Persistent-homology-based detection of power system low-frequency oscillations using PMUs

Yang Chen, Harish Chintakunta, Le Xie, Yuliy M. Baryshnikov, P. R. Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages796-800
Number of pages5
ISBN (Electronic)9781509045457
DOIs
Publication statusPublished - Apr 19 2017
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: Dec 7 2016Dec 9 2016

Publication series

Name2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings

Conference

Conference2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
CountryUnited States
CityWashington
Period12/7/1612/9/16

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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    Chen, Y., Chintakunta, H., Xie, L., Baryshnikov, Y. M., & Kumar, P. R. (2017). Persistent-homology-based detection of power system low-frequency oscillations using PMUs. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 796-800). [7905952] (2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7905952