HHT算法在电力系统低频振荡模态辨识中的应用

Application of Hilbert Huang Transform Algorithm for Model Identification of Low Frequency Oscillation in Power Systems

针对电力系统低频振荡信号的非线性、非平稳特征,提出了一种新的处理方法——希尔伯特-黄变换(HHT)。该方法能够克服传统分析难以处理非平稳信号的缺点;利用其中的经验模态分解(EMD)对信号模态分量的有效分离,对分量进行Hilbert变换,得到相应的参量。通过计算实现对振荡信号的模态参数的辨识与提取,因此该方法能够应用到阻尼控制器的设计中。仿真结果表明该控制器能有效地抑制电力系统低频振荡,提高了系统的安全稳定性。

Aiming at the characteristics of nonlinear and non-stationary of low frequency oscillation signal in power system, this paper raised a kind of new method, Hilbert-Huang transform, which overcame the shortcoming that it was difficult for traditional analysis to deal with non- stationary signals. The empirical mode decomposition （EMD） method was used to decompose the low frequency oscillation signals mad then car- fled out Hilbert transform for each model component to get corresponding parameters. The model parameters of oscillation signals were identified and extracted by calculation, so this method could be used for the damping controller design. The simulation results show that the controller can restrain low frequency oscillation of power system effectively, improving the safety and stability of the system..