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文章摘要
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
Received:March 11, 2014  Revised:March 15, 2014
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:
Author NameAffiliationE-mail
HU Zhi-bing* Northeast Dianli University,School of Electrical Engineering,Jilin City,Jilin Province hzb890210@126.com 
CAI Guo-wei Northeast Dianli University,School of Electrical Engineering,Jilin City,Jilin Province  
LIU Cheng Northeast Dianli University,School of Electrical Engineering,Jilin City,Jilin Province  
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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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