Persistent-Homology-based Detection of Power System Low-frequency Oscillations using PMUs Conference Paper uri icon

abstract

  • 2016 IEEE. This paper presents a new methodology to detect low-frequency oscillations in power grids by use of time-synchronized data from phasor measurement units (PMUs). Principal component analysis (PCA) is first applied to the massive PMU data to extract the low-dimensional features, i.e., the principal components (PCs). Then, based on persistent homology, a cyclicity response function is proposed to detect low-frequency oscillations through the use of PCs. Whenever the cyclicity response exceeds a numerically robust threshold, a low-frequency oscillation can be detected instantly. Such swift detection can then be followed by modal analysis tools for more detailed information about the oscillation. Numerical examples using real data illustrate the effectiveness of the proposed methodology for quick detection of oscillations during operations.

name of conference

  • 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

published proceedings

  • 2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP)

author list (cited authors)

  • Chen, Y., Chintakunta, H., Xie, L. e., Baryshnikov, Y. M., & Kumar, P. R.

citation count

  • 0

complete list of authors

  • Chen, Yang||Chintakunta, Harish||Xie, Le||Baryshnikov, Yuliy M||Kumar, PR

publication date

  • January 2016