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Arabian Journal for Science and Engineering

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25-06-2021 | Research Article-Electrical Engineering

Dominant Electromechanical Oscillation Mode Identification using Modified Variational Mode Decomposition

Authors: Rahul S, Sunitha R

Published in: Arabian Journal for Science and Engineering | Issue 10/2021

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Abstract

Following the widespread implementation of Phasor Measurement Units (PMU) across the power grid, the measurement-based methods are extensively used to track power system oscillations efficiently in real-time. This paper proposes a novel dynamic approach for rapid monitoring and identification of electromechanical oscillation modes using real-time measurement signals. The measurement-based method has been recently improved by the Variational Mode Decomposition (VMD) technique, a nonlinear, nonstationary analysis tool used to estimate low-frequency modes in the power system. However, the random selection of the initial parameter utilized in the conventional VMD process significantly affects its performance and often leads to computational complexities. Thus, a Modified Variational Mode Decomposition (MVMD) method based on Particle Swarm Optimization (PSO) has been proposed in this work. MVMD eliminates unnecessary decomposition modes involved in the conventional VMD process by optimizing parameters using PSO. The analysis of these modes is accomplished by assessing instantaneous modal parameters using the Hilbert transform and spectral analysis. The raised approach is validated using a test signal, IEEE standard 16 machine 68 bus system and real-world PMU data. Simulation results show that the dominant low-frequency oscillatory mode with high noise tolerance can be effectively determined with less computational complexity.

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Title: Dominant Electromechanical Oscillation Mode Identification using Modified Variational Mode Decomposition
Authors: Rahul S
Sunitha R
Publication date: 25-06-2021
Publisher: Springer Berlin Heidelberg
Published in: Arabian Journal for Science and Engineering / Issue 10/2021
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI: https://doi.org/10.1007/s13369-021-05818-x

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