IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i11p4326-d1155703.html
   My bibliography  Save this article

Experimental Performance Analysis of Hardware-Based Link Quality Estimation Modelling Applied to Smart Grid Communications

Author

Listed:
  • Natthanan Tangsunantham

    (Research Centre of Advanced Metering Infrastructure (AMI), The Sirindhorn International Thai-German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1 Rd. Bangsue, Bangkok 10800, Thailand)

  • Chaiyod Pirak

    (Research Centre of Advanced Metering Infrastructure (AMI), The Sirindhorn International Thai-German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, 1518 Pracharat 1 Rd. Bangsue, Bangkok 10800, Thailand)

Abstract

The smart grid is the modern electricity grid, which significantly improves the efficiency, reliability, and sustainability of electricity transmission systems. The advanced metering infrastructure (AMI) system, which is the essential system in the smart grid, enables real-time data collection and data analysis obtained from smart meters (SMs) and other devices through last-mile communication networks. In this paper, the hardware-based link quality estimation (LQE) was modeled, namely an SNR-based model, a mapping model, and an RSSI- and PRR-based logistic regression model, and their performance was then evaluated by the root mean-squared error (RMSE) with the empirical data. The SNR-based and mapping models were formulated by the packet error probability, whereas the RSSI- and PRR-based logistic regression model was formulated by the empirical data fitting. The RSSI- and PRR-based logistic regression model outperformed the other two models, with an RMSE difference of 111–122%. These LQE models can be implemented on SMs or modems to monitor the reliability and efficiency of the AMI last-mile communication network.

Suggested Citation

  • Natthanan Tangsunantham & Chaiyod Pirak, 2023. "Experimental Performance Analysis of Hardware-Based Link Quality Estimation Modelling Applied to Smart Grid Communications," Energies, MDPI, vol. 16(11), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4326-:d:1155703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/11/4326/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/11/4326/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Natthanan Tangsunantham & Chaiyod Pirak, 2022. "Experimental Performance Analysis of Wi-SUN Channel Modelling Applied to Smart Grid Applications," Energies, MDPI, vol. 15(7), pages 1-15, March.
    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.

      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:16:y:2023:i:11:p:4326-:d:1155703. 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.