• DocumentCode
    1610031
  • Title

    Comparison of ANN and P&O MPPT methods for PV applications under changing solar irradiation

  • Author

    Khanaki, Razieh ; Radzi, M.A.M. ; Marhaban, M.H.

  • Author_Institution
    Dept. of Electr. & Electron. Eng. Fac. of Eng., Univ. Putra Malaysia, Serdang, Malaysia
  • fYear
    2013
  • Firstpage
    287
  • Lastpage
    292
  • Abstract
    This paper presents an artificial neural network (ANN) maximum power point tracking (MPPT) method which is fast and precise in finding and tracking the maximum power point (MPP) in photovoltaic (PV) applications, under rapidly changing of solar irradiation, and is stable under slowly changing of solar irradiation. ANN and P&O MPPT algorithms, and other components of the MPPT control system which are PV module and DC-DC boost converter, are simulated in MATLAB-Simulink, and their performances under rapidly and slowly changing of solar irradiation are compared as well. Simulation results show that ANN method has very fast and more precise response under fast changes of solar irradiation. In addition, this method performs with less power oscillation under constant or slow changes of solar irradiation.
  • Keywords
    maximum power point trackers; neural nets; photovoltaic power systems; power engineering computing; ANN; DC-DC boost converter; MATLAB-Simulink; MPPT control; P&O MPPT algorithms; PV applications; artificial neural network; maximum power point tracking; perturbation and observation methods; photovoltaic applications; power oscillation; solar irradiation; Artificial neural networks; Equations; Mathematical model; Maximum power point trackers; Oscillators; Radiation effects; Simulation; Maximum power point tracking (MPPT); artificial neural network (ANN); perturbation and observation (P&O); photovoltaic (PV);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Clean Energy and Technology (CEAT), 2013 IEEE Conference on
  • Conference_Location
    Lankgkawi
  • Print_ISBN
    978-1-4799-3237-5
  • Type

    conf

  • DOI
    10.1109/CEAT.2013.6775642
  • Filename
    6775642