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The widespread deployment of phasor measurement unit (PMU) overpower systemsmakes it possible to monitor and analyze grid dynamics in real-time.Low-frequency oscillation is harmful to power system equipment and operation,and in the worst-case scenario may lead to cascading failures. Therefore, it iscritical to detect and identify them as soon as they appear. This paperpresents an online low-frequency oscillation detection and analysis (LFODA)system, which has the merit of significantly reducing the chance of false alarmvia a voting schema and a time-serial filter. A novel algorithm based ondensity-based spatial clustering of applications with noise (DBSCAN) isproposed to classify oscillation modes as well as to group their correspondingbuses/monitoring sites. Performance of the LFODA system is evaluated throughexperiments using both simulated and real-world PMU data.

Online Low Frequency Oscillation Detection and Analysis System with an Ensemble Filter