Real-time testing of an optimal fractional-order PI controller for BDFIG-based wind energy conversion systems

This paper proposes an advanced control strategy for a grid-connected Brushless Doubly-Fed Induction Generator (BDFIG) wind energy system operating under variable wind and grid conditions. The method employs a Fractional-Order Proportional–Integral (FOPI) controller optimally tuned via a novel Cloud Drift Optimization (CDO) algorithm and applied across key control loops, including active/reactive power, DC-link voltage, and grid-side inverter control. By combining fractional calculus with optimal tuning, the proposed scheme significantly enhances transient response, robustness under parameter uncertainties, and DC-link voltage stabilization compared to conventional PI control. The simulation and Hardware-in-the-Loop (HIL) results demonstrate a 35% faster settling time, overshoot below 4%, and steady-state errors under 0.5%. Moreover, the controller improves DC-link voltage regulation with reduced ITAE, IAE, and ISE indices under wind speed variations between 8 and 12 m/s, confirming its effectiveness and practical suitability for high-performance BDFIG-based wind energy systems.