Model predictive control of a wind turbine using short‐term wind field predictions

As wind turbines become larger and hence more flexible the design of adv anced controllers to mitigate fatigue damage and optimise power capture is becoming increasingly important. The majority of the existing literature focuses on feedback controllers which use measurements from the turbine itself and possibly an estimate or measurement of the current local wind profile. This work investigates a predictive controller which can use s hort-term predictions about the approaching wind field in order to improve performance by compensating for measur ement and actuation delays. Simulations are carried out using the FAST aeroelastic design code modelling the NREL 5MW reference turbine, and controllers are designed for both above and below rated wind conditions using Model Predictive Control. Tests are conducted in various wind conditions and with different future wind information available. It is shown that in above rated wind conditions, significant fatigue load reductions are possible compare d with a controller which knows only the current wind profile. However, this is very much dependent on the speed of the p itch actuator response and the wind conditions. In below rated wind conditions the goals of power capture and fatigue load control were considered separately. It was found that power capture could only be improved using wind predictions if the wind speed changed rapidly during the simulation and that fatigue loads were not consistently reduced when wind predictions were available, indicating that wind predictions are of limited benefit in below rated wind conditions. Copyright c 2010 John Wiley & Sons, Ltd.