Enhancing Wind Energy Generation: Designing and Optimizing a Novel FO Fuzzy PD+I Regulator Using the SSO Method

Abstract

In this article, an optimized design methodology is presented for a Fractional-Order Fuzzy Proportional-Derivative with Integral (FO Fuzzy PD + I) regulator using the Social Spider Optimization (SSO) technique. The research focuses on its application in the control of Doubly Fed Induction Generator (DFIG)-based wind turbine systems (WTS). The FO Fuzzy PD + I controller integrates the capabilities of the Fuzzy intelligent regulator and the Fractional-Order Proportional-Integral-Derivative (FO-PID) controller, enhancing DFIG current control while allowing independent control of active and reactive power. The approach is incorporated within the Direct Vector Control (DVC) strategy of the DFIG's rotor-side converter (RSC), replacing the conventional Proportional-Integral (PI) regulator in the internal current loops. Extensive performance evaluations are conducted under various operating conditions, including active power reference changes, parameter uncertainties, and rapid wind speed variations. Comparative analyses with SSO-optimized PID and Fuzzy regulators show the FO Fuzzy PD + I regulator performs better in terms of maximum overshoot, extreme undershoot, settling time, and Total Harmonic Distortion (THD) reduction. These findings underscore the regulator's potential for enhancing the reliability and efficiency of DFIG-based WTS. Furthermore, the adaptability of the FO Fuzzy PD + I regulator positions it as a versatile control solution with implications extending beyond the realm of wind energy, potentially benefiting various industrial sectors that demand precise and dynamic control mechanisms. As renewable energy sources continue to gain prominence in the global energy landscape, this research contributes to the broader mission of realizing a sustainable and eco-friendly energy future.