Subsynchronous oscillation detection based on Kmeans clustering and frequency synchrosqueezing wavelet transforms
Author:
Affiliation:

Clc Number:

TM763

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Power system has nonstationary and nonlinear characteristics of the subsynchronous oscillation (SSO), it is difficult for existing detection methods to capture the oscillation characteristics and the changing trend. In this paper, an oscillation detection approach, which combines Kmeans clustering and synchrosqueezed wavelet transform (SWT), is proposed to achieve the harmonic detection and analysis of subsynchronous oscillation. The antimodal aliasing ability and antinoise ability of the SWT are utilized to clearly and intuitively show the oscillation modes of the signals with noise. The frequency domain slicing is employed in the SWT to extract multiple oscillation modes for the reconstruction and the parameter identification. Considering that the SWT will squeeze the wavelet coefficients to the central frequency, the Kmeans clustering method is applied to calculate the central frequency of the oscillating signal. At the same time, the frequency interval of the signal can be automatically selected for reconstruction. Finally, the simulations are conducted to examine the effectiveness of the proposed method.

    Reference
    Related
    Cited by
Get Citation

刘韶峰,徐泰山,鲍颜红,陈颖杰.基于K-means聚类和同步挤压小波变换的次同步振荡检[J].电力科学与技术学报英文版,2021,36(4):132-140. Liu Shaofeng, Xu Taishan, Bao Yanhong, Chen Yingjie. Subsynchronous oscillation detection based on Kmeans clustering and frequency synchrosqueezing wavelet transforms[J]. Journal of Electric Power Science and Technology,2021,36(4):132-140.

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: August 28,2021
  • Published: