Wind Prediction Enhancement by Exploiting Data Non-stationarity

Malvaldi, A., Dowell, J. , Weiss, S. and Infield, D. (2015) Wind Prediction Enhancement by Exploiting Data Non-stationarity. In: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP), London, UK, 01-02 Dec 2015, ISBN 9781785611360 (doi: 10.1049/cp.2015.1795)

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The short term forecasting of wind speed and direction has previously been improved by adopting a cyclo-stationary multichannel linear prediction approach which incorporated seasonal cycles into the estimation of statistics. This paper expands previous analysis by also incorporating diurnal variation and time-dependent window lengths. Based on a large data set from the UK's Met Ofjice, we demonstrate the impact of this proposed approach.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Browell, Dr Jethro
Authors: Malvaldi, A., Dowell, J., Weiss, S., and Infield, D.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Published Online:17 November 2016

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