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
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