Enhanced Power Quality in Counter‐Rotating Wind Turbines Using an Advanced Control Strategy

ABSTRACT

The increasing penetration of renewable energy into power networks calls for advanced control techniques capable of maintaining power quality and robustness under varying operating conditions. This study proposes a fuzzy backstepping terminal control (FBTC) strategy for counter‐rotating wind turbines (CRWTs) equipped with a doubly‐fed induction generator (DFIG). The approach combines the stability properties of backstepping control (BC) with the finite‐time convergence capability of terminal sliding mode control (TSMC). In addition, fuzzy logic control (FLC) is employed to substitute the discontinuous switching component of TSMC, thereby reducing chattering and enhancing the dynamic performance. The effectiveness of the proposed FBTC scheme was evaluated through comprehensive MATLAB/Simulink simulations and compared with the conventional BC method under various operating conditions, including variable wind speeds, grid voltage unbalances, and parameter variations in the DFIG. The results demonstrate that FBTC consistently outperforms BC in enhancing current and power quality, ensuring precise reference tracking, and improving robustness. Under variable wind conditions, FBTC achieved reductions of 49.52% in current total harmonic distortion (THD) and 48.88% in torque ripples. When exposed to unbalanced grid voltages, active power fluctuations decreased by 57.27% and reactive power ripples by 50%, accompanied by a 23.83% reduction in THD. Even under parameter variations, FBTC maintained stability and delivered improvements with ripple reductions of 54.83% for active power, 47.22% for reactive power, and 55.15% for torque. Moreover, significant decreases in the integral of time absolute error (ITAE) and steady‐state error (SSE) indices confirm its superior dynamic performance. These findings underline the effectiveness of FBTC as a practical and reliable control solution for CRWT systems, ensuring improved energy quality and system resilience in modern wind power applications.