Improved LVRT Performance of Doubly-Fed Wind Generator System in Comparison with Neuro and Sliding Mode Control

Abstract

The Doubly Fed Induction Generator (DFIG) in wind system is linked to the power-grid, which is vulnerable to significant grid failures. Because of the DFIG’s sensitivity to disturbances in the grid, designing of the controller is considered. In this article, the Feed-Forward Neuro-Second Order Sliding Mode (FFN-SOSM) controller and the Second Order Sliding Mode (SOSM) controller are compared for the Low Voltage Ride Through (LVRT) enhancement under voltage sag situation. Convergence in the sliding surface control is assisted by the use of higher-order switching functions in the FFN-SOSM. Importantly, controller benefits are such that reduction in chattering effect and minimized settling time for the system’s parameters as a result in the implementation of the FFN-SOSM method. With the assistance of MATLAB/SIMULINK, a comparison is made between the performances of the FFN-SOSM controller and those of SOSM controller, which is described in the existed research. The results of the simulation indicate that the "FFN-SOSM controller improved the LVRT capability of the DFIG-Wind Turbine (WT) system" when it is functioning under dynamic conditions.