Research On The Dynamic Equivalent Of Asynchronous Generators In Wind Park Based On Genetic Optimization Algorithm

In recent years, the development of wind power generation is very rapid. Capacity of wind generators and the scale of wind farm are becoming larger and larger. Because of the randomness and intermittence of wind, the grid-connected wind turbines will produce disturbance on the of dynamic behavior power system. Accordingly the researches on technology problems of grid-connected wind turbines increase progressively with time. However a wind park consists of tens or hundreds of wind turbines. If the wind park is represented by a detailed model including of all wind turbines, the detailed model presents a high order model and therefore the simulation time is long. So it is necessary to present a dynamic equivalence approach of wind turbines before dynamic analysis. At present, wind-electricity system in our country often uses fixed-speed wind turbines. And asynchronous generators are often used in fixed-speed wind turbines. Then the asynchronous generators are taken as the object of study to research the dynamic equivalence problem.As the theoretical basis of research, mathematical models of wind-electricity system are first modeled, including models of wind velocity, wind turbine, asynchronous generator. Among them the three-step transient mathematical model of asynchronous generator are focused on. And based on the model, the main parameters of the equivalent model of asynchronous generators are determined. Secondly the power flow calculation of wind-electricity system is introduced. And the results act as the initial value of dynamic analysis. Thirdly this paper presents the equivalent modeling of wind farm and the theory of genetic optimization algorithm. Under that, genetic optimization algorithm is proposed for the equivalence of different types of asynchronous generators. It uses MATLAB/SIMULINK software as simulation tools. This paper uses weighted method as reference substance. Under the impact of gust and earth-fault, genetic optimization equivalent model are simulated and compared with detailed model. It concludes that genetic optimization equivalent model can reflect the dynamic behavior of generators under different failure conditions more exactly and has strong applicability. Besides, equivalent parameters are also suitable for the steady-state operation and the outputs have higher accuracy.