• DocumentCode
    2060990
  • Title

    Short-term load forecasting: Revising how good we actually are

  • Author

    Lopez, M. ; Valero, S. ; Senabre, C. ; Gabaldon, A.

  • Author_Institution
    Univ. Miguel Hernandez de Elche, Elche, Spain
  • fYear
    2012
  • fDate
    22-26 July 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper proposes the use of an indicator of the predictability of the load series along with an accuracy value such as Mean Average Percentage Error as standard measures of load forecasting performance. Over the last 10 years, there has been a significant increase in load forecasting models proposed in engineering journals. Most of these models provide a description of the inner design of the model, the results from applying this model to a specific data base and the conclusions drawn from this application. However, a single accuracy value may not be sufficient to describe the performance of the model when applied to other data bases. The aim of this paper is to provide researchers with a tool that is able to assess the predictability of a load series and, therefore, contextualize the forecasting accuracy reported. Thirteen different data bases were used to determine its validity.
  • Keywords
    load forecasting; databases; engineering journals; load series predictability; mean average percentage error; short-term load forecasting; Accuracy; Data models; Filtering theory; Forecasting; Load forecasting; Load modeling; Predictive models; Forecasting; frequency domain analysis; performance evaluation; power demand;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting, 2012 IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1944-9925
  • Print_ISBN
    978-1-4673-2727-5
  • Electronic_ISBN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESGM.2012.6345392
  • Filename
    6345392