Intelligent Chopper and RSC Control Using Crayfish Optimization for Dynamic Stability and Fault Ride-Through of DFIG Wind Turbines

This paper investigates the enhancement of dynamic performance of a doubly fed induction generator (DFIG)–based wind turbine under variable wind speeds and severe grid fault conditions using a Crayfish Optimization Algorithm (CFO)–based control strategy. The proposed method optimizes the rotor-side converter controller gains and incorporates a braking chopper with CFO-tuned PI controllers to ensure maximum power point tracking and improved fault ride-through capability. The system is evaluated in MATLAB/Simulink under stepwise wind speed variations and an 85% grid voltage dip lasting 150 ms, satisfying grid-code requirements. Simulation results demonstrate fast power coefficient recovery, effective DC-link voltage regulation, reduced current transients, and stable reactive power support. During grid faults, the proposed approach maintains grid connection and enhances post-fault reactive power injection. Comparative results confirm superior transient performance with lower hardware complexity compared to recent optimized DC chopper-based methods.