• DocumentCode
    3088463
  • Title

    Developing a matlab tool while exploiting neural networks for combined prediction of hour´s ahead system load along with irradiation, to estimate the system load covered by PV integrated systems

  • Author

    Kolentini, E. ; Sideratos, G. ; Rikos, V. ; Hatziargyriou, N.

  • Author_Institution
    NTUA, Athens, Greece
  • fYear
    2009
  • fDate
    9-11 June 2009
  • Firstpage
    182
  • Lastpage
    186
  • Abstract
    Renewable energy systems (RES), being a controversial issue regarding their integration into the electric power systems, create the necessity for research. In order to take part in the electricity market, a critical point is the prediction of the system load as well as the prediction of the RES production. Within this scope, a matlab tool was developed to facilitate both the prediction of the system load as well as the PV production in several penetration levels.
  • Keywords
    neural nets; photovoltaic power systems; power generation economics; power markets; power system analysis computing; PV integrated systems; electricity market; matlab tool; neural networks; renewable energy systems; system load estimation; Artificial neural networks; Biological neural networks; Chromium; Economic forecasting; Electricity supply industry; Neural networks; Neurons; Production systems; Temperature; Voltage; grid integration; matlab GUI tool; neural networks (NN); photovoltaic systems (PV); renewable energy systems (RES); system load;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Clean Electrical Power, 2009 International Conference on
  • Conference_Location
    Capri
  • Print_ISBN
    978-1-4244-2543-3
  • Electronic_ISBN
    978-1-4244-2544-0
  • Type

    conf

  • DOI
    10.1109/ICCEP.2009.5212061
  • Filename
    5212061