Enhancement on transient stability of LVRT of DFIG based on neural network D-STATCOM and crowbar

This paper analyses the improvement of LVRT(low voltage ride-through) ability of DFIG(doubly-fed induction generator under the operation of a series of fluctuating caused by asymmetric grid faults. This study proposes the coordination of neural network D-STATCOM and Crowbar protection which can greatly enhance transient stability of DFIG. Firstly, the model and control of neural network D-STATCOM and Crowbar are presented. Then, the coordination is introduced, which solves the over-current, voltage drop, reactive power fluctuations and other issues under grid fault. The simulation results show the validity of the proposed approach. The reactive power can be adjusted quickly and accurately when an asymmetrical fault occurs in the grid. The rotor over current can be restrained and the transition process is shortened. This protection improve the LVRT ability of DFIG effectively.