• DocumentCode
    555002
  • Title

    Forecasting the next day load profile using load profiling information and meteorological variables

  • Author

    Sousa, J.C. ; Jorge, Humberto M. ; Neves, Lucio P.

  • Author_Institution
    Dept. of Electr. Eng., Polytech. Inst. of Leiria, Leiria, Portugal
  • fYear
    2011
  • fDate
    7-9 July 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The article proposes a new approach to support the process of forecasting the hourly electric load values for the following day. The adopted methodology based on neural networks is only supported by detailed information related with consumers´ typical behavior and climatic information. The case study was tested in two real distribution substation outputs, demonstrating its effectiveness and practical applicability.
  • Keywords
    load forecasting; neural nets; power distribution; power engineering computing; substations; climatic information; consumer behavior; distribution substation outputs; hourly-electric load value forecasting; load profiling information; meteorological variables; neural networks; next-day load profile forecasting; Forecasting; Load forecasting; Load modeling; Low voltage; Neurons; Predictive models; Training; Load Forecasting; Load Profiling and Neural Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energetics (IYCE), Proceedings of the 2011 3rd International Youth Conference on
  • Conference_Location
    Leiria
  • Print_ISBN
    978-1-4577-1494-8
  • Type

    conf

  • Filename
    6028118