TY - JOUR
T1 - Improved Grey predictor rolling models for wind power prediction
AU - El-Fouly, T. H.M.
AU - El-Saadany, E. F.
AU - Salama, M. M.A.
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34548790280&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd:20060564
DO - 10.1049/iet-gtd:20060564
M3 - Article
AN - SCOPUS:34548790280
SN - 1751-8687
VL - 1
SP - 928
EP - 937
JO - IET Generation, Transmission and Distribution
JF - IET Generation, Transmission and Distribution
IS - 6
ER -