基于ISPM和SDM-Prony算法的电力系统低频振荡模式辨识

Identification of Power System Low Frequency Oscillations With ISPM and SDM-Prony

针对广域测量系统低频振荡辨识过程中的噪声干扰和定阶问题,提出了基于改进平滑优先方法(improved smoothness priors method,ISPM)和SDM定阶的Prony方法进行电力系统低频振荡模态辨识。首先将待处理信号经过ISPM滤波同时对高频干扰项和趋势项进行快速准确去除,然后对消噪后的信号进行SDM-Prony辨识,得到低频振荡的主导模态参数。该方法在定阶时能够根据奇异值分解的具体情况进行自动准确定阶,无需阈值的人为选取,使定阶具有自适应性。将该方法分别用于仿真信号和实测振荡信号分析,并和传统的Prony方法进行比较,该方法在拟合精度指标相差不大的情况下估计的阶数更加逼近真实阶数,并且具有运算简单、抗噪性能好等特点,可快速准确辨识出主导振荡模态信息。仿真结果表明,文中方法具有良好的实用性。

This paper proposes a novel Prony method for identifying low frequency oscillations in power systems based on improved smoothness priors method（ISPM） and second-derivative method（SDM）, determining order selection in low frequency oscillations using wide area measurement system. First, high frequency interference and trend components are removed rapidly and correctly with ISPM. Next, SDM-Prony identification is performed using denoised signal to obtain dominant mode parameters of low frequency oscillation. This method can automatically and accurately determine order according to specific conditions for singular value decomposition without artificially selecting threshold, making order determination self-adaptive. The proposed method is applied to simulated signal and actual oscillation signal measurements, and obtained results were compared with those produced with traditional Prony. Using the proposed method, estimated order was closer to actual order and fitting accuracy difference was not high. The proposed method was characterized with simple calculation and excellent anti-noise performance, able to identify dominant oscillation modes rapidly and accurately. Simulation result showed that this method has good practicability.