基于改进EMD去噪和矩阵束的电力系统低频振荡模态辨识

doi:10.3969/j.issn.0255-8297.2019.06.001

摘要/Abstract

摘要： 提出了一种电力系统低频振荡模态辨识方法.首先使用改进的经验模态分解（empirical mode decomposition，EMD）去噪算法对低频振荡信号进行预处理.针对传统EMD去噪时混叠噪声严重和计算时间较长的问题，在区间阈值处理的基础上向信号叠加余弦波并进行二次分解，可以快速有效地实现信噪分离.随后再利用矩阵束（matrix pencil，MP）算法提取模态参数.对于MP算法的关键定阶问题，引入奇异值的相对差值作为定阶指标，可以实现较为准确的阶数估计.最后对数值信号、系统仿真信号和电网实测信号进行分析.仿真结果表明，所提方法在抗噪能力、参数精度和计算速度等方面都表现优异.

关键词: 低频振荡, 模态辨识, 经验模态分解, 矩阵束, 奇异值分解

Abstract: The paper proposes a mode identification method for low frequency oscillations in power system. First, an improved empirical mode decomposition (EMD) denoising algorithm is employed for signal preprocessing. The algorithm superimposes a cosine wave onto the signal and conducts a second decomposition after implementing the interval thresholding. It overcomes the shortcomings of serious aliasing noise and long computing time, which exist in the conventional algorithms, and separates the signal and noise in a fast and effective manner. After signal denoising, the matrix pencil (MP) algorithm is used to extract mode parameters. Introducing relative difference of singular values can solve the key problem of order determination in MP algorithm, thus leading to an accurate estimation for model order. Lastly, numerical signals, system simulation signals and tested power grid signals are analyzed. Simulation results show that the proposed method achieves excellent performance in anti-noise ability, parameter accuracy and computing speed.

Key words: low frequency oscillation, mode identification, empirical mode decomposition (EMD), matrix pencil, singular value decomposition

中图分类号:

TM712

沈钟婷, 丁仁杰. 基于改进EMD去噪和矩阵束的电力系统低频振荡模态辨识[J]. 应用科学学报, 2019, 37(6): 761-774.

SHEN Zhongting, DING Renjie. Power System Low Frequency Oscillation Mode Identification Based on Improved EMD Denoising and Matrix Pencil Algorithm[J]. Journal of Applied Sciences, 2019, 37(6): 761-774.

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