基于MSST-HT的次同步振荡参数辨识研究

次同步振荡是在电力系统运行平衡点受到扰动后产生的一种异常电磁及机械振荡现象。针对希尔伯特黄变换在次同步振荡分量提取时存在噪声干扰和模态混叠问题,提出一种适用于次同步振荡参数辨识的多重同步压缩变换（MSST）和希尔伯特变换结合的方法。该方法在傅里叶同步压缩变换基础上,对次同步振荡信号时频谱进行多次同步压缩,以此来提高信号时频分布的重构精度和能量聚集程度。通过仿真并结合实际工程录波数据进行验证,首先使用多重同步压缩变换方法对信号进行时频分析,得到信号时频图,然后用多重同步压缩变换变换逆变换分解重构出各个模态分量,最后用希尔伯特变换对提取出来的单个模态分量进行参数辨识,识别其频率、阻尼比、衰减因子等主要参数。仿真结果表明,相比于短时傅里叶变换（STFT）、同步提取变换（SET）和傅里叶同步挤压变换（FSST）,MSST能够提高信号时频分布的能量聚集程度和重构精度,能够实现多分量的次同步振荡模态分解。实际数据结果表明该方法能有效克服噪声干扰和模态混叠问题,准确辨识次同步震荡参数,对电力系统安全稳定运行具有一定的参考意义。

Research on parameter identification of subsynchronous oscillation based on MSST HT

Subsynchronous oscillation is a kind of abnormal electromagnetic and mechanical oscillation which occurs when the equilibrium point of power system is disturbed. Aiming at the problems of noise interference and mode aliasing in the extraction of sub synchronous oscillation components by the Hilbert Huang transform, a method combining multisyn chrosqueezing transform (MSST) and Hilbert transform is proposed to identify sub synchronous oscillation parameters. Based on Fourier synchronous compression transform, the frequency spectrum of sub synchronous oscillating signal is compressed synchronously for several times, so as to improve the reconstruction accuracy of signal time frequency distribution and the degree of energy aggregation. Through simulation and verification combined with actual engineering recording data, firstly, the signal time frequency analysis was carried out using the multi synchronous compression transform method to obtain the signal time frequency diagram, and then the multi synchronous compression transform transform inverse transformation decomposition was used to reconstruct each modal component, and finally the extracted single modal component parameter identification was carried out using the Hilbert transform. Identify its frequency, damping ratio, attenuation factor and other major parameters. The simulation results show that compared with short time Fourier transform (STFT) and synchroextracting transform(SET) and Fourier based synchrosqueezing transform (FSST). MSST can improve the energy concentration degree and reconstruction accuracy of signal time frequency distribution, and realize multi component sub synchronous oscillation mode decomposition. The actual data show that the method can overcome the noise interference and mode aliasing effectively, identify the sub synchronous oscillation parameters accurately, and has certain reference significance for the safe and stable operation of power system.