Subsynchronous Oscillation Mode Identification Based on ICEEMDAN and TLS-ESPRIT

Aiming at the noise interference and accuracy problems in the current power system sub-synchronous oscillation parameter identification, a sub-synchronous oscillation modal identification method is proposed based on the combination of improved adaptive noise-complete ensemble empirical modal decomposition (ICEEMDAN)and the total least squares-rotation invariant technique (TLS-ESPRIT). The sub-synchronous oscillation signal is firstly decomposed by ICEEMDAN to obtain a series of intrinsic modal functions, then the correlation coefficients between each IMF and the original signal are calculated, and the individual IMFs obtained from the decomposition are filtered and reconstructed by using the correlation coefficient thresholds, and finally, the preprocessed signals are parametrically identified by using the TLS-ESPRIT algorithm. The proposed method is verified by the ideal example, the standard model of wind farm and the measured signals, and the results show that the proposed method can accurately and effectively identify the parameters of the subsynchronous oscillation, which lays the foundation for the suppression of the subsynchronous oscillation afterwards.