• DocumentCode
    2236074
  • Title

    PV fed MLI with ANN based MPPT

  • Author

    Nambiar, Nirupama ; Palackal, RoseMary S. ; Greeshma K.V ; Chitra A

  • Author_Institution
    School Of Electrical Engineering (SELECT), VIT University, Vellore-632014, India
  • fYear
    2015
  • fDate
    22-23 April 2015
  • Abstract
    There is an urgent need to hasten the development of advanced energy technologies to address the global changes of sustainable development, climate change and clean energy. Renewable power generation can help the world nations meet these challenges and thus re-strategize the existing system. Solar photovoltaic power is a commercially viable and reliable technology with enormous potential in the distant future. The panel, a power source having non-linear internal resistance, behaves differently with varying irradiation conditions as the photovoltaic current and irradiation are directly proportional. The paper presents a PV fed five level Multi Level Inverter ( MLI) wherein the Maximum Power Point Tracking (MPPT) is done using an Artificial Neural Network (ANN). PV panel modeling, ANN based MPPT algorithm, DC-DC Buck Boost Converter and the Five level MLI are simulated in MATLAB/SIMULINK.
  • Keywords
    Artificial neural networks; Reliability; Silicon; Software packages; Switches; ANN (Artificial Neural Network); DC-DC Buck Boost converter; Five Level MLI; MPPT (Maximum Power Point Tracking); PV (Photovoltaic);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computation of Power, Energy Information and Commuincation (ICCPEIC), 2015 International Conference on
  • Conference_Location
    Melmaruvathur, Chennai, India
  • Print_ISBN
    978-1-4673-6524-6
  • Type

    conf

  • DOI
    10.1109/ICCPEIC.2015.7259478
  • Filename
    7259478