DocumentCode :
792548
Title :
Probabilistic forecasts of the magnitude and timing of peak electricity demand
Author :
McSharry, Patrick E. ; Bouwman, Sonja ; Bloemhof, Gabriël
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, UK
Volume :
20
Issue :
2
fYear :
2005
fDate :
5/1/2005 12:00:00 AM
Firstpage :
1166
Lastpage :
1172
Abstract :
Adequate capacity planning requires accurate forecasts of the future magnitude and timing of peak electricity demand. Electricity demand is affected by the day of the week, seasonal variations, holiday periods, feast days, and the weather. A model that provides probabilistic forecasts of both magnitude and timing for lead times of one year is presented. This model is capable of capturing the main sources of variation in demand and uses simulated weather time series, including temperature, wind speed, and luminosity, for producing probabilistic forecasts of future peak demand. Having access to such probabilistic forecasts provides a means of assessing the uncertainty in the forecasts and can lead to improved decision making and better risk management.
Keywords :
decision making; load forecasting; load management; probability; risk management; time series; capacity planning; decision making; magnitude forecasting; peak electricity demand; risk management; timing forecasting; weather time series; Capacity planning; Decision making; Demand forecasting; Predictive models; Temperature distribution; Timing; Uncertainty; Weather forecasting; Wind forecasting; Wind speed; Load forecasting; load management; management decision making; power demand; power generation peaking capacity; power system planning; simulation; temperature; time series;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2005.846071
Filename :
1425617
Link To Document :
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