Impedance Model Identification of DFIG-Based Wind Turbine Based on Neural Network

The impedance-based analysis method is an effective tool to study the small-signal stability of power electronic systems. The conventional impedance modeling method needs to know the internal control structure and parameters in advance, which is not suitable for black/grey-box models in practice. In order to easily obtain port impedance characteristics under various operating points, this paper presents an impedance model identification method based on neural network. The impedance identification model of a doubly-fed induction generator (DFIG) based wind turbine is established by considering different operating points and address the problem of the scant data in online impedance identification. Through the error analysis, the validity of the established impedance identification model is verified.