Robust model predictive load frequency control for DFIG based wind-integrated power systems with nonlinear physical constraints

Wind power integration into power systems presents challenges for frequency control due to the inherent variability and uncertainty of wind power generation. This paper explores the potential of employing variable speed wind turbines (VSWTs), specifically doubly-fed induction generator (DFIG) based wind turbines, to contribute in load frequency control (LFC) within a multi-area power system with significant wind power penetration considering nonlinear physical constraints, i.e., generation rate constraint (GRC), governor dead-band (GDB), and time delay. We develop a comprehensive model of the DFIG, accounting for its unique characteristics and control strategies. Our proposed approach utilizes model predictive control (MPC) to ensure optimal LFC performance by actively adjusting the power output of the DFIG based on frequency deviations. We present the dynamic response of the DFIG in regulating power injection, demonstrating its capability to mitigate frequency deviations and ensure reliable system operation. Through simulation results, we validate the effectiveness of our proposed approach and assess its robustness against various uncertainties. Our findings underscore the significant role of DFIG in enhancing frequency control and offer valuable insights into wind power integration into power systems. The proposed algorithms are implemented in MATLAB/SIMULINK and demonstrate efficiency and accuracy.