An intercomparison of mesoscale models at simple sites for wind energy applications

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Abstract

Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated sing a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft ( < 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.
Original languageEnglish
JournalWind Energy Science
Volume2
Issue number1
Pages (from-to)211-228
ISSN2366-7443
DOIs
Publication statusPublished - 2017

Cite this

@article{c8992d404fb44b4b8b13dfb16127655d,
title = "An intercomparison of mesoscale models at simple sites for wind energy applications",
abstract = "Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated sing a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft ( < 4 {\%}) and larger biases closer to the surface over land (> 7 {\%}). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.",
author = "Olsen, {Bjarke Tobias} and Hahmann, {Andrea N.} and Sempreviva, {Anna Maria} and Jake Badger and J{\o}rgensen, {Hans E.}",
year = "2017",
doi = "10.5194/wes-2-211-2017",
language = "English",
volume = "2",
pages = "211--228",
journal = "Wind Energy Science",
issn = "2366-7443",
publisher = "Copernicus GmbH",
number = "1",

}

TY - JOUR

T1 - An intercomparison of mesoscale models at simple sites for wind energy applications

AU - Olsen, Bjarke Tobias

AU - Hahmann, Andrea N.

AU - Sempreviva, Anna Maria

AU - Badger, Jake

AU - Jørgensen, Hans E.

PY - 2017

Y1 - 2017

N2 - Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated sing a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft ( < 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

AB - Understanding uncertainties in wind resource assessment associated with the use of the output from numerical weather prediction (NWP) models is important for wind energy applications. A better understanding of the sources of error reduces risk and lowers costs. Here, an intercomparison of the output from 25 NWP models is presented for three sites in northern Europe characterized by simple terrain. The models are evaluated sing a number of statistical properties relevant to wind energy and verified with observations. On average the models have small wind speed biases offshore and aloft ( < 4 %) and larger biases closer to the surface over land (> 7 %). A similar pattern is detected for the inter-model spread. Strongly stable and strongly unstable atmospheric stability conditions are associated with larger wind speed errors. Strong indications are found that using a grid spacing larger than 3 km decreases the accuracy of the models, but we found no evidence that using a grid spacing smaller than 3 km is necessary for these simple sites. Applying the models to a simple wind energy offshore wind farm highlights the importance of capturing the correct distributions of wind speed and direction.

U2 - 10.5194/wes-2-211-2017

DO - 10.5194/wes-2-211-2017

M3 - Journal article

VL - 2

SP - 211

EP - 228

JO - Wind Energy Science

JF - Wind Energy Science

SN - 2366-7443

IS - 1

ER -