Model-based model predictive control for a direct-driven permanent magnet synchronous generator with internal and external disturbances

This paper deals with the critical issue in a direct-driven permanent magnet synchronous generator (PMSG)-based wind energy conversion system (WECS): the rejection of internal and external disturbances, including the uncertainties of external environment, rapid wind speed changes in the original parameters of the generator caused by mutative operating conditions. To track the maximum power, a maximum power point tracking strategy based on model predictive controller (MPC) is proposed with extended state observer (ESO) to attenuate the disturbances and uncertainties. In real application, system inertia and the system parameters vary in a wide range with variations of wind speeds and disturbances, which substantially degrade the maximum power tracking performance of wind turbine. The MPC design should incorporate the available model information into the ESO to improve the control efficiency. Based on this principle, a model-based MPC with ESO control structure is proposed in this paper. Simulation study is conducted to evaluate the performance of the proposed control strategy. It is shown that the effect of internal and external disturbances is compensated in a more effective way compared with the ESO-based MPC approach and traditional proportional integral differential (PID) control method.