Enhanced FCS-MPC for DFIG Under Non-Ideal Grid Conditions

This paper proposes an enhanced Model Predictive Control–Finite Control Set (MPC-FCS) strategy for grid-connected Doubly-Fed Induction Generators (DFIG) operating under distorted voltage conditions. The controller employs a discrete-time model of the system to predict the future behavior of rotor currents and minimizes a cost function based on the deviation between predicted and reference current values. To improve synchronization accuracy under non-ideal grid conditions, the approach integrates a Decoupled Double Synchronous Reference Frame Phase-Locked Loop (DDSRF-PLL). This integration enables robust phase tracking and enhances the selection of optimal voltage vectors applied to the rotor, thereby improving dynamic response and control accuracy. Overall, the proposed method addresses key limitations of conventional MPC-FCS techniques and contributes to the literature by filling a notable gap in the study of advanced control strategies for DFIG-based wind energy systems under distorted grid conditions.

Keywords: Model predictive control (MPC), doubly fed induction generator (DFIG), decoupled double synchronous reference frame phase-locked loop (DDSRF-PLL), Distorted voltage, finite control set (FCS), wind generation systems.