Experimental validation of metaheuristic-optimized control for standalone DFIG dynamic performance enhancement

This paper proposes a robust control strategy to enhance the dynamic performance and power quality of standalone Doubly Fed Induction Generator (DFIG) systems under unbalanced loads. The approach employs metaheuristic optimization techniques the Cuckoo Search Algorithm (CSA) and Whale Optimization Algorithm (WOA) to optimally tune PI controllers in a direct-voltage control scheme for the rotor-side converter. Comprehensive simulation and experimental validation (using a dSPACE DS1104 platform) demonstrate the superiority of the optimized controllers over conventional PI tuning. Key experimental improvements include: overshoot reduced by up to 88% (from 36.8 to 4.2%), rise time accelerated by 99% (from 0.22 to 0.002 s), and stator voltage THD suppressed by 82% (from 31.8 to 5.9%) during load and voltage step variations. The results confirm that CSA and WOA optimization significantly boost transient response and power quality in off-grid DFIG wind energy systems.