@article{Ji2025, 
author = {Tianyao Ji and Shiyu Wang and Luliang Zhang and Q. H. Wu},
title = {Sub/Super-Synchronous Oscillation Detection Based on Matching Synchroextracting Wavelet Transform},
year = {2025},
journal = {CSEE Journal of Power and Energy Systems},
volume = {11},
number = {2},
pages = {649-660},
keywords = {Matching synchroextracting wavelet transform, Modal parameter estimation, Sub/super-synchronous oscillation, Time-frequency analysis},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2023.01310},
doi = {10.17775/CSEEJPES.2023.01310},
abstract = {When disturbed, the interaction between power grid and wind farm may cause serious sub/super-synchronous oscillation (SSO), affecting the security and stability of the system. It is therefore important to detect the time-varying amplitude and frequency of SSO to provide information for its control. The matching synchroextracting wavelet transform (MSEWT) is a new method proposed in this paper to serve this purpose. Based on the original synchrosqueezing wavelet transform, MSEWT uses a synchronous extraction operator to calculate the time-frequency coefficients and a chirp-rate estimation to modify the instantaneous frequency estimation. Thus, MSEWT can improve the concentration degree and reconstruction accuracy of the signal’s time-frequency representation without iterative calculation, and can achieve superior noise robustness. After the time-frequency analysis and modal decomposition of the SSO by MSEWT, the amplitudes and frequencies of each oscillation component can be obtained by Hilbert transform (HT). The simulation studies demonstrate that the proposed scheme can accurately identify the modal parameters of SSO even in the case of noise interference, providing a reliable reference for stable operation of power system time-frequency.}
}