• DocumentCode
    3095266
  • Title

    Long-term electric power load forecasting using fuzzy linear regression technique

  • Author

    Al-Hamadi, H.M.

  • Author_Institution
    Dept. of Inf. Syst., Kuwait Univ., Safat, Kuwait
  • Volume
    3
  • fYear
    2011
  • fDate
    8-9 Sept. 2011
  • Firstpage
    96
  • Lastpage
    99
  • Abstract
    This paper presents a new technique for long-term electric power load forecasting. The technique is based on fuzzy linear regression which uses long term annual growth factors to estimate fuzzy linear regression model parameters. In this technique a linear optimization problem is formulated, where the objective is to minimize the spread of fuzzy regression parameters. The annual growths for each of the long-term forecasting factors are calculated using cubic polynomials. The performance of the proposed technique is illustrated on real power network data.
  • Keywords
    fuzzy set theory; load forecasting; optimisation; polynomial approximation; regression analysis; cubic polynomials; fuzzy linear regression model parameters; linear optimization problem; long term annual growth factors; long-term electric power load forecasting; real power network data; Autoregressive processes; Forecasting; Linear regression; Load forecasting; Load modeling; Mathematical model; Linear Fuzzy regression; Long-term load forecasting; annual growth;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering and Automation Conference (PEAM), 2011 IEEE
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9691-4
  • Type

    conf

  • DOI
    10.1109/PEAM.2011.6135023
  • Filename
    6135023