Wake position tracking using dynamic wake meandering model and rotor loads

The wake position is crucial feedback information for closed loop wind farm control. This paper presents a center tracking approach based on turbine rotor loads, which feasible to track the while impinging downstream turbine. equivalent characteristics are estimated blade root bending moments. Furthermore, wake-wind model developed describe relationship between averaged and position, in velocity deficit profile of defined by Gaussian model. An adaptive extended Kalman filter proposed estimate lateral vertical states, dynamics described dynamic meandering driven colored noise with covariance matrix that gain scheduled according characteristic. Uncertainties detection discussed various combinations ambient atmospheric condition. Simulation results show method achieves good estimates low turbulence intensity, while, condition high relatively longer time averaging needs be applied smooth out short-term fluctuations highlight longer-term trends.