Empirical Mode Decomposition Based Prony's Method for Fundamental and Harmonics Analysis of Power System

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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“…Further, explanation of Prony analysis and implementation in identification of dominant oscillator modes can be found in [21], [22].…”

Section: Prony's Methodsmentioning

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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“…Electromagnetic target recognition is an ‘inverse problem’ where one is concerned with obtaining information of a scatterer from the scattered field response. This paper is concerned with natural frequency based radar target recognition, where the natural frequencies of a target are extracted and used for target recognition [1–21]. The objective of target recognition is not only to detect the existence of a target, but also to identify the target.…”

Section: Introductionmentioning

confidence: 99%