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research article

Step detection in power system waveforms for improved RoCoF and frequency estimation

Karpilow, Alexandra  
•
Derviskadic, Asja  
•
Frigo, Guglielmo  
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November 1, 2022
Electric Power Systems Research

The evaluation of the signal frequency and Rate of Change of Frequency (RoCoF) from voltage or current waveforms is used for critical grid control, monitoring and protection applications. However, when step changes in the amplitude or phase of the signal occur, conventional frequency and RoCoF estimation methods, typically based on phasor models, are highly unreliable and can yield large frequency errors. To address this issue, this paper proposes a technique that uses dictionaries based on common signal dynamic models to identify and track amplitude and/or phase steps in AC signals. Additional signal dynamics including amplitude modulations, frequency ramps and harmonic tones are also characterized. Distinct from a previous iteration of this method developed by the authors, the proposed Step Change Detection (SCD) technique separates the envelope and angle of the signal's analytic form for independent analysis of these components. For numerical validation the method is applied to synthetically generated signals with challenging combinations of signal dynamics. The technique is shown to greatly improve frequency and RoCoF approximations as compared to state-of-the-art phasor estimation methods.

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Type
research article
DOI
10.1016/j.epsr.2022.108527
Web of Science ID

WOS:000856623900032

Author(s)
Karpilow, Alexandra  
Derviskadic, Asja  
Frigo, Guglielmo  
Paolone, Mario  
Date Issued

2022-11-01

Publisher

Elsevier

Published in
Electric Power Systems Research
Volume

212

Article Number

108527

Subjects

Engineering, Electrical & Electronic

•

Engineering

•

amplitude and phase steps

•

compressed sensing

•

event detection

•

frequency

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power system dynamics

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synchrophasor

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
DESL  
DESL  
Available on Infoscience
October 24, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/191553
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