Optimization of DFIG power control using the Bald Eagle search algorithm

• Integration of the Bald Eagle Search (BES) algorithm within a Direct Power Control (DPC) scheme for DFIG-based WECS. • Real-time optimization of active and reactive power references to enhance MPPT, power ripples, and stabilize flux linkage. • Demonstration of BES superiority in achieving improved dynamic performance and fault ride-through capability. • Reduction of torque and flux ripples, harmonic distortions, and sensitivity to variable switching frequency. In light of the growing demand for sustainable energy and the diminishing viability of conventional fossil fuels, wind energy has become a compelling alternative particularly in wind-rich regions such as Morocco. Among the various variable-speed wind turbine technologies, the Doubly Fed Induction Generator (DFIG) stands out for its efficiency and cost-effectiveness. However, traditional control methods for DFIGs, including Field-Oriented Control and Direct Power Control (DPC), are hindered by limitations such as sensitivity to parameter variations, torque and flux oscillations, and fluctuating switching frequencies that contribute to harmonic distortion. To address these challenges, this study introduces an enhanced power control strategy for DFIG-based Wind Energy Conversion Systems (WECS), incorporating the Bald Eagle Search (BES) algorithm into the FOC framework. The proposed method dynamically adjusts the reference values of active and reactive power in real time, guided by system performance metrics such as power error and flux stability. Inspired by the bald eagle’s hunting strategy, the BES algorithm enables rapid convergence, high adaptability, and reduced computational complexity. Simulation results validate the effectiveness of the proposed BES-based controller, showing superior performance compared to conventional FOC and Fuzzy Logic Controller methods particularly in terms of harmonic distortion and dynamic response. The Total Harmonic Distortion (THD) values achieved are 2.69% for FOC, 2.52% for FLC, and 2.51% for the BES-based method, highlighting its potential to enhance power quality and operational stability under varying wind and grid conditions.