• DocumentCode
    2897121
  • Title

    Application of maximum entropy principle to load forecasting collaboration

  • Author

    Xiao, Jun ; Zhang, Xuan ; Xu, Binshan

  • Author_Institution
    Key Lab. of Smart Grid of Minist. of Educ., Tianjin Univ., Tianjin, China
  • fYear
    2011
  • fDate
    6-9 July 2011
  • Firstpage
    1607
  • Lastpage
    1612
  • Abstract
    This paper proposes a collaborative load forecasting method based on maximum entropy principle. Taking the expectation and second order central moment of forecasting results into account and using the maximum entropy principle, the load forecasting method receives the probability distribution function of the forecasted values and obtains the final high, middle and low forecasting scheme based on the probability theory. Based on this method, three applications in load forecasting are introduced in this paper. Case studies have shown applications of this method can take the affection of the conflicts among different forecasting path into account in forecasting, resulting in higher precision of load forecasting.
  • Keywords
    entropy; load forecasting; probability; load forecasting collaboration; maximum entropy principle; probability distribution function; second order central moment; Entropy; Equations; Forecasting; Load forecasting; Load modeling; Mathematical model; Predictive models; Integrated model; Load Forecasting; Maximum Entropy Principle; Multi-route;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
  • Conference_Location
    Weihai, Shandong
  • Print_ISBN
    978-1-4577-0364-5
  • Type

    conf

  • DOI
    10.1109/DRPT.2011.5994154
  • Filename
    5994154