A time series ensemble method to predict wind power
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Tasnim, S., Rahman, A., Shafiullah, GM.
ORCID: 0000-0002-2211-184X, Oo, A.M.T. and Stojcevski, A.
(2014)
A time series ensemble method to predict wind power.
In: IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG) 2014, 9 - 12 Dec. 2014, Orlando, FL
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Abstract
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.
| Item Type: | Conference Paper |
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| URI: | http://researchrepository.murdoch.edu.au/id/eprint/31738 |
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