基于自然激励技术和TLS-ESPRIT方法的低频振荡模式辨识

WANG Xiangchao

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基于自然激励技术和TLS-ESPRIT方法的低频振荡模式辨识

更新时间：2025-08-13

- 基于自然激励技术和TLS-ESPRIT方法的低频振荡模式辨识
- Automation of Electric Power Systems Vol. 39, Issue 10, Pages: 75-80(2015)
- 作者机构：
  
  西南交通大学电气工程学院,四川省,成都市,610031
- 作者简介：
- 基金信息：
- DOI：
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- Published：2015
- 稿件说明：
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WANG Xiangchao. [J]. Automation of electric power systems, 2015, 39(10): 75-80.
DOI：

WANG Xiangchao. [J]. Automation of electric power systems, 2015, 39(10): 75-80. DOI：

摘要

提出了一种利用系统随机响应信号辨识低频振荡模式的方法。利用自然激励技术(NExT)从系统随机响应信号中获得自由振荡信号

采用总体最小二乘-旋转不变技术的信号参数估计 (TLS-ESPRIT)方法对所获得的自由振荡信号进行模式辨识

得到低频振荡模式的频率和阻尼比。采用16机系统仿真数据和四川电网实测数据验证了所提方法的有效性;与随机减量技术(RDT)结合Prony方法对比表明

所提方法对阻尼比估计更准确且抗噪性更强。

Abstract

An approach to identifying low frequency oscillation modes based on the stochastic response signals of the system is presented. First

the free oscillation signals are extracted from the stochastic response signals of the system by the natural excitation technique (NExT). Then the mode parameters of the obtained free oscillation signals are identified by the total least squares-estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) algorithm. Finally

the frequencies and damping ratios of low frequency oscillations are obtained. The effectiveness of the proposed method has been verified by the simulation data from a 16-machine system and the measurement data in Sichuan power grid. Compared with the random decrement technique (RDT) and Prony method

the proposed method is more accurate in identifying the damping ratios and has a better noise immunity performance.

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