• DocumentCode
    2564068
  • Title

    Short-range load forecasting for distribution system planning-an improved method for extrapolating feeder load growth

  • Author

    Willis, H.L. ; Tram, H.N. ; Rackliffe, G.B.

  • Author_Institution
    ABB Advanced Systems Technology, Pittsburgh, PA, USA
  • fYear
    1991
  • fDate
    22-27 Sep 1991
  • Firstpage
    294
  • Lastpage
    300
  • Abstract
    A new method of extrapolating feeder peak load histories to produce estimates of future feeder loads is described. The method, an improvement on past multiple regression curve fit methods, uses an assumed geometry based on substation locations and a classification by recent growth rates to group feeders into six classes, each extrapolated in a slightly different manner. The new method is simple enough to be applied in situations where computing resources are limited. A series of tests shows that the new method outperforms other distribution load extrapolation methods, and that for short range (less than five years ahead) forecasts, it matches the accuracy of simulation forecasting methods, which require considerably more data and computer resources
  • Keywords
    distribution networks; extrapolation; load forecasting; power system planning; distribution system planning; feeder load growth extrapolation; multiple regression curve fit methods; short-range load forecasting; Computational modeling; Computer simulation; Distributed computing; Extrapolation; Geometry; History; Load forecasting; Predictive models; Substations; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Transmission and Distribution Conference, 1991., Proceedings of the 1991 IEEE Power Engineering Society
  • Conference_Location
    Dallas, TX
  • Print_ISBN
    0-7803-0219-2
  • Type

    conf

  • DOI
    10.1109/TDC.1991.169522
  • Filename
    169522