A time series ensemble method to predict wind power

Tasnim, Sumaira, Rahman, Ashfaqur, Shafiullah, G. M., Maung Than Oo, Amanullah and Stojcevski, Aleksandar 2014, A time series ensemble method to predict wind power, in CIASG 2014 : Proceesings of the IEEE Computational Intelligence Applications in Smart Grid 2014 Symposium, IEEE, Piscataway, NJ, pp. 1-5, doi: 10.1109/CIASG.2014.7011544.

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Title A time series ensemble method to predict wind power
Author(s) Tasnim, Sumaira
Rahman, Ashfaqur
Shafiullah, G. M.
Maung Than Oo, Amanullah
Stojcevski, Aleksandar
Conference name IEEE Computational Intelligence Applications in Smart Grid. Symposium (2014 : Orlando, Fla.)
Conference location Orlando, Fla.
Conference dates 9-12 Dec. 2014
Title of proceedings CIASG 2014 : Proceesings of the IEEE Computational Intelligence Applications in Smart Grid 2014 Symposium
Editor(s) [Unknown]
Publication date 2014
Conference series IEEE Computational Intelligence Applications in Smart Grid Symposium
Start page 1
End page 5
Total pages 5
Publisher IEEE
Place of publication Piscataway, NJ
Keyword(s) wind power prediction
time series ensemble
Summary Wind power prediction refers to an approximation of the probable production of wind turbines in the near future. We present a time series ensemble framework to predict wind power. Time series wind data is transformed using a number of complementary methods. Wind power is predicted on each transformed feature space. Predictions are aggregated using a neural network at a second stage. The proposed framework is validated on wind data obtained from ten different locations across Australia. Experimental results demonstrate that the ensemble predictor performs better than the base predictors.
ISSN 2326-7682
2326-7690
Language eng
DOI 10.1109/CIASG.2014.7011544
Field of Research 090608 Renewable Power and Energy Systems Engineering (excl Solar Cells)
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082969

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