多信号模态参数识别的小波方法

Wavelet analysis based modal parameter identification from multiple signals

在小波分析的基础上,采用优化方法同时从多个信号提取电力系统振荡模式和模态。首先根据小波脊线处的小波系数幅值判断信号对待辨识模式的可观程度,舍去可观性较小的信号后,进一步采用优化方法协调剩余信号中的模式参数。同时,根据这些信号在脊点处的小波系数,辨识系统的振荡模态参数。由于待辨识模式在各信号中能量衰减至零的时刻不同,为便于模态分析,提出在统一的辨识区间辨识系统的模式参数。4机2区域系统和10机新英格兰系统算例表明,所提出的方法可提高振荡频率和阻尼参数的辨识精度,同时还可以获得多信号间的模态信息。

An optimization method based on wavelet analysis is applied to identify the mode and modal shape of power system oscillation from multiple signals,which judges the mode observability of each signal according to the wavelet coefficients at wavelet ridge and adopts an Optimization method to coordinate the mode parameters of signals with higher observability while neglects those with poor observability. The modal shape is also identified according to the wavelet coefficients at wavelet ridge. Because the energy of mode to be identified decays to zero at different times in different signals,a unified identification interval is proposed to identify the system modal parameters for easy modal shape analysis. Case study for a 2-area 4-machine system and the 10-machine New England system demonstrates that the identification accuracy of oscillation frequency and damping parameters is improved and the modal shape information among multiple signals is obtained.