A flexible and secure model predictive control strategy for frequency regulation of wind turbines considering fatigue load mitigation

This paper proposes a flexible and safe model predictive control strategy for wind turbines to improve grid frequency support while reducing drivetrain fatigue loads. As wind power penetration increases, wind turbines are increasingly required to participate in frequency regulation, but frequent active power adjustment may intensify shaft fatigue. A discrete-time state-space model of the coupled wind turbine and power grid is first established, and a fatigue-load sensitivity model is introduced to describe the influence of power and pitch commands on drivetrain torque fluctuation. Based on real-time operating data, the controller performs rolling optimization of generator power and blade pitch angle under frequency support, power balance, and load constraints. Thus, the frequency response intensity is adjusted according to the real-time mechanical state of the turbine. Simulation results under ±0.2 Hz and ±1 Hz frequency disturbances show that the proposed strategy provides directionally consistent power support, with mean active-power differences below 0.01%. The low-speed shaft fatigue load is reduced by up to 7.67%, and the tower base fore-aft fatigue load is reduced by up to 9.44%. Field tests on a 10 MW doubly-fed wind turbine validate its effectiveness.