Wind Power Yaw Control Based on Time Series Kalman Filter

Abstract

Due to the excessive weight of the yaw mechanism, a certain inertia will be generated during steering, resulting in the non continuous deflection of the fan. The fan is in the process of yaw most of the time, which affects the utilization efficiency of wind energy and the service life of the yaw mechanism. In order to reduce the invalid yaw times of the wind turbine, a yaw control method combining the time series prophet model and Kalman filter is proposed. The fusion control method is to preprocess the wind direction with Kalman filter, and then predict the time series to double judge whether the motor is yaw, and integrate it into the yaw control system of wind turbine. Compared with different control methods, the analysis results effectively reduce the yaw frequency of the unit, so as to improve the service life of the yaw mechanism of the unit. It is proved that the fusion control method is effective.