Enhanced Deadbeat MPC for Robust Large-Scale Wind Power Integration into Smart Grid

Wind power is highly unpredictable, dispersed geographically, and exhibits complex spatiotemporal coupling and aggregation characteristics. Power grid integration will be a significant technical challenge because of wind energy's highly variable nature, which may threaten the safety and stability of power, frequency, and voltage. Model predictive control (MPC) technology is an effective and efficient way of analyzing control issues associated with the integration of large-scale wind power into power systems and stability of power, frequency, and voltage. A deadbeat function (DB) is utilized to compute the reference voltage vector (VV) based on the demanded currents. The proposed control technique uses the reference voltage vector to compute the voltage gradient. For increased robustness against variations in machine parameters, a discrete-time integral action (DTIA) is added to the DB function. This technique improves dynamic performance, including reference tracking, disturbance rejection, and robustness to parameter variation. Discrete space vector modulation (DSVM) can keep the switching frequency constant, and torque-flux ripples can be reduced. Based on MATLAB / Simulink simulation results, the proposed strategy has demonstrated its feasibility and validity with excellent performance.