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.
|Number of pages||4|
|Publication status||Published - Oct 2014|
|Event||10th EAWE PhD Seminar on Wind Energy in Europe - l'Ecole Polytechnique de l'Université d'Orléans, Orléans, France|
Duration: 28 Oct 2014 → 31 Oct 2014
|Conference||10th EAWE PhD Seminar on Wind Energy in Europe|
|Period||28/10/14 → 31/10/14|
- wind energy
- wind forecasting
- multichannel adaptive filter
Malvaldi, A., Dowell, J., Weiss, S., Infield, D., & Hill, D. (2014). Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts. 1-4. Paper presented at 10th EAWE PhD Seminar on Wind Energy in Europe, Orléans, France.