Stochastic model predictive control for the yaw control system of horizontal-axis wind turbines

Model predictive yaw control (MPYC) using the future wind direction information could improve energy conversion efficiency of wind turbines. However, the performance of MPYC system is closely related to the wind direction prediction of which the accuracy is actually difficult to improve. In this paper, we propose a stochastic model predictive yaw control (SMPYC) based on multi-scenario optimization to solve the uncertainty of future wind direction prediction. Meanwhile, in order to reduce computational burden during the model solving, the synchronous backward substitution method is used to cut down the scenarios with guaranteed precision. Then, the performance of the proposed SMPYC method is demonstrated by the simulation tests comparing with baseline control method (MPYC). Finally, our results show that the overall performance including power production and yaw actuator usage of SMPYC is enhanced.