DocumentCode
2315689
Title
Short-term wind speed forecasting combined time series method and arch model
Author
Meng-Di Wang ; Qi-Rong Qiu ; Bing-Wei Cui
Author_Institution
Fac. of Mech. & Electron. Inf., China Univ. of Geosci., Wuhan, China
Volume
3
fYear
2012
fDate
15-17 July 2012
Firstpage
924
Lastpage
927
Abstract
In order to improve the accuracy of the wind speed forecasting in the wind farm, this paper presents an ARIMA-ARCH model, which considers the heteroscedastic effect between the fluctuation of wind speed and the characteristics of the change of wind speed, to forecast the wind speed. First of all, the ARIMA model for the wind speed time series is built by SPSS. After that, the high lag order ARCH effect is found in the residual of the ARIMA model by Lagrange multiplier (LM) test. At last, the GARCH model is built for simulating the residual series and thus to construct the ARIMA-ARCH model. Numerical experiments demonstrate the superiority of the proposed method when comparing with the traditional ARIMA model.
Keywords
forecasting theory; time series; wind power; ARIMA-ARCH model; Lagrange multiplier; short-term wind speed forecasting; time series method; wind farm; Abstracts; Atmospheric measurements; Pollution measurement; Predictive models; Time series analysis; Wind forecasting; Wind speed; ARCH model; ARIMA model; Short-term wind speed forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
Conference_Location
Xian
ISSN
2160-133X
Print_ISBN
978-1-4673-1484-8
Type
conf
DOI
10.1109/ICMLC.2012.6359477
Filename
6359477
Link To Document