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Detection of voltage variation events using variational mode decomposition

Authors: Pankaj D. Achlerkar; S. R. Samantaray; M. Sabarimalai Manikandan;

Detection of voltage variation events using variational mode decomposition

Abstract

This paper presents a method of detecting voltage sag, swell and interruption events based on a signal processing tool viz. variational mode decomposition (VMD). The proposed method is able to keep track of variations in amplitude, phase, frequency and undelivered energy due to such events. Voltage signal is half-wave rectified and then decomposed by VMD to get DC part representing instantaneous amplitude envelope, thereby obtaining start/end times and depth of sag/swell. The phase jump and frequency deviations are observed from instantaneous phase, obtained from analytic signal of VMD mode having center frequency nearer to fundamental. Algorithm is tested for various cases of synthetic and simulated signals in MATLAB/Simulink. Comparative performance with recursive discrete Fourier transform and Hilbert transform based method is demonstrated.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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