Identifications of Power System Dominant Low-Frequency Eletromechanical Oscillations Using Hilbert Marginal Spectrum

Dedović, Maja Muftić; Avdaković, Samir

doi:10.1007/978-3-319-71321-2_17

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“…The Wavelet transform analysis of disturbance identification and the analysis and identification of low-frequency electromechanical oscillations (LFEOs) in power systems is presented in [12]. A method for LFO identification based on Hilbert Huang transform was proposed in [13], [14]. This paper introduces the techniques for identification and analysis of low frequency oscillations in power system.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Different Methods for Identification of Dominant Oscillation Mode

Dedović

Avdaković

Mujezinović

et al. 2020

B&H Electrical Engineering

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This paper introduces and compares the various techniques for identification and analysis of low frequency oscillations in a power system. Inter-area electromechanical oscillations are the focus of this paper. After multiresolution decomposition of characteristic signals, physical characteristics of system oscillations in signal components are identified and presented using the Fourier transform, Prony’s method, Matrix Pencil Analysis Method, S-transform, Global Wavelet Spectrum and Hilbert Huang transform (Hilbert Marginal Spectrum) in time-frequency domain representation. The analyses were performed on real frequency signals obtained from FNET/GridEye system during the earthquake that triggered the shutdown of the North Anna Nuclear Generating Station in the east coast of the United States. In addition, according to the obtained results the proposed methods have proven to be reliable for identification of the model parameters of low-frequency oscillation in power systems. The relevant analyses are carried out in MATLAB coding environment.

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Section: Introductionmentioning

confidence: 99%