Mathematical modeling and control of DFIG-based wind energy system by using optimized linear quadratic regulator weight matrices

This paper deals with a genetic algorithm (GA)-based linear quadratic regulator (LQR) controller to improve the dynamic response, stability, and robustness of the doubly fed induction generator (DFIG) system at various stator voltage disturbances. The complete model has been represented by a state-space model. This helps to optimally control all the states through the full-state feedback LQR controller. GA is employed in the LQR algorithm for optimal tuning of the Q and R matrices. For finding out the effectiveness of the proposed controller, its dynamic response has been compared with proportional integral (PI) and LQR controllers. The simulation results indicate that the proposed controller has better performance in comparison to the PI and LQR controllers in terms of peak value, settling time, rise time, and steady-state values of the DFIG outputs. The stability and robustness of the study system have also been investigated by the eigenvalue and participation factor analyses.