Persistent-Homology-Based Detection Of Power System Low-Frequency Oscillations Using Pmus

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.