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Estimating wind conditions in forests using roughness lengths: A matter of data input

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Estimating wind conditions in forests using roughness lengths : A matter of data input. / Enevoldsen, Peter.

In: Wind Engineering, Vol. 44, No. 2, 2020, p. 142-151.

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@article{4d61fe325c234bc4a7b056c39e25c171,
title = "Estimating wind conditions in forests using roughness lengths: A matter of data input",
abstract = "This study makes use of data from six meteorological masts to examine five different data sources of roughness lengths. The data sources can be applied in most regions of the world. The consequences of applying wrong roughness lengths can impact the business case of a wind project. The experiment confirmed the preliminary expectation, as the optimized roughness approach provided better results than the remaining four approaches and, furthermore, was able to treat different tree heights. The initial test was conducted using a spatial resolution of 20 m for optimized roughness approach, while the other data sources used a greater resolution. As a response, optimized roughness approach was reused for the other spatial resolutions showing better results than the remaining approaches. One other remarkable finding associated with this study was the relationship between spatial resolution and errors in the estimation, as a resolution above 100 m provided random results with no relationship whatsoever.",
keywords = "Wind power, data quality, forest, modeling, roughness length",
author = "Peter Enevoldsen",
year = "2020",
doi = "10.1177/0309524X19849849",
language = "English",
volume = "44",
pages = "142--151",
journal = "Wind Engineering",
issn = "0309-524X",
publisher = "SAGE Publications Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Estimating wind conditions in forests using roughness lengths

T2 - A matter of data input

AU - Enevoldsen, Peter

PY - 2020

Y1 - 2020

N2 - This study makes use of data from six meteorological masts to examine five different data sources of roughness lengths. The data sources can be applied in most regions of the world. The consequences of applying wrong roughness lengths can impact the business case of a wind project. The experiment confirmed the preliminary expectation, as the optimized roughness approach provided better results than the remaining four approaches and, furthermore, was able to treat different tree heights. The initial test was conducted using a spatial resolution of 20 m for optimized roughness approach, while the other data sources used a greater resolution. As a response, optimized roughness approach was reused for the other spatial resolutions showing better results than the remaining approaches. One other remarkable finding associated with this study was the relationship between spatial resolution and errors in the estimation, as a resolution above 100 m provided random results with no relationship whatsoever.

AB - This study makes use of data from six meteorological masts to examine five different data sources of roughness lengths. The data sources can be applied in most regions of the world. The consequences of applying wrong roughness lengths can impact the business case of a wind project. The experiment confirmed the preliminary expectation, as the optimized roughness approach provided better results than the remaining four approaches and, furthermore, was able to treat different tree heights. The initial test was conducted using a spatial resolution of 20 m for optimized roughness approach, while the other data sources used a greater resolution. As a response, optimized roughness approach was reused for the other spatial resolutions showing better results than the remaining approaches. One other remarkable finding associated with this study was the relationship between spatial resolution and errors in the estimation, as a resolution above 100 m provided random results with no relationship whatsoever.

KW - Wind power

KW - data quality

KW - forest

KW - modeling

KW - roughness length

UR - http://www.scopus.com/inward/record.url?scp=85082506542&partnerID=8YFLogxK

U2 - 10.1177/0309524X19849849

DO - 10.1177/0309524X19849849

M3 - Journal article

VL - 44

SP - 142

EP - 151

JO - Wind Engineering

JF - Wind Engineering

SN - 0309-524X

IS - 2

ER -