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电网技术  2010 

基于ARMA模型的低频振荡模式在线辨识技术研究

, PP. 48-54

Keywords: 自回归滑动平均模型,广域测量系统,在线辨识,低频振荡,类噪声信号,主导模式

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Abstract:

为提高电力系统低频振荡实时监测的水平,在讨论基于自回归滑动平均模型(auto-regressivemoving-average,ARMA)及广域实测类噪声信号的低频振荡模式辨识方法的基础上,给出了一种基于奇异值分解的ARMA模型定阶方法;提出了在辨识出ARMA模型参数之后采用ARMA谱估计以识别低频振荡主导模式;最后结合工程实际提出了基于广域测量系统的低频振荡模式在线辨识框架,主要包括数据预处理、基于ARMA模型及滑动窗的低频振荡模式参数追踪以及大扰动下动态响应信号的辨识策略等。通过对测试系统时域仿真以及南方电网广域实测所得的类噪声数据进行分析,表明所述方法可以准确辨识低频振荡的主导模式,特别是对于弱阻尼模式的参数辨识精度较高,具有很高的实用意义。

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