• DocumentCode
    3624665
  • Title

    Preliminary comparison of different neural-fuzzy mappers for load curve short term prediction

  • Author

    Dzenana Malkocevic;Tatjana Konjic;Vladimiro Miranda

  • Author_Institution
    Elektroprivreda BiH, TEMPUS CEFES post-graduation program run, Universities of Tuzla (BiH), Novi Sad (Serbia) and Skopje (FYR of Macedonia). m.dzenana@gmail.com
  • fYear
    2006
  • Firstpage
    213
  • Lastpage
    217
  • Abstract
    This paper is written with the didactic purpose of exploring and indicating possibilities to power companies in the Balkan region for the application of adaptive neuro-fuzzy inference system (ANFIS) models in load prediction with real load data set. ANFIS models were trained and tested using 15-minute load data collected in Portugal by the electric power company EDP during a 42 day period. Simulation results gave promising results especially considering small size of used data set. Although the objective of the paper is to demonstrate possibilities for practical implementation, further research and improvement including the contributions of similar approaches in the world must be done
  • Keywords
    "Power system modeling","Load forecasting","Power system dynamics","Adaptive systems","Predictive models","Power system control","Power system planning","Neural networks","Fuzzy systems","Power systems"
  • Publisher
    ieee
  • Conference_Titel
    Neural Network Applications in Electrical Engineering, 2006. NEUREL 2006. 8th Seminar on
  • Print_ISBN
    1-4244-0432-0
  • Type

    conf

  • DOI
    10.1109/NEUREL.2006.341216
  • Filename
    4147204