基于改进多信号矩阵束算法的电力系统低频振荡识别

摘要

提出了适用于电力系统低频振荡模态识别的改进多信号矩阵束算法。利用奇异值分解（Singular value decomposition， SVD）分离信号和噪声子空间，确定阶数并消除信号噪声。通过建立多信号归一化的样本函数矩阵对矩阵束算法进行改进，辨识电力系统模态。利用原始Prony法、谐波恢复的Prony法和改进的多信号矩阵束法，对理想信号和仿真系统进行分析。结果表明多信号矩阵束法的辨识精度较高，具有一定的抗噪能力，并且通过对多信号归一化的处理避免了不同类型信号叠加时较小信号的湮没，适用于低频振荡在线识别。%Modern power system has become complex and the size of the nonlinear systems makes the traditional analysis method present more and more limitations. Therefore this paper introduces an improved multi-signal matrix pencil algorithm suitable for low-frequency oscillations modal identification of power system. First, the method of singular value decomposition (SVD) is used to separate the signal from the noise sub-space, confirm the order and eliminate the signal noise. And then through the establishment of multi-signal normalized experiment matrix, the matrix pencil algorithm is improved to identify power system mode. The ideal signal and simulation system are analyzed by using the original Prony method, the harmonic retrieval Prony method and the matrix pencil method. Results show that multi-signal matrix pencil method has high precision and a certain anti-noise ability. Through the normalized processing of the multi-signal, the submerging of small signals is avoided when different types of signals are overlying, thus it is suitable for low frequency oscillation on-line identification.