| Title |
Oscillation Theories in Various Systems and Detection in Power Systems Using Prony Analysis |
| Authors |
최윤성(Yoon-Seong Choi) ; 이동호(Dongho Lee) |
| DOI |
https://doi.org/10.5370/KIEE.2025.74.3.377 |
| Keywords |
Power System Oscillation; Prony Analysis; RMS Energy Filter; Spring-Mass System; Barkhausen criteria; Eigenvalue |
| Abstract |
The integration of inverter-based renewable energy sources in power systems affects frequency stability and oscillation characteristics, posing challenges to system reliability. Complex interactions between generators' dynamic behaviors and transient electrical flows complicate oscillation detection. This study reviews oscillation theories, such as the spring-mass system and radio frequency oscillation, which help explain oscillation mechanisms but are limited in detecting power system oscillations. To address this, the study applies Prony analysis, which models time-series data as a sum of exponential functions, and compares it with RMS Energy Filtering. The proposed algorithm, combining these methods, is tested on real power system data from the U.S., successfully detecting primary oscillation modes and damping characteristics. The results highlight the method’s accuracy in identifying critical oscillation frequencies and the importance of selecting an appropriate order in Prony analysis to prevent overfitting or underfitting. |