用改进的Hilbert-Huang变换辨识电力系统低频振荡
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摘要
针对Hilbert-Huang变换(HHT)在辨识电力系统低频振荡模态时易出现的模态混叠问题,提出了利用改进HHT辨识密频电力系统低频振荡模态参数的方法。首先通过Fourier变换确定每个模态频率的大致范围;然后在利用经验模态分解(EMD)求取每个模态时,根据所求得的模态频率的密集程度,或引入屏蔽信号,或通过滤波处理的方式,以分离频率相近的模态;最后通过对每个模态的瞬时幅值和频率进行线性最小二乘拟合,得到每个模态的模态参数。利用传统的HHT和改进的HHT分别对理想信号、仿真信号以及实际录波信号进行了分析,分析结果表明该方法能够准确辨识出低频振荡的特征参数,适用于密频电力系统低频振荡的辨识。
We proposed an improved Hilbert-Huang transform(HHT) algorithm to identify close modes of low frequency oscillation(LFO) in power systems.Firstly,by means of the Fourier transform,the approximate frequency range of every mode was determined;then according to the closely degree,methods such as masking signals or filters were chosen to separate close modes.Finally,parameters of every mode could be calculated by linear least quadratic fitting.The ideal signal,simulated signal and practical recorded signal were analyzed by traditional HHT algorithm and the improved HHT algorithm,respectively.The analysis results show that the improved HHT algorithm can correctly separate the close modes and identify the modes parameters,the identified results are prior to those by traditional algorithms,so the proposed algorithm is suitable to close mode identification of LFO.
引文
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