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
Link To Document :
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