LVRT enhancement of DFIG-driven wind system using feed-forward neuro-sliding mode control

Abstract

Power generation losses arise in doubly fed induction generator (DFIG) system due to grid faults. The system’s protection should ensure that the wind turbine (WT) generator meets the grid requirements through a low voltage ride through (LVRT) technique. This article proposes the feed-forward neuro-second order sliding mode (FFN-SOSM) control for the LVRT enhancement under voltage sag. This controller operates with the levenberg marquardt (LM)-super twisting (ST) algorithm for the uncertainties of the DFIG system. The LM-ST algorithm-based proposed controller is subjected to stability analysis. The advantages of the proposed controller are that it reduces the system parameter’s peak values and harmonic distortion of the system during grid disturbance. The performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the LVRT performance of the WT-DFIG system under transient conditions.

Keywords

• wt
• dfig
• lvrt
• ffn
• sosm