Advanced Aerodynamic and Fault-Tolerant Control for VSVP Wind Turbines and DFIG Using Predictive and Sliding Mode Techniques

Abstract

The integration of renewable energy systems, particularly Variable Speed Variable Pitch (VSVP) wind turbines, into the power grid is crucial for maximizing power generation efficiency and maintaining stability under fluctuating environmental conditions. However, challenges such as wind speed variations and grid disturbances affect their performance. This study proposes an advanced hybrid control framework to optimize aerodynamic performance, power capture, and fault resilience in Doubly Fed Induction Generator (DFIG)-based wind turbines. The primary objective of this research is to enhance power extraction efficiency and ensure robust Fault Ride-Through (FRT) capability by integrating Model Predictive Control (MPC) and Sliding Mode Control (SMC). MPC dynamically adjusts the pitch angle and generator torque, optimizing the power coefficient  and reducing pitch angle deviation, rotor speed fluctuations, and response time. For fault mitigation during voltage dips, Higher-Order Sliding Mode Control (HOSMC) and the Super-Twisting Algorithm (STA) are implemented to regulate DFIG electromagnetic force, reducing torque ripples, voltage sags, and Total Harmonic Distortion (THD). The proposed framework is implemented using MATLAB. The power coefficient  is improved to 0.52 at λ = 6.5, surpassing PI (0.42) and Fuzzy Logic (0.48) controllers. THD is reduced to 1.8%, compared to 3.5% (PI) and 2.3% (Fuzzy Logic), ensuring superior power quality. Torque ripple is minimized to 2.1%, enhancing turbine mechanical stability. The proposed strategy successfully improves FRT capability, enhances energy capture efficiency, and ensures grid stability. This dual-layer control framework offers a promising solution for improving the efficiency, reliability, and resilience of wind turbines under variable wind and grid conditions.