DocumentCode :
1188048
Title :
Improved Grey predictor rolling models for wind power prediction
Author :
El-Fouly, T.H.M. ; El-Saadany, E.F. ; Salama, M.M.A.
Author_Institution :
Univ. of Waterloo, Waterloo
Volume :
1
Issue :
6
fYear :
2007
Firstpage :
928
Lastpage :
937
Abstract :
A new technique for one step ahead average hourly wind speed forecasting and wind turbines´ output power prediction based on using the Grey predictor models is presented. The required mathematical formulation for developing the Grey predictor models is also presented. The obtained results from the proposed models are compared with the corresponding results obtained when using the persistent model. Utilising the traditional Grey model, GM(1,1) was first investigated and showed good improvement over the persistent model. However, the generated results demonstrate the presence of intervals with overshoots in the predicted values. To reduce such overshoots, a modified version for the Grey predictor model referred to as the adaptive alpha GM(1,1) model is investigated and two new models are proposed, hereafter, referred to as the improved Grey model and the averaged Grey model. The presented results demonstrate the effectiveness, the accuracy and the superiority of the proposed averaged Grey model for wind speed and wind power prediction.
Keywords :
load forecasting; mathematical analysis; wind turbines; Grey predictor rolling models; adaptive alpha model; wind power prediction; wind speed forecasting; wind turbines;
fLanguage :
English
Journal_Title :
Generation, Transmission & Distribution, IET
Publisher :
iet
ISSN :
1751-8687
Type :
jour
DOI :
10.1049/iet-gtd:20060564
Filename :
4312803
Link To Document :
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