• DocumentCode
    645794
  • Title

    Statistics of building-specific load forecasting models

  • Author

    Berardino, J. ; Nwankpa, Chika

  • Author_Institution
    Electr. & Comput. Eng. Dept., Drexel Univ., Philadelphia, PA, USA
  • fYear
    2013
  • fDate
    22-24 Sept. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper reviews a method of load forecasting specifically for predicting a building´s electrical load for demand resource planning. The authors introduced a general problem formulation for building-specific load forecasting in previous works. This paper will enhance this idea with extensive forecaster performance and results based on studies done using historical building demand and thermal data collected for the main library building at Drexel University. These results demonstrate the improvement obtained by including building-specific parameters in the load forecast. Additionally, the variability of this method and how it can inform demand-side decision making is explored, particularly in allowing the manager of a controllable load to assess his or her risk and capabilities when participating in the energy market.
  • Keywords
    building management systems; decision making; load forecasting; power markets; power system planning; Drexel University; building demand; building-specific load forecasting; demand resource planning; demand-side decision making; electrical load; energy market; forecaster performance; statistics; Buildings; Forecasting; Load forecasting; Load modeling; Planning; Predictive models; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2013
  • Conference_Location
    Manhattan, KS
  • Type

    conf

  • DOI
    10.1109/NAPS.2013.6666947
  • Filename
    6666947