Research On Output Power Characteristics And Scheduling Optimization Of Large Wind Turbine

In the context of energy issues and environmental issues, wind power has been widely valued. Because of the strong randomness of natural wind, the output power of wind power generation is very volatile and uncertain, and it also increases the difficulty of wind turbine control; the natural environment of the wind farm is relatively poor, which greatly increases the operating cost of the wind farm and the hidden trouble of the fault. According to wind power generation principle and operation data of wind farm, the output characteristic of wind turbine generator, yaw control and wind field scheduling strategy are studied.This paper firstly introduces the existing types of wind turbine and the operation status of the wind turbine and the power dispatch optimization of the wind farm. In order to improve the accuracy of the wind yaw, reduce the wind caused by the fluctuation of the yaw system of frequent operation, puts forward a forecasting model based on the similarity and support vector machine for wind turbine yaw system strategy. According to the similarity principle and algorithm of support vector machine to the direction of the sample clustering analysis to establish a stand-alone wind forecasting model, control of the yaw system according to the prediction result. The simulation results show that the prediction model can predict the trend of changes in wind direction, the strategy can improve the operation mechanism of adjusting frequency and amplitude of the yaw system and reduce the accuracy of the wind. The thesis makes the optimization design of a wind farm wind load cluster scheduling, in order to achieve the best running state as the optimization target. Under the condition of satisfying the constraints, to fan cluster for the fan running state comprehensive evaluation based on the results, the encourage normal wind conditions for continuous operation, inhibit the fault state of wind machines to start running, by Using Chaos Quantum behaved particle swarm optimization algorithm to achieve wind farm cluster load distribution optimization scheduling. The simulation results show that the optimization scheduling strategy can maintain the fan cluster in the running state of health to meet the output load conditions, has guiding significance for wind load distribution.