Ring-down oscillation mode identification using multivariate Empirical Mode Decomposition

• Published in: 2016 IEEE Power and Energy Society General Meeting (PESGM) pp. 1 - 5
• Main Authors: Shutang You, Jiahui Guo, Wenxuan Yao, Siqi Wang, Yong Liu, Yilu Liu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-07-2016
• Subjects: Biomedical measurement; Empirical mode decomposition; Fluctuations; Generators; multivariate empirical model decomposition (MEMD); Oscillation mode analysis; Oscillators; synchrophasor measurements; Time-frequency analysis
• ISSN: 1944-9933
• DOI: 10.1109/PESGM.2016.7742032

Inter-area oscillation in a large power systems draws much attention because it might severely influence system security and reduce transmission capability. The recent large-scale deployment of phasor measurement units (PMUs) enables online measurement-based monitoring and analysis on inter-area oscillatory modes. However, the nonstationary characteristics of measurements become obstacles for oscillation analysis. This work proposes multivariate empirical mode decomposition (MEMD), a multi-channel time frequency analysis method, for ring-down oscillation mode identification. The capability of the MEMD in oscillation mode identification is verified based on a test system. In addition, MEMD is compared with classical Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT) for evaluation. The result shows that MEMD can improve oscillation identification through separating different oscillation modes while persevering their phase and amplitude information.