A new approach for improving dynamic fault ride through capability of gridctied based wind turbines

The Doubly-Fed Induction Generator (DFIG) is preferred for wind turbines (WTs) due to their variable speed capability, reinforcing energy capture efficiency. Despite its advantages, researchers continually face challenges in managing the DFIG, including overshooting, rising time, and stability under fault conditions. The faults in WTs may stem from the grid or different operational disturbances. The crowbar protection mechanism is an efficient strategy to reduce fault impacts on DFIGs. However, the traditional hysteresis-based methods to detect faults and crowbar activation are prone to false triggering, and to address the challenges posed, this paper presents a novel control strategy that increases the low-voltage ride-through (LVRT) capability of the grid-connected DFIG systems by incorporating Fuzzy Logic Control (FLC) to enhance accuracy in fault detection and employs the Salp Swarm Optimization Algorithm (SSA) to refine controller parameters. The SSA algorithm shows a superior dynamic response and stabilizes the DFIG system efficiently. Besides, the SSA algorithm precisely calibrates the proportional-integral (PI) controller gains and DC-link capacitance values to achieve the optimal transient response between Distributed Generation (DG) integration and fluctuating loads. It is evident by the results that the power quality is improved, and the active power overshoot value is decreased from 10.12 × 10⁶ to 3.78 × 10⁶. Moreover, by implementing the SSA algorithm in which the overshoot value is also decreased from 15.01 × 10⁶ to 6.10 × 10⁶, the best results are achieved. The proposed method is validated by comparative analyses with recent studies that showcase its superiority in refining machine dynamics and decreasing overshoots and transients. Henceforth, the obtained results validate the proposed method's ability to compete against other conventional methods.