Robust Control for DFIG-Based WECS with ANN-Based MPPT

Mitigating nonlinearities and parameter fluctuations in high-rated wind energy systems is crucial for efficient energy conversion and grid integration. This paper presents a robust Integral Sliding Mode Control (ISMC) strategy for monitoring active and reactive power in a DFIG-based wind turbine. An artificial neural network based MPPT algorithm enhances speed control and addresses power fluctuations. The proposed ISMC ensures an optimal dynamic response to wind variations. Its performance is compared using a PI controller in Field-Oriented Control (FOC_PI) in MATLAB/Simulink on a wind system of 1.5 MW and tested under real-wind conditions. Simulation results confirm that ISMC outperforms FOC_PI in reference tracking, accuracy, dynamic behavior, and current distortion reduction.