Efficient Power Control of DFIG-Based Wind Energy Systems Using Double-Stage Fractional-Order Controllers Optimized by Gazelle Algorithm With Multiple Cost Functions

Wind energy conversion systems (WECSs) require robust and efficient control strategies to ensure optimal energy conversion. This study proposes a nonlinear and resilient control approach using a fractional-order proportional integral- and fractional-order proportional derivative (FOPI–FOPD) controller for direct power regulation of a doubly fed induction generator (DFIG)–based WECS. To meet the control objectives, two cascaded FOPI–FOPD controllers were designed, resulting in 12 parameters requiring precise tuning. To optimize these parameters, the Gazelle optimization algorithm (GOA) was employed, targeting the minimization of key performance-based cost functions: mean error (ME), mean absolute error (MAE), mean-square error (MSE), and integral time absolute error (ITAE). These functions integrate dynamic response criteria such as overshoot, rise time, and settling time. Simulation results highlight the effectiveness of the GOA-tuned FOPI–FOPD controller, particularly when using ITAE as the optimization criterion. The controller significantly reduces power ripples by 86.13% in active power and 75.66% in reactive power. It also improves transient response by reducing rise time by 0.035 ms, settling time by 0.3 ms, and completely eliminating overshoot. Moreover, the proposed strategies lower the current total harmonic distortion (THD) by approximately 21.43% compared to the basic strategy. The proposed ITAE–GOA–FOPI–FOPD technique ensures system stability and enhances performance across various operating conditions.