Statistical Behavior of Low-Amplitude Power System Point-on-Wave Measurements

Aaron J. Wilson; Ali Riza Ekti

doi:10.1109/TPWRD.2024.3406991

Statistical Behavior of Low-Amplitude Power System Point-on-Wave Measurements

Aaron J. Wilson, Ali Riza Ekti

Grid Communications and Security

Research output: Contribution to journal › Article › peer-review

Abstract

The power grid is undergoing massive changes to ensure resiliency and reliability in a more decentralized world. Distributed energy resources are becoming a prominent source of generation, potentially leading to a lack of centralized generation sources. Due to these new behaviors and system topologies, it is important to install measurement devices that are 1) accurate and 2) self-aware of their measurement quality. In this paper, a residential-scale microgrid is used to generate voltage and current waveforms, captured by Verivolt and National Instruments measurement equipment. A least-squares approach is used to separate the "clean"signals from the noise. Gaussian mixture modeling is used to approximate noise distributions, and it is shown these higher-order distribution estimates are a better fit to voltage and current noise profiles than single-mode Gaussian estimates.

Original language	English
Pages (from-to)	3547-3550
Number of pages	4
Journal	IEEE Transactions on Power Delivery
Volume	39
Issue number	6
DOIs	https://doi.org/10.1109/TPWRD.2024.3406991
State	Published - 2024

Funding

This work was supported in part by the US Department of Energy (DOE), Office of Electricity, under Contract DE-AC05-00OR22725 with UT-Battelle, LLC, for the US DOE, and in part by the AI Initiative Project funded by Oak Ridge National Laboratory.

Funders	Funder number
U.S. Department of Energy
Oak Ridge National Laboratory
Office of Electricity	DE-AC05-00OR22725
Office of Electricity

Keywords

Gaussian mixture modeling
noise estimation
power system measurement

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10.1109/TPWRD.2024.3406991

Cite this

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AB - The power grid is undergoing massive changes to ensure resiliency and reliability in a more decentralized world. Distributed energy resources are becoming a prominent source of generation, potentially leading to a lack of centralized generation sources. Due to these new behaviors and system topologies, it is important to install measurement devices that are 1) accurate and 2) self-aware of their measurement quality. In this paper, a residential-scale microgrid is used to generate voltage and current waveforms, captured by Verivolt and National Instruments measurement equipment. A least-squares approach is used to separate the "clean"signals from the noise. Gaussian mixture modeling is used to approximate noise distributions, and it is shown these higher-order distribution estimates are a better fit to voltage and current noise profiles than single-mode Gaussian estimates.

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Statistical Behavior of Low-Amplitude Power System Point-on-Wave Measurements

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