Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts

Research output: Contribution to conferencePaper

Abstract

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.

Conference

Conference10th EAWE PhD Seminar on Wind Energy in Europe
CountryFrance
CityOrléans
Period28/10/1431/10/14
Internet address

Keywords

  • wind energy
  • wind forecasting
  • multichannel adaptive filter

Cite this

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.
Malvaldi, A. ; Dowell, J. ; Weiss, S. ; Infield, D. ; Hill, D. / Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts. Paper presented at 10th EAWE PhD Seminar on Wind Energy in Europe, Orléans, France.4 p.
@conference{a0f296ada9194d5b90a9e47ecf99e58f,
title = "Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts",
abstract = "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.",
keywords = "wind energy, wind forecasting, multichannel adaptive filter",
author = "A. Malvaldi and J. Dowell and S. Weiss and D. Infield and D. Hill",
year = "2014",
month = "10",
language = "English",
pages = "1--4",
note = "10th EAWE PhD Seminar on Wind Energy in Europe ; Conference date: 28-10-2014 Through 31-10-2014",
url = "http://eawephdseminar.sciencesconf.org/",

}

Malvaldi, A, Dowell, J, Weiss, S, Infield, D & Hill, D 2014, 'Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts' Paper presented at 10th EAWE PhD Seminar on Wind Energy in Europe, Orléans, France, 28/10/14 - 31/10/14, pp. 1-4.

Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts. / Malvaldi, A.; Dowell, J.; Weiss, S.; Infield, D.; Hill, D.

2014. 1-4 Paper presented at 10th EAWE PhD Seminar on Wind Energy in Europe, Orléans, France.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts

AU - Malvaldi, A.

AU - Dowell, J.

AU - Weiss, S.

AU - Infield, D.

AU - Hill, D.

PY - 2014/10

Y1 - 2014/10

N2 - 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.

AB - 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.

KW - wind energy

KW - wind forecasting

KW - multichannel adaptive filter

UR - https://eawephdseminar.sciencesconf.org/

M3 - Paper

SP - 1

EP - 4

ER -

Malvaldi A, Dowell J, Weiss S, Infield D, Hill D. Wind prediction enhancement by supplementing measurements with numerical weather prediction now-casts. 2014. Paper presented at 10th EAWE PhD Seminar on Wind Energy in Europe, Orléans, France.