Tube-based linear parameter-varying model predictive control for wind energy conversion systems

Maximum power extraction and transfer from wind energy conversion systems (WECS) to the power grid depends on a high-performance control system. This paper proposes a robust tube-based linear parameter-varying (LPV) model predictive controller (MPC) for rotor speed and stator’s active and reactive power control of a Doubly-Fed Induction Generator (DFIG) based WECS. The turbine dynamics and the DFIG is modeled as a single LPV system, which enables the model transformation into an equivalent linear time-invariant (LTI) system to avoid online updates of the prediction matrix. Based on the LTI representation, a tube-based LPV MPC (TLPVMPC) is developed, consisting of a tracking nominal MPC with tightened constraint sets and a disturbance controller. In the proposed method, the disturbance upper bound is estimated by Kalman filtering, which provides less conservative performance. The proposed controller is compared to sliding mode control (SMC), LPVMPC and nonlinear MPC (NMPC) methods. Simulations are conducted under model uncertainties and partial faults in the DFIG control voltages. The results show the robust performance of the proposed controller in power extraction and reduction of mechanical stress build-up compared to the other control methods.