2018/12/29 by Desong Bian, Zhe Yu, Bian, Desong +7
Engineering · #FOS: Electrical engineering #Optimal Power Flow Distribution #Power System Optimization and Stability #Power System Reliability and Maintenance #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1812.11266
openalex publication_date 2018/12/29 · openalex created_date 2019/05/03 · openalex updated_date 2026/07/28
The widespread deployment of phasor measurement unit (PMU) overpower systems makes 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 is critical to detect and identify them as soon as they appear. This paper presents an online low-frequency oscillation detection and analysis (LFODA) system, which has the merit of significantly reducing the chance of false alarm via a voting schema and a time-serial filter. A novel algorithm based on density-based spatial clustering of applications with noise (DBSCAN) is proposed to classify oscillation modes as well as to group their corresponding buses/monitoring sites. Performance of the LFODA system is evaluated through experiments using both simulated and real-world PMU data.