用改进的Hilbert-Huang变换辨识电力系统低频振荡OA北大核心CSCDCSTPCD
Identification of Low-frequency Oscillations in Power System Based on Improved Hilbert-Huang Transform
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…查看全部>>
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…查看全部>>
马燕峰;赵书强
华北电力大学新能源电力系统国家重点实验室,保定071003华北电力大学新能源电力系统国家重点实验室,保定071003
数理科学
低频振荡Hilbert-Huang变换（HHT）密集模态经验模态分解（EMD）屏蔽信号模态辨识滤波器
low-frequency oscillationHilbert-Huang transform(HHT)close modeempirical mode decomposition(EMD)masking signalmode identificationfilter
《高电压技术》 2012 (6)
1492-1499,8
河北省自然科学基金（E2010001693E2011502014）中央高校基本科研业务费专项资金（09MG07）~~
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