IDEAS home Printed from https://ideas.repec.org/a/epw/ejece0/v4y2020i6id19267.html

A Review of Conventional Fault Detection Techniques in Solar PV Systems and a Proposal of Long Range (LoRa) Wireless Sensor Network for Module Level Monitoring and Fault Diagnosis in Large Solar PV Farms

Author

Listed:
  • Aruoriwoghene Okere

    (Memorial University of Newfoundland, Canada)

  • M. Tariq Iqbal

    (Memorial University of Newfoundland, Canada)

Abstract

This paper reviews various faults that exist in large solar Photovoltaic (PV) systems. The faults are reviewed in their various classes based on the location and structure. Conventional solutions for fault detection and various research work in PV system monitoring and fault detection are reviewed. It is obvious that PV module level monitoring exhibit advantages over array or string monitoring. Therefore, the paper proposes the use of Long Range (LoRa) Wireless Sensor Networks (WSN) for PV module level monitoring and fault diagnosis. LoRa was proposed for this application due to the advantages it has over other wireless technologies which include long range of data transfer, low cost, low power consumption and multi sensor connection capabilities.

Suggested Citation

  • Aruoriwoghene Okere & M. Tariq Iqbal, 2020. "A Review of Conventional Fault Detection Techniques in Solar PV Systems and a Proposal of Long Range (LoRa) Wireless Sensor Network for Module Level Monitoring and Fault Diagnosis in Large Solar PV Farms," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 4(6), November.
  • Handle: RePEc:epw:ejece0:v:4:y:2020:i:6:id:19267
    DOI: 10.24018/ejece.2020.4.6.267
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejece/article/view/19267
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejece/article/download/19267/11133
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejece.2020.4.6.267?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

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:epw:ejece0:v:4:y:2020:i:6:id:19267. 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: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .

    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.