Performance optimization of wind turbines via fractional-order type 2 fuzzy MPPT control

Abstract

This paper proposes a new fractional-order type-2 fuzzy logic control (FO-T2FLC) technique for maximum power point tracking (MPPT) in a wind turbine system based on doubly fed induction generators (DFIGs). Type-1 fuzzy logic control (T1FLC) and traditional proportional-integral (PI) techniques have limitations in terms of accuracy, reaction time, and resilience under fluctuating wind conditions. The suggested FO-T2FLC combines type-2 fuzzy logic with fractional calculus to enhance dynamic performance, minimize steady-state error, and increase system flexibility, all without requiring a precise mathematical description of the system. The MATLAB simulations are used to evaluate the control strategy under step, random, and fault-like wind speed fluctuations. Comparative analyses show that FO-T2FLC outperforms PI and T1FLC by more than 99% in terms of performance indices, including Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE), Integral Squared Error (ISE), and Integral Time Squared Error (ITSE). It also minimizes tracking error and converges to the optimal tip speed ratio more quickly. The results demonstrate that the FO-T2FLC-based MPPT approach significantly enhances the robustness, stability, and efficiency of DFIG wind energy conversion systems, making it a viable option for contemporary wind power applications.

Affiliated Institutions

• King Khalid University SA
• University of Sciences and Technology Houari Boumediene DZ
• École Nationale Polytechnique d'Oran DZ
• Istinye University TR
• Hassiba Benbouali University of Chlef DZ

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