In this section
@inproceedings{Chen:2026,
author = {Chen, Y and Bhattacharjee, D and Chaudhuri, B and O'Malley, M and Qin, N and Expethit, AP},
publisher = {IEEE},
title = {Data-driven post-event analysis with real-world oscillation data from Denmark},
year = {2026}
}
TY - CPAPER
AB - This paper demonstrates how Extended Dynamic Mode Decomposition (EDMD), grounded in Koopman operator theory, can effectively identify the main contributor(s) to oscillations in power grids. We use PMU data recorded from a real 0.16 Hz oscillation event in Denmark for post-event analysis. To this end, the EDMD algorithm processed only voltage and current phasors from nineteen PMUs at different voltage levels across the Danish grid. In such a blind-test setting with no supplementary system information, EDMD accurately pinpointed the location of the main contributor to the 0.16 Hz oscillation. Energinet later confirmed that this was a 145 MW solar photovoltaic (PV) park with control system issues. Notably, conventional approaches, such as the dissipating energy flow (DEF) method used in the ISO-NE OSLp tool did not correctly identify this plant. This joint validation with Energinet, reinforcing earlier studies using simulated IBR-dominated systems and real PMU data from ISO-NE, highlights the potential of EDMD-based post-event analysis for identifying major oscillation contributors and enabling targeted SSO mitigation.
AU - Chen,Y
AU - Bhattacharjee,D
AU - Chaudhuri,B
AU - O'Malley,M
AU - Qin,N
AU - Expethit,AP
PB - IEEE
PY - 2026///
TI - Data-driven post-event analysis with real-world oscillation data from Denmark
ER -