Parameter identification of DFIG model based on HHT marginal spectrum

Due to the randomness and volatility of the environment where the wind turbine is generated, the model parameters of the wind turbine are in a state of fluctuation, high precision parameter identification of doubly-fed induction generator (DFIG) is beneficial to a more thorough understanding of the operating state of the generator and the impact of wind turbines on the power grid. A method based on Hilbert-Huang Transformation (HHT) marginal spectrum is proposed to identify the electrical parameters of DFIG, where the objective function related to parameter identification is improved, and the characteristics of different frequency signals contained in the output signals are decoupled. The simulation results show that proposed method is feasible and effective.