Global data-driven modeling of wind turbines in the presence of turbulence

This paper presents a practical approach to identify a global model of a wind turbine from operational data, while it operates in a turbulent wind field with a varying mean wind speed and under closed-loop control. The approach is based on the realization that the nonlinearities are dominated by the aerodynamics of the rotor, which change with the operating condition. The dynamics of a wind turbine can be decomposed into a nonlinear static part, governed by the torque and thrust characteristics of the rotor, and a linear time-invariant dynamic part. The multi-input–multi-output linear dynamics are estimated using a recent closed-loop subspace identification method. The practical applicability of the algorithm is demonstrated by applying it to data obtained from the NREL CART 3 research turbine.