NDLI: Long term wind speed prediction with polynomial autoregressive model

Content Provider	IEEE Xplore Digital Library
Author	Karakus, O. Kuruoglu, E.E. Altinkaya, M.A.
Copyright Year	2015
Description	Author affiliation: ISTI, Pisa, Italy (Kuruoglu, E.E.) \|\| Elektrik ve Elektron. Muhendisligi Bolumu, Izmir Yuksek Teknol. Enstitusu, Izmir, Turkey (Karakus, O.; Altinkaya, M.A.)
Abstract	Wind energy is one of the preferred energy generation methods because wind is an important renewable energy source. Prediction of wind speed in a time period, is important due to the one-to-one relationship between wind speed and wind power. Due to the nonlinear character of the wind speed data, nonlinear methods are known to produce better results compared to linear time series methods like Autoregressive (AR), Autoregressive Moving Average (ARMA) in predicting in a period longer than 12 hours. A method is proposed to apply a 48-hour ahead wind speed prediction by using the past wind speed measurements of the Çeşme Peninsula. We proposed to model wind speed data with a Polynomial AR (PAR) model. Coefficients of the models are estimated via linear Least Squares (LS) method and up to 48 hours ahead wind speed prediction is calculated for different models. In conclusion, a better performance is observed for higher than 12-hour ahead wind speed predictions of wind speed data which is modelled with PAR model, than AR and ARMA models.
Starting Page	645
Ending Page	648
File Size	303564
Page Count	4
File Format	PDF
ISBN	9781467373869
DOI	10.1109/SIU.2015.7129907
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-16
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	PAR AR Wind speed long term wind speed prediction Time series analysis nonlinear time series Predictive models Wind power generation Data models ARMA Forecasting Autoregressive processes
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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