• DocumentCode
    3153845
  • Title

    Next day load curve forecasting using hybrid correction method

  • Author

    Senjyu, Tomonobu ; Takara, Hitoshi ; Asato, Kentarou ; Uezato, Katsumi ; Funabashi, Toshihisa

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa, Japan
  • Volume
    3
  • fYear
    2002
  • fDate
    6-10 Oct. 2002
  • Firstpage
    1701
  • Abstract
    In this paper, the authors propose a next day load curve forecasting using a hybrid correction method which is a combination of neural network and fuzzy logic. In this proposed prediction method, the forecasted load power is obtained by adding a correction that is obtained from the neural network and a fuzzy logic to the selected similar day´s data. The neural network has the advantage of dealing with the nonlinear part of forecasted load curves. The fuzzy rules are constructed based on expert knowledge. Therefore, combining these methods, the proposed method is useful in situations where accurate forecasting models are difficult to obtain. The suitability of the proposed approach is illustrated through an application to actual load data of the Okinawa Electric Power Company in Japan.
  • Keywords
    expert systems; fuzzy logic; load forecasting; neural nets; power system analysis computing; power system planning; Japan; expert knowledge; fuzzy logic; hybrid correction method; neural network; next day load curve forecasting; Demand forecasting; Fuzzy logic; Input variables; Load forecasting; Neural networks; Power system modeling; Prediction methods; Predictive models; Temperature; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES
  • Print_ISBN
    0-7803-7525-4
  • Type

    conf

  • DOI
    10.1109/TDC.2002.1177710
  • Filename
    1177710