Study On Multi-Objective Reactive Power Optimization Of Power System With Doubly Fed Wind Farm

New energy power generation is an inevitable development process to replace the traditional fossil energy power generation.With the development of new energy in China,the scale of wind farms is increasing sharply.However,due to the randomness and intermittence of wind power,the influence of wind power on the economy and stability of power grid becomes one of the problems to be explored in the process of new energy consumption.In recent years,doubly fed induction generator(DFIG)has become one of the most widely used wind farm models.DFIG has the advantages of continuous decoupling control of active power and reactive power.Based on the consideration of DFIG's reactive power optimization capability and DFIG's P-Q characteristics,this paper studies the static reactive power optimization and dynamic reactive power cost optimization in the power market.Firstly,the DFIG unit model is established,and the P-Q characteristic curves of synchronous generator and DFIG unit are drawn.Secondly,the advantages and disadvantages of many modern intelligent algorithms are compared,and in order to solve the static reactive power optimization model,the hybrid concept of genetic algorithm is proposed based on the basic PSO algorithm,which is easy to fall into local optimization and premature.In the dynamic reactive power cost optimization with wind farms in the power market,two improvements are made to deal with the disadvantages of HPSO algorithm,such as difficult to deal with different types of variables and easy to premature :(1)Different inertia weights are used in different dimensions,and linear decreasing weight is used instead of fixed weight.(2)When the particle fitness of the last iteration is greater than that of the current iteration,the inertia weight of the particle is set to 0.In the static reactive power optimization,taking a wind farm in North China and IEEE30 node distribution network with doubly fed wind farm as an example,the reactive power optimization solution of the established model is carried out.Finally,the reactive power pricing model of DFIG is established,and the dynamic reactive power optimization model with the objective function of generator reactive cost,discrete equipment action depreciation cost,active network lossconversion cost and total node voltage deviation under the power market is established.In this paper,a new method of reactive power subsection pricing under wind speed fluctuation is proposed.Taking IEEE30 node with doubly fed wind farm as an example,the dynamic reactive cost optimization model with wind farm is solved.The results show that :(1)Using the flexible reactive power regulation ability of DFIG can significantly reduce the active power loss in the wind farm and significantly support the node voltage in the wind farm.(2)Using wind farm as reactive power optimization equipment can not only reduce investment cost,but also solve the problem of discretization of traditional reactive power voltage regulation means to a certain extent.(3)Compared with the traditional model and the static reactive cost optimization model,the proposed reactive cost optimization model can reduce the reactive cost and discrete equipment action more effectively,combined with the proposed reactive pricing strategy can reduce more operating costs in a longer period of time.(4)The proposed wind power pricing strategy under the fluctuation of wind speed can reduce the reduction of the unit active power output caused by the excessive reactive power distribution of the system to the doubly fed wind turbine to a certain extent.(5)The improvement of HPSO algorithm can effectively improve the adaptability of the algorithm to the reactive cost optimization model,effectively improve the optimization ability and convergence speed when solving the reactive cost optimization model,and provide a new method for solving the reactive cost optimization.