Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing

Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Inte...

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Main Authors: Kamisan, Nur A., Lee, Muhammad H., Hassan, Siti F., Norrulashikin, Siti M., Nor, Maria E., A. Rahman, Nur H.
Format: Article
Language:English
Published: International Information and Engineering Technology Association 2021
Subjects:
Online Access:http://eprints.uthm.edu.my/2549/
http://eprints.uthm.edu.my/2549/1/J12375_c5a60f4885efb6141f464f4c666a993d.pdf
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author Kamisan, Nur A.
Lee, Muhammad H.
Hassan, Siti F.
Norrulashikin, Siti M.
Nor, Maria E.
A. Rahman, Nur H.
author_facet Kamisan, Nur A.
Lee, Muhammad H.
Hassan, Siti F.
Norrulashikin, Siti M.
Nor, Maria E.
A. Rahman, Nur H.
author_sort Kamisan, Nur A.
building UTHM Institutional Repository
collection Online Access
description Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES.
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institution Universiti Tun Hussein Onn Malaysia
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language English
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publisher International Information and Engineering Technology Association
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spelling uthm-25492021-10-20T04:03:34Z http://eprints.uthm.edu.my/2549/ Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing Kamisan, Nur A. Lee, Muhammad H. Hassan, Siti F. Norrulashikin, Siti M. Nor, Maria E. A. Rahman, Nur H. TJ266-267.5 Turbines. Turbomachines (General) Wind serves as natural resources as the solution to minimize global warming and has been commonly used to produce electricity. Because of their uncontrollable wind characteristics, wind speed forecasting is considered one of the best challenges in developing power generation. The Autoregressive Integrated Moving Average (ARIMA), Simple Exponential Smoothing (SES) and a hybrid model combination of ARIMA and SES will be used in this study to predict the wind speed. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) are used as measurement of efficiency. The hybrid model provides a positive outcome for predicting wind speed compare to the single model of ARIMA and SES. International Information and Engineering Technology Association 2021 Article PeerReviewed text en http://eprints.uthm.edu.my/2549/1/J12375_c5a60f4885efb6141f464f4c666a993d.pdf Kamisan, Nur A. and Lee, Muhammad H. and Hassan, Siti F. and Norrulashikin, Siti M. and Nor, Maria E. and A. Rahman, Nur H. (2021) Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing. Mathematical Modelling of Engineering Problems, 8 (2). pp. 207-212. (Submitted) https://doi.org/10.18280/mmep.080206
spellingShingle TJ266-267.5 Turbines. Turbomachines (General)
Kamisan, Nur A.
Lee, Muhammad H.
Hassan, Siti F.
Norrulashikin, Siti M.
Nor, Maria E.
A. Rahman, Nur H.
Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title_full Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title_fullStr Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title_full_unstemmed Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title_short Forecasting wind speed data by using a combination of ARIMA model with single exponential smoothing
title_sort forecasting wind speed data by using a combination of arima model with single exponential smoothing
topic TJ266-267.5 Turbines. Turbomachines (General)
url http://eprints.uthm.edu.my/2549/
http://eprints.uthm.edu.my/2549/
http://eprints.uthm.edu.my/2549/1/J12375_c5a60f4885efb6141f464f4c666a993d.pdf