• DocumentCode
    2640485
  • Title

    Forecasting Turkey´s short term hourly load with artificial neural networks

  • Author

    Bilgic, M. ; Girep, C.P. ; Aslanoglu, S.Y. ; Aydinalp-Koksal, M.

  • Author_Institution
    Clean & Renewable Energies Div., Hacettepe Univ., Ankara, Turkey
  • fYear
    2010
  • fDate
    19-22 April 2010
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Load forecasting is important necessity to provide economic, reliable, high grade energy. In this study, short term hourly load forecasting systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. ANN is the most commonly preferred approach for load forecasting. The mean average percent error (MAPE) of total hourly load forecast for Turkey is found as 1.81%.
  • Keywords
    Artificial neural networks; Calendars; Economic forecasting; Electronic mail; Fuzzy logic; Load forecasting; Power generation economics; Predictive models; Statistical analysis; Temperature; Short term load forecasting; artificial neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exposition, 2010 IEEE PES
  • Conference_Location
    New Orleans, LA, USA
  • Print_ISBN
    978-1-4244-6546-0
  • Type

    conf

  • DOI
    10.1109/TDC.2010.5484442
  • Filename
    5484442
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2640485