• DocumentCode
    3496057
  • Title

    Determination of power losses in solar panels using artificial neural network

  • Author

    Jazayeri, Kian ; Uysal, Sener ; Jazayeri, Moein

  • Author_Institution
    Electr. & Electron. Eng. Dept., Eastern Mediterranean Univ., Famagusta, Cyprus
  • fYear
    2013
  • fDate
    9-12 Sept. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The main purpose of this paper is on developing an intelligent system which provides real time monitoring and fault detection for solar panels. Utilizing artificial neural network technology, the solar panel fault detection system is capable of perceiving sun´s position in the sky and estimating the corresponding output power of a solar panel based on the algorithms derived by the artificial neural network which has been trained on solar data at several time intervals. The system is capable of operating in any geographical location providing 24hour monitoring and fault detection as well as future power estimations for solar panels.
  • Keywords
    fault diagnosis; losses; neural nets; power engineering computing; solar cells; artificial neural network; intelligent system; power estimations; power losses determination; solar panel fault detection system; Artificial neural networks; Azimuth; Fault detection; Power generation; Power measurement; Training; Training data; artificial neural networks; fault detection; photovoltaic cells; photovoltaic systems; solar energy; solar power generation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AFRICON, 2013
  • Conference_Location
    Pointe-Aux-Piments
  • ISSN
    2153-0025
  • Print_ISBN
    978-1-4673-5940-5
  • Type

    conf

  • DOI
    10.1109/AFRCON.2013.6757775
  • Filename
    6757775