Title :
One day ahead prediction of wind speed using annual trends
Author :
El-Fouly, T.H.M. ; El-Saadany, E.F. ; Salama, M.M.A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont.
Abstract :
The growing revolution in wind energy encourages for more accurate models for wind speed forecasting and wind power generation prediction. This paper presents a new technique for wind speed forecasting based on using a time series model relating the predicted interval to its corresponding one and two year old data. A set of data that extends to 72 hours is used in investigating the accuracy of the model for predicting wind speeds up 24 hours ahead. Obtained results, form the proposed model, are compared with their corresponding values generated when using the persistence model. The presented results validate the effectiveness of the new prediction models for wind speed
Keywords :
load forecasting; time series; wind power plants; annual trends; time series model; wind energy; wind power generation prediction; wind speed forecasting; Power generation; Power system interconnection; Power system modeling; Power system planning; Predictive models; Production systems; Wind energy; Wind farms; Wind forecasting; Wind speed; Least square method; prediction; time series; wind;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1709373
