基于FastICA和Prony算法的低频振荡参数辨识

胡志冰; 蔡国伟; 刘铖

胡志冰,蔡国伟,刘铖.基于FastICA和Prony算法的低频振荡参数辨识[J].电测与仪表,2014,51(18):.
HU Zhi-bing,CAI Guo-wei,LIU Cheng.Parameter Identification of low frequency oscillation based on FastICA and Prony algorithm[J].Electrical Measurement & Instrumentation,2014,51(18):.

基于FastICA和Prony算法的低频振荡参数辨识

Parameter Identification of low frequency oscillation based on FastICA and Prony algorithm

DOI：

中文关键词: Prony算法快速独立分量分析低频振荡参数辨识

英文关键词:Prony algorithm,Fast Independent Component Analysis, low frequency oscillations,parameter identification

基金项目:

作者中文名	作者英文名	单位
胡志冰	HU Zhi-bing	东北电力大学电气工程学院
蔡国伟	CAI Guo-wei	东北电力大学电气工程学院
刘铖	LIU Cheng	东北电力大学电气工程学院

摘要点击次数: 2218

中文摘要:

传统Prony算法进行参数辨识存在对信号噪声非常敏感的缺点,同时对输入信号有较高的要求。因此,本文首先介绍独立分量分析(Independent Component Analysis,即ICA)和FsatICA基本原理,然后将FastICA算法和Prony算法结合的低频振荡参数辨识方法。该方法首先以广域测量信号作为输入信号,然后利用FastICA方法对输入信号进行预处理而达到降噪,最后利用Prony算法对滤波后的信号进行分析得到电力系统低频振荡参数。通过对理想信号和四机两区算例分析,验证了此方法在FastICA去噪之后,能够提高Prony提取低频振荡参数辨识的准确性、快速性和抗噪能力。

英文摘要:

Parameters are often identified by using Prony algorithm,but this method is sensitive to the noise of signals and has a high demand to the input signal.Therefore,the paper proposes a algorithm for identifying power system low frequency oscillation,which combines FastICA(Fast Independent Component Analysis) and Prony algorithm.First of all, wide area measurement signal is used as the input signal.And the preprocessing signal is denoised by ICA algorithm.In the end,the parameters of low frequency oscillation in the power system are obtained by using Prony algorithm,which analysis the denoised signal.Through analyzing the case studies on the ideal signal and four-machine system,it was found that the method improve the ability of accuracy,rapidity and anti-noise after the signal is denoised to identify the parameter of low frequency oscillation.

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