization algorithm are applied to 2 test functions. The test results show that the improved PSO algorithm is significantly improved compared with the optimization algorithm. Next, a single objective reactive power optimization model with active power loss and voltage deviation is established, and a multi-objective reactive power optimization model considering active power loss and voltage deviation is established. At last, the algorithm and model of the IEEE33 system with doubly fed induction generator are used to verify the reactive poweroptimization of single target and multiple targets separately, the calculation results show that the algorithm and the model are feasible and correct in the field of reactive power optimization.