IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i20p5245-d425442.html
   My bibliography  Save this article

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

Author

Listed:
  • Žilvinas Nakutis

    (Electrical and Electronics Engineering Faculty, Kaunas University of Technology, Kaunas 51368, Lithuania)

  • Paulius Kaškonas

    (Electrical and Electronics Engineering Faculty, Kaunas University of Technology, Kaunas 51368, Lithuania)

Abstract

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.

Suggested Citation

  • Žilvinas Nakutis & Paulius Kaškonas, 2020. "A Contemplation on Electricity Meters In-Service Surveillance Assisted by Remote Error Monitoring," Energies, MDPI, vol. 13(20), pages 1-13, October.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5245-:d:425442
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/20/5245/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/20/5245/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiangyu Kong & Yuying Ma & Xin Zhao & Ye Li & Yongxing Teng, 2019. "A Recursive Least Squares Method with Double-Parameter for Online Estimation of Electric Meter Errors," Energies, MDPI, vol. 12(5), pages 1-16, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kong, Xiangyu & Zhang, Xiaopeng & Li, Gang & Dong, Delong & Li, Ye, 2020. "An estimation method of smart meter errors based on DREM and DRLS," Energy, Elsevier, vol. 204(C).
    2. Anastasios Dounis, 2019. "Special Issue “Intelligent Control in Energy Systems”," Energies, MDPI, vol. 12(15), pages 1-9, August.
    3. Qingsheng Zhao & Juwen Mu & Xiaoqing Han & Dingkang Liang & Xuping Wang, 2021. "Evaluation Model of Operation State Based on Deep Learning for Smart Meter," Energies, MDPI, vol. 14(15), pages 1-17, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5245-:d:425442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.