• DocumentCode
    2455106
  • Title

    Determining Suitability of Locations for Installation of Solar Power Station Based on Probabilistic Inference

  • Author

    Colak, Ilhami ; Sagiroglu, Seref ; Demirtas, Mehmet ; Kahraman, Hamdi Tolga

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Gazi Univ., Ankara, Turkey
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    714
  • Lastpage
    719
  • Abstract
    This paper presents a novel system is to develop to determine the suitability of a location for installation of solar power stations. Necessary data including speed and direction of wind, solar radiation and rainfall are received from a meteorology station, and data acquired are then converted to the labels. Finally, the labels are evaluated in a Naïve Bayes algorithm to determine the suitability of the location for the installation and axial structure of a Solar Power Plant. This helps to determine complicated calculations by means of the support system developed.
  • Keywords
    Bayes methods; probability; solar power stations; axial structure; meteorology station; naive Bayes algorithm; probabilistic inference; rainfall; solar power plant; solar power stations; solar radiation; support system; Classification algorithms; Equations; Power generation; Solar energy; Solar radiation; Strontium; Wind speed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.169
  • Filename
    5708910