IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v8y2012i2p214068.html
   My bibliography  Save this article

Wireless Link-Quality Estimation in Smart Grid Environments

Author

Listed:
  • V. C. Gungor
  • M. K. Korkmaz

Abstract

Recently, wireless sensor networks (WSNs) have gained great attention from the research community for various smart grid applications, including advanced metering infrastructure (AMI), power outage detection, distribution automation, towers and poles monitoring, line fault diagnostics, power fraud detection, and underground cable system monitoring. However, multipath, fading, environmental noise, and obstructions in harsh smart grid environments make reliable communication a challenging task for wireless-sensor-network- (WSN-) based smart grid applications. To overcome varying link conditions in smart grid environments, sensor nodes must be capable of estimating link quality dynamically and reliably. In this paper, the performance of the state-of-the-art link-quality estimation methods is investigated for different smart power grid environments, such as outdoor substation, underground network transformer vault, and main power control room, in terms of packet delivery ratio, average number of packet retransmissions, average number of parent changes, average number of hops, and average communication delay. In addition, main smart grid characteristics and potential applications of WSNs in smart grid have been introduced along with the related technical challenges. Overall, our performance evaluations show that the link-quality estimators, called Expected Transmission Count (ETX) and four-bit, show the best performance in harsh smart grid environments.

Suggested Citation

  • V. C. Gungor & M. K. Korkmaz, 2012. "Wireless Link-Quality Estimation in Smart Grid Environments," International Journal of Distributed Sensor Networks, , vol. 8(2), pages 214068-2140, February.
  • Handle: RePEc:sae:intdis:v:8:y:2012:i:2:p:214068
    DOI: 10.1155/2012/214068
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1155/2012/214068
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2012/214068?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:sae:intdis:v:8:y:2012:i:2:p:214068. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: SAGE Publications (email available below). General contact details of provider: .

    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.