Nonlinear model predictive controller design for extreme load mitigation in transition operation region in wind turbines

This paper addresses the problem of alleviating tower stresses for wind turbines in the event of extreme loads during the transition between the partial and full load operation regions. A Nonlinear Model Predictive Controller (NMPC) is used to enhance power capture for the National Renewable Energy Laboratory (NREL) 5MW variable-pitch variable-speed reference wind turbine. It is assumed that wind field preview information is measurable using wind speed/direction measurement devices such as LIDAR. The objective is to mitigate extreme loads on the turbine structure by minimizing the tower-top movement caused by thrust forces. While conventional controllers aim to extract maximal power from the wind by tracking the maximum power coefficient c_{P, max} for below-rated wind speeds, the proposed NMPC approach additionally damps the tower fore-aft movement in response to sudden changes in the wind speed. This results in considerable load mitigation. Simulations demonstrate the efficacy of the proposed approach.