Abstract
In this paper, the application of the Prony’s method based on Empirical Mode Decomposition (EMD) and Ensembled Empirical Mode Decomposition (EEMD) for identification of dominant modal parameter, oscillation frequency, is presented. The validation of the methods are done on real frequency signal obtained from FNET/GridEye, GPS-synchronized wide-area frequency measurement network obtained during tornado outbreak in Southeastern U.S. According to many studies and reports, the values of dominant modal parameters from such event, are already known, and have been used to compare method performance and accuracy of results. Firstly, EMD and EEMD are performed over the frequency time series to obtain intrinsic mode functions IMFs, on which the Prony’s method for frequency oscillation extraction is further applied. In addition, according to obtained results the proposed methods have proven to be reliable for identification of the model parameters of low-frequency oscillation in power systems.
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Dedovic, M.M., Mujezinović, A., Dautbasic, N. (2021). Identification on Dominant Oscillation Based on EMD and Prony’s Method Approach. In: Avdaković, S., Volić, I., Mujčić, A., Uzunović, T., Mujezinović, A. (eds) Advanced Technologies, Systems, and Applications V. IAT 2020. Lecture Notes in Networks and Systems, vol 142. Springer, Cham. https://doi.org/10.1007/978-3-030-54765-3_8
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