[1]邱炳林.基于SURE小波与ITD法的电力系统模态辨识[J].福建工程学院学报,2023,21(04):370-377.[doi:10.3969/j.issn.1672-4348.2023.04.010]
　QIU Binglin.Power system modal identification based on SURE wavelet and ITD method[J].Journal of FuJian University of Technology,2023,21(04):370-377.[doi:10.3969/j.issn.1672-4348.2023.04.010]
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基于SURE小波与ITD法的电力系统模态辨识()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第21卷
期数:
2023年04期
页码:
370-377
栏目:
出版日期:
2023-08-25

文章信息/Info

Title:
Power system modal identification based on SURE wavelet and ITD method
作者:
邱炳林
厦门大学嘉庚学院
Author(s):
QIU Binglin
Tan Kah Kee College, Xiamen University
关键词:
电力系统; 低频振荡; 模态辨识; SURE小波; 固有时间尺度
Keywords:
power system;  lowfrequency oscillation;  modal identification;  SURE wavelet;  intrinsic time scale
分类号:
TM712
DOI:
10.3969/j.issn.1672-4348.2023.04.010
文献标志码:
A
摘要:
针对因互联系统稳定性的下降引起的低频振荡事故,提出了基于无偏似然估计(stein unbiasedrisk estimate,SURE)的自适应小波阈值与固有时间尺度分解(intrinsic time?scale decomposition,ITD)的联合辨识算法,以解决在低频振荡的关键模态辨识中提取出的参数精度不够准确的问题。对含有噪声干扰的信号进行小波变换得到其小波系数,根据信号特点按照最小均方误差算法估计其最优阈值,从而进行小波系数的筛选和信号的重构,得到去除噪声后的信号。对处理后的信号进行固有时间尺度分解,构建相应的信号测点矩阵并求解矩阵的特征值,获取系统的关键振荡参数。采用数学测试信号、PSASP软件中的8机36节点仿真系统信号以及实测信号,验证了所提方法对实际电网是有效可行的。
Abstract:
Aiming at the lowfrequency oscillation accidents caused by the decline of the stability of the interconnected system, a joint identification algorithm of adaptive wavelet threshold and intrinsic timescale decomposition (ITD) based on stein unbiased risk estimate (SURE) was proposed to solve the problem that the accuracy of the extracted parameters is not accurate in the identification of key modes of lowfrequency oscillation. Firstly, the wavelet transformation was performed on the signal containing noise interference, each wavelet coefficient was obtained, and the optimal threshold was estimated according to the minimum mean square error algorithm based on the characteristics of the signal, so as to screen the wavelet coefficient and reconstruct the signal, thus obtaining the signal after removing noise. Secondly, the processed signal was decomposed on the intrinsic time scale, the corresponding signal measurement point matrix was constructed and the eigenvalues of the matrix were solved, so as to obtain the key oscillation parameters of the system. Finally, the mathematical test signals, 8machine 36node simulation system signals and measured signals in PSASP software were used to verify the effective feasibility of the proposed method in practice.

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更新日期/Last Update: 2023-08-25