Power System Low Frequency Oscillation Modal Identification Based on the FastICA Technique and TLS-ESPRIT Algorithm

ZHANG Cheng; LIU Jiajing; KUANG Yu; QIU Binglin

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Power System Low Frequency Oscillation Modal Identification Based on the FastICA Technique and TLS-ESPRIT Algorithm

更新时间：2025-12-08

- Power System Low Frequency Oscillation Modal Identification Based on the FastICA Technique and TLS-ESPRIT Algorithm
- Vol. 47, Issue 6, Pages: 2214-2222(2021)
- 作者机构：
  
  1. 福建工程学院电子电气与物理学院
  2. 智能电网仿真分析与综合控制福建省高校工程研究中心
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published Online：30 June 2021，
  
  Published：2021
- 稿件说明：
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ZHANG Cheng, LIU Jiajing, KUANG Yu, et al. Power System Low Frequency Oscillation Modal Identification Based on the FastICA Technique and TLS-ESPRIT Algorithm[J]. 2021, 47(6): 2214-2222.
DOI：

ZHANG Cheng, LIU Jiajing, KUANG Yu, et al. Power System Low Frequency Oscillation Modal Identification Based on the FastICA Technique and TLS-ESPRIT Algorithm[J]. 2021, 47(6): 2214-2222. DOI：

摘要

对于目前电力系统中低频振荡参数辨识中的噪声干扰和精度问题

提出了一种新的提取低频振荡模态参数的方法

将快速独立分量分析技术(fast independent component analysis

Fast ICA)和总体最小二乘-旋转不变技术(total least squares-estimation of signal parameters via rotational invariance technique

TLS-ESPRIT)联合起来。首先运用FastICA技术对含有噪声的电力系统低频振荡广域测量信号进行预处理而达到降噪效果

而后将处理后的信号作为新的输入信号利用TLS-ESPRIT算法进行估计辨识

从而得到各个模态特征参数。通过对理想信号、EPRI-36机系统和电网实测信号仿真验证了所提方法的有效可行性

不但能够有效抑制噪声并准确地辨识低频振荡参数

而且在抗干扰性和提取精度上与传统辨识方法相比来说是有一定优势的。

Abstract

The noise interference and accuracy of low-frequency oscillation parameter identification in the power system are discussed

and a new method for extracting the modal parameters of low frequency oscillation is put forward. The Fast ICA（Fast Independent Component Analysis） is combined with the total least squares-estimation of signal parameters via rotational invariance technique（TLS-ESPRIT）. Firstly

the FastICA technology is employed to pre-process the low-frequency oscillation wide-area measurement signal of power system containing noise so as to achieve noise reduction effect.Then

the TLS-ESPRIT algorithm is employed to estimate and identify the filtered signal to obtain each modal parameter. Finally

the validity and feasibility of FastICA-TLS-ESPRIT method are verified by simulation of ideal signal and EPRI-36 machine system and grid measure signal

and it is that this method not only can be adopted to effectively suppress noise and accurately identify low-frequency oscillation parameters

but also has certain advantages in anti-interference and extraction accuracy compared with traditional identification methods.

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Related Institution

State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment,Department of Electrical Engineering, Tsinghua University

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