Intelligent MPPT and coordinated control for voltage stability in brushless DFIG wind turbines

This research develops a novel control approach for improving voltage stability and maximizing power extraction in Brushless Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion Systems (WECS). The developed approach incorporates a Chaotic Salp Swarm Optimization (CSSO) tuned Adaptive Neuro Fuzzy Inference System (ANFIS) for Maximum Power Point Tracking (MPPT) allowing rotor speed's dynamic adjustments and torque to attain better wind power extraction. The control framework has coordinated control among the Rotor Side Converter (RSC) and Grid Side Converter (GSC), where the GSC provides the delivery of power to the grid and offers grid support features while the RSC manages torque of rotor side and DC link voltage. To support grid stability under changing conditions, reactive power balancing and voltage regulation are incorporated into the system. By utilizing a d-q reference frame based current control strategy, the harmonic distortion in the grid current is alleviated. Furthermore, the efficacy of developed controller is validated in MATLAB/Simulink tool demonstrating tracking efficiency of [Formula: see text] with improved tracking speed (0.08s), reduced total harmonic distortion (THD < 2.85%), enhanced voltage stability revealing significant improvements in voltage stability, harmonic suppression and wind energy harvesting efficiency under both steady-state and dynamic operating conditions.