基于改进TLS-ESPRIT的电力系统低频振荡模态辨识

现有基于实测信号的电力系统低频振荡模态辨识方法大都只考虑了高斯白噪声,对高斯色噪声的考虑不足,对此,提出一种改进最小二乘–旋转不变技术(TLS-ESPRIT)的模态辨识方法;该方法首先利用FOMMC来对辨识信号进行预处理,抑制信号中的色噪声;接着,利用TLS-ESPRIT对信号进行辨识。通过构建的数值信号和电力系统中实测的信号进行测试,其结果表明,该方法对色噪声具有较强的抑制作用,同时辨识的速度和精度更高。

Identification of Low Frequency Oscillation Modes of Power System Based on Improved FOMMC and TLS-ESPRIT

Most of the existing low-frequency oscillation mode identification methods in power system based on measured signals only consider Gaussian white noise and the Gaussian noise is not considered sufficiently.In this regard,an improved least squares-rotation are proposed Modal identification method of invariant technology(TLS-ESPRIT);This method first uses FOMMC to preprocess the identification signal to suppress the color noise in the signal;Then,the signals are identified using TLS-ESPRIT.The numerical signals and measured signals in the power system are used to test.The results show that the method has a strong suppression effect on the color noise,and the identification speed and accuracy are higher.