A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring

In this paper, remote error monitoring techniques for electricity meters are overviewed suggesting their utilization for in-service surveillance assistance. It is discussed that in-service error observation could provide valuable input, contributing to the timely detection of batches of meters reach...

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Main Authors: Žilvinas Nakutis, Paulius Kaškonas
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/20/5245
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spelling doaj-6f346444e4194cf6a2cec4e6ec63a00a2020-11-25T03:35:21ZengMDPI AGEnergies1996-10732020-10-01135245524510.3390/en13205245A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error MonitoringŽilvinas Nakutis0Paulius Kaškonas1Electrical and Electronics Engineering Faculty, Kaunas University of Technology, 51368 Kaunas, LithuaniaElectrical and Electronics Engineering Faculty, Kaunas University of Technology, 51368 Kaunas, LithuaniaIn this paper, remote error monitoring techniques for electricity meters are overviewed suggesting their utilization for in-service surveillance assistance. It is discussed that in-service error observation could provide valuable input, contributing to the timely detection of batches of meters reaching nonconformance status. The payback period analysis of the deployment of a remote error monitoring solution is considered. However, it is pointed out that such an analysis lacks input information describing the relationship between the remote monitoring system’s performance and its ability to detect nonconformance of the batch. It is also noticed that there is no published methodology for grading the status of an entire batch of meters referring to error estimates of a subset of the meters, when the uncertainty of estimation is rather high.https://www.mdpi.com/1996-1073/13/20/5245power measurementremote monitoringwatt-hour meterstime series analysis
collection DOAJ
language English
format Article
sources DOAJ
author Žilvinas Nakutis
Paulius Kaškonas
spellingShingle Žilvinas Nakutis
Paulius Kaškonas
A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
Energies
power measurement
remote monitoring
watt-hour meters
time series analysis
author_facet Žilvinas Nakutis
Paulius Kaškonas
author_sort Žilvinas Nakutis
title A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
title_short A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
title_full A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
title_fullStr A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
title_full_unstemmed A Contemplation on Electricity Meters In-service Surveillance Assisted by Remote Error Monitoring
title_sort contemplation on electricity meters in-service surveillance assisted by remote error monitoring
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-10-01
description In this paper, remote error monitoring techniques for electricity meters are overviewed suggesting their utilization for in-service surveillance assistance. It is discussed that in-service error observation could provide valuable input, contributing to the timely detection of batches of meters reaching nonconformance status. The payback period analysis of the deployment of a remote error monitoring solution is considered. However, it is pointed out that such an analysis lacks input information describing the relationship between the remote monitoring system’s performance and its ability to detect nonconformance of the batch. It is also noticed that there is no published methodology for grading the status of an entire batch of meters referring to error estimates of a subset of the meters, when the uncertainty of estimation is rather high.
topic power measurement
remote monitoring
watt-hour meters
time series analysis
url https://www.mdpi.com/1996-1073/13/20/5245
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