• DocumentCode
    3647668
  • Title

    ANN-based maximum power point tracking of photovoltaic system using fuzzy controller

  • Author

    Ahmet Afşin Kulaksiz;Ömer Aydoğdu

  • Author_Institution
    Department of Electrical and Electronics Engineering, Selcuk University, Konya, Turkey
  • fYear
    2012
  • fDate
    7/1/2012 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional perturbation & observation based method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.
  • Keywords
    "Fuzzy logic","Photovoltaic systems","Niobium","Artificial neural networks","Photovoltaic cells","Voltage control","Batteries"
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on
  • Print_ISBN
    978-1-4673-1446-6
  • Type

    conf

  • DOI
    10.1109/INISTA.2012.6246936
  • Filename
    6246936