• DocumentCode
    729511
  • Title

    Research on mid-long term load forecasting based on combination forecasting mode

  • Author

    Yao Min ; Zhao Min ; Xiao Hui ; Wang Dongyue

  • Author_Institution
    Coll. of Autom. Eng., NUAA, Nanjing, China
  • fYear
    2015
  • fDate
    1-3 June 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Mid-long term load forecasting for power system is one of the basic works of power planning for cities. Each power forecasting model has its own advantages and disadvantages and has its own application range. In this paper a combination load forecasting model with variable weight is built. In this way it can maximize the advantage of each single model in different ranges. Furthermore, the Fourier technique of the residual correction method is used to decrease the absolute error of forecasting error of combination model. Based on the sample data in a city, the experiments are performed. The results show that the forecasting precision of combination model is higher than any single model which is more than 94%. After residual correction, the forecasting precision is further improved to 95%.
  • Keywords
    Fourier series; grey systems; load forecasting; power system planning; regression analysis; Fourier technique; combination load forecasting model; grey model; linear regression; mid-long term load forecasting; power planning; power system; residual correction method; variable weight; Adaptation models; Forecasting; Linear regression; Load forecasting; Load modeling; Mathematical model; Predictive models; combination forecasting model; grey model; linear regression; load forecasting; neutral network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015 16th IEEE/ACIS International Conference on
  • Conference_Location
    Takamatsu
  • Type

    conf

  • DOI
    10.1109/SNPD.2015.7176268
  • Filename
    7176268