摘要
针对现有的电力系统次同步振荡的检测方法存在对噪声敏感、振荡的特征和变化趋势难以获得的局限性,提出将频率切片小波变换(FSWT)方法应用于次同步振荡的分析和参数辨识。FSWT方法自由切割时频面,实现信号频率区间的灵活分割,可以实现对次同步振荡信号的总体和细化分析。首先,采用FSWT方法对含噪的次同步振荡信号进行总体时频分析,得到其时频能量分布。根据时频能量分布,可以预判是否发生次同步振荡、确定模态分量的数量及其频率分布区间。然后,合理选择频率切片区间,进行细化特征分析,通过对信号特征频率切片区间信号的重构,实现了次同步振荡的模态分量的分离及提取。最后,结合Hilbert变换获得高准确度的次同步振荡模态参数。
It is hard to use the existing methods to effectively identify subsynchronous oscillation(SSO)of power system.Most methods are sensitive to noise,and it is difficult to obtain the characteristic and development trend of oscillation.In this paper,a method using Frequency Slice Wavelet Transform(FSWT)is proposed for analysis and parameter identification of SSO.FSWT can cut time-frequency areas freely,so that full band time-frequency distribution analysis and fine analysis can be realized.Firstly,SSO signal is decomposed by FSWT and the full band of its time-frequency distribution is obtained.After that,due to its energy distribution,the occurrence of SSO can be predicted,and determined the number and frequency slices of modal components can be determined.Through reconstructing signals in characteristic frequency slices,separation and extraction of SSO mode components are realized.Finally,high-accuracy detection for modal parameter identification is achieved by the Hilbert transform.
作者
赵妍
李武璟
聂永辉
Zhao Yan;Li Wujing;Nie Yonghui(School of Power Transmission and Distribution Technology Northeast Electric Power University Jilin 132012 China;School of Electrical Engineering and Automation Harbin Institute of Technology Harbin 150001 China)
出处
《电工技术学报》
EI
CSCD
北大核心
2017年第6期106-114,共9页
Transactions of China Electrotechnical Society
基金
国家自然科学基金(51577023)
东北电力大学博士科研启动基金(BSJXM-2016240)资助项目
关键词
次同步振荡
时频分析
频率切片小波变换
参数辨识
Subsynchronous oscillation
time frequency analysis
frequency slice wavelet transform
parameter identification
