TY - GEN
T1 - Persistent-homology-based detection of power system low-frequency oscillations using PMUs
AU - Chen, Yang
AU - Chintakunta, Harish
AU - Xie, Le
AU - Baryshnikov, Yuliy M.
AU - Kumar, P. R.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/4/19
Y1 - 2017/4/19
N2 - 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.
AB - 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.
KW - Detection
KW - Low-frequency oscillation
KW - Persistent homology
KW - Phasor measurement unit
KW - Principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=85019184826&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019184826&partnerID=8YFLogxK
U2 - 10.1109/GlobalSIP.2016.7905952
DO - 10.1109/GlobalSIP.2016.7905952
M3 - Conference contribution
AN - SCOPUS:85019184826
T3 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
SP - 796
EP - 800
BT - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Y2 - 7 December 2016 through 9 December 2016
ER -