Enhanced Control of DFIG-Based Wind Turbine Using Hybrid Fuzzy Super-Twisting Sliding Mode Control for Improved Power Quality and Robustness

Abstract

In the pursuit of advancing renewable energy technologies, optimizing wind turbine performance through sophisticated control systems is pivotal for addressing energy variability and enhancing system efficiency. This paper presents a novel hybrid fuzzy super-twisting sliding mode control (HFSTSMC) strategy for Doubly Fed Induction Generators (DFIGs) used in modern wind turbine configurations. DFIGs are favored for their adaptability and efficiency in managing variable wind speeds, making them integral to sustainable energy solutions. The proposed HFSTSMC integrates the robustness of super-twisting sliding mode control (STSMC) with the adaptive capabilities of fuzzy logic control (FLC), aiming to mitigate the chattering effect inherent in traditional sliding mode controls while maintaining high tracking accuracy and robustness. The hybrid controller utilizes fuzzy logic to dynamically adjust control gains based on system states, enhancing the dynamic performance and stability of DFIG-based wind turbines. Extensive modeling and simulation using MATLAB/SIMULINK validate the effectiveness of HFSTSMC in improving power quality, reducing mechanical stresses, and optimizing energy capture. The results demonstrate significant improvements in system response to rapid wind condition changes and overall operational efficiency under transient and uncertain conditions. This research underscores the substantial benefits of implementing HFSTSMC, highlighting its potential to revolutionize wind turbine control systems and contribute significantly to the global transition towards reliable and efficient renewable energy sources.