Research on Modes Identification of Low-frequency Oscillation of Power System Based on Adjacent Coefficient TQWT and Improved TLS-ESPRIT Algorithm

被引：0
|
作者：
Liu S. [1 ]
Zhang C. [2 ]
Jin T. [2 ]
机构：
[1] Zhangzhou Power Supply Company, State Grid Fujian Electric Power Co., Ltd., Zhangzhou
[2] College of Electrical Engineering and Automation, Fuzhou University, Fuzhou
来源：
Gaodianya Jishu/High Voltage Engineering | 2019年 / 45卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Adjacent coefficient threshold denoising rule; Gaussian noise; Low frequency oscillation; Modes identification; Tunable Q-factor wavelet transform;
D O I：
10.13336/j.1003-6520.hve.20190226029
中图分类号：
学科分类号：
摘要：
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. © 2019, High Voltage Engineering Editorial Department of CEPRI. All right reserved.
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页码：890 / 898
页数：8
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