Malvaldi, A. and Dowell, J. and Weiss, S. and Infield, D. and Hill, D. (2014) Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts. In: 10th EAWE PhD Seminar on Wind Energy in Europe, 2014-10-28 - 2014-10-31, l'Ecole Polytechnique de l'Université d'Orléans.
Malvaldi_etal_EAWE_2016_Wind_prediction_enhancement.pdf - Final Published Version
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This paper explores how the accuracy of short-term prediction of wind speed and direction can be enhanced by considering additional spatial measurements. To achieve this, two different data sets have been used: (i) wind speed and direction measurements taken over 23 Met Office weather stations distributed across the UK, and (ii) outputs from the Consortium for Small-scale Modelling (COSMO) numerical weather model on a grid of points covering the UK and the surrounding sea. A multivariate complex valued adaptive prediction filter is applied to these data. The study provides an assessment of how well the proposed model can predict the data one hour ahead and what improvements can be accomplished by using additional data from the COSMO model.
|Item type:||Conference or Workshop Item (Paper)|
|Keywords:||wind energy, wind forecasting, multichannel adaptive filter, Electrical engineering. Electronics Nuclear engineering, Renewable Energy, Sustainability and the Environment, Energy Engineering and Power Technology, Electrical and Electronic Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
|Depositing user:||Pure Administrator|
|Date Deposited:||16 Dec 2016 09:38|
|Last modified:||18 Apr 2017 19:45|