LIU Siyi, ZHANG Cheng, JIN Tao. Research on Modes Identification of Low-frequency Oscillation of Power System Based on Adjacent Coefficient TQWT and Improved TLS-ESPRIT Algorithm[J]. 2019, 45(3): 890-898.
LIU Siyi, ZHANG Cheng, JIN Tao. Research on Modes Identification of Low-frequency Oscillation of Power System Based on Adjacent Coefficient TQWT and Improved TLS-ESPRIT Algorithm[J]. 2019, 45(3): 890-898.DOI:
Aiming at the problem of Gaussian noise interference and order in the process of low-frequency oscillation of wide area measurement system
we propose a new method based on adjacent coefficient tunable Q-factor wavelet transform(TQWT) and improved TLS-ESPRIT algorithm to identify the modes of low-frequency oscillation signal in power grid. In the proposed method
the TQWT is used to decompose the power signal to obtain the initial wavelet coefficients
and the adjacent coefficient threshold rule is used to deal with the wavelet coefficients
and reconstruct the processed wavelet coefficients using inverse TQWT; then an improved TLS-ESPRIT algorithm is utilized to identify the low-frequency oscillation modes parameters. The results of numerical simulations
the IEEE four-machine two-area simulations
and the actual case simulations of North American power grid show that the proposed method can accurately identify low-frequency oscillation modes parameters
and has better anti-noise performance and higher fitting accuracy than other methods.The proposed method has strong practicability
and can realize on-line identification better
which will lay the foundation for the further research of low-frequency oscillation suppression.