基于FastICA-MP算法的次同步振荡模态参数辨识

Parameter identification of subsynchronous oscillation based on Fast ICA-MP algorithm

WAMS在电力系统中的应用越来越广,使得电力系统次同步振荡模态参数在线辨识成为可能。但系统中存在大量电力电子设备,造成了WAMS采样信号中存在较强的噪声干扰,影响了振荡模态参数辨识的准确性。鉴于快速独立分量分析可以实现噪声信号与原始信号的有效分离,提出首先通过快速独立分量分析对采样信号进行预处理,然后将滤噪后的信号通过矩阵束算法进行辨识得到振荡模态参数。通过此方法可以进一步提高矩阵束的辨识准确度。通过理想仿真算例和国内某特高压直流输电系统作为实际仿真算例进行分析。仿真结果表明,快速独立分量分析可有效分离噪声信号,提高了矩阵束辨识准确性,为后续阻尼控制器的设计奠定了基础。

The online identification of subsynchronous oscillation modal parameter became possible with a wide use of WAMS in power system. However, there is much power electronic equipment in the power system, which causes strong interference noises in WAMS sampled signal, and the veracity of vibration modal parameters is influenced. Because of the Fast Independent Component Analysis （FastICA） could separate noise signal from observed signal. This paper first presents to pretreat sampling signal through the FastlCA. And then it identifies the denoised signals through Matrix Pencil （MP） to obtain the oscillation modal parameter, with which he recognition accuracy of MP could be enhanced based on FastICA-ME This paper takes an ideal example and a UHVDC system in China as the simulation examples. The simulation results show that the FastICA can separate noise signal effectively and improve the MP identification accuracy, laying the foundations for the design of supplementary subsynchronous damping controller.