Performance Enhancement of DFIG based WECS during Voltage Fluctuations using ANN Controller

Abstract

The demand for wind generation in today’s grid is increasing its proposition in total electricity generated. To enhance the dependableness of the ability system a completely unique fault-tolerant configuration for wind energy conversion systems (WECSs) throughout totally different varieties of grid faults is planned. The planned configuration is developed by commutation the standard six-switch grid-side device (GSC) of DFIG (Doubly Fed Induction Generator) with a nine-switch device. The nine-switch device provides six  output terminals. The primary 3 output terminals  connected to the grid and therefore the next 3 output terminals are connected to neutral aspect of the mechanical device windings to supply pre-fault voltage. the substitute NEURAL NETWORK (ANN) primarily based PI management for wind energy conversion systems (WECSs) is developed , that achieves improved fault ride-through capability throughout LLLG faults. The effectiveness of the ANN management is compared thereto of a Proportional Integral (PI) controller and  evaluated victimization MATLAB on a 5-MW WECS. The simulations for Doubly Fed Induction Generator are elucidated using SIMULINK/MATLAB, corresponding results and waveforms are displayed.