Long-term wind resource and uncertainty estimation using wind records from Scotland as example

Research output: Contribution to journalArticle

Abstract

A systematic analysis of the sensitivity of a wind turbine’s output to changes in observed wind statistics between different sites in Scotland over available wind records of up to 43 years length was performed. The analysis was performed in the context of observed variability on time scales longer than a year. The findings are discussed in the context of the ability to predict the long-term wind energy potential reliably both for wind farms as well as small turbines. In the analysis, some measures are defined to quantify the forecast accuracy and the long-term prediction error. One of the items of discussion was motivated by the observation in the wind industry that the year 2010 was a poor year, with hopes that it was just an exceptional year and fears that it might be an indicator of continuing climate change. The result of this discussion is that 2010 can only be seen as an outlier if one assumes that the past decades represent a constant wind climate. A linear regression, however, suggests that this assumption may not be correct and that 2010 may have been a low-wind year but consistent with generally observed fluctuations around a changing wind climate.
Original languageEnglish
Pages (from-to)1014 - 1026
Number of pages13
JournalRenewable Energy
Volume50
Issue number-
Early online date25 Sep 2012
DOIs
Publication statusPublished - 2013

Fingerprint

resource
wind farm
wind turbine
climate
outlier
potential energy
turbine
timescale
climate change
industry
prediction
analysis

Cite this

@article{9a88c6b787be4e35b15037747b4422c0,
title = "Long-term wind resource and uncertainty estimation using wind records from Scotland as example",
abstract = "A systematic analysis of the sensitivity of a wind turbine’s output to changes in observed wind statistics between different sites in Scotland over available wind records of up to 43 years length was performed. The analysis was performed in the context of observed variability on time scales longer than a year. The findings are discussed in the context of the ability to predict the long-term wind energy potential reliably both for wind farms as well as small turbines. In the analysis, some measures are defined to quantify the forecast accuracy and the long-term prediction error. One of the items of discussion was motivated by the observation in the wind industry that the year 2010 was a poor year, with hopes that it was just an exceptional year and fears that it might be an indicator of continuing climate change. The result of this discussion is that 2010 can only be seen as an outlier if one assumes that the past decades represent a constant wind climate. A linear regression, however, suggests that this assumption may not be correct and that 2010 may have been a low-wind year but consistent with generally observed fluctuations around a changing wind climate.",
author = "Wolf-Gerrit Fruh",
year = "2013",
doi = "10.1016/j.renene.2012.08.047",
language = "English",
volume = "50",
pages = "1014 -- 1026",
journal = "Renewable Energy",
issn = "0960-1481",
publisher = "Elsevier",
number = "-",

}

Long-term wind resource and uncertainty estimation using wind records from Scotland as example. / Fruh, Wolf-Gerrit.

In: Renewable Energy, Vol. 50, No. -, 2013, p. 1014 - 1026.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Long-term wind resource and uncertainty estimation using wind records from Scotland as example

AU - Fruh, Wolf-Gerrit

PY - 2013

Y1 - 2013

N2 - A systematic analysis of the sensitivity of a wind turbine’s output to changes in observed wind statistics between different sites in Scotland over available wind records of up to 43 years length was performed. The analysis was performed in the context of observed variability on time scales longer than a year. The findings are discussed in the context of the ability to predict the long-term wind energy potential reliably both for wind farms as well as small turbines. In the analysis, some measures are defined to quantify the forecast accuracy and the long-term prediction error. One of the items of discussion was motivated by the observation in the wind industry that the year 2010 was a poor year, with hopes that it was just an exceptional year and fears that it might be an indicator of continuing climate change. The result of this discussion is that 2010 can only be seen as an outlier if one assumes that the past decades represent a constant wind climate. A linear regression, however, suggests that this assumption may not be correct and that 2010 may have been a low-wind year but consistent with generally observed fluctuations around a changing wind climate.

AB - A systematic analysis of the sensitivity of a wind turbine’s output to changes in observed wind statistics between different sites in Scotland over available wind records of up to 43 years length was performed. The analysis was performed in the context of observed variability on time scales longer than a year. The findings are discussed in the context of the ability to predict the long-term wind energy potential reliably both for wind farms as well as small turbines. In the analysis, some measures are defined to quantify the forecast accuracy and the long-term prediction error. One of the items of discussion was motivated by the observation in the wind industry that the year 2010 was a poor year, with hopes that it was just an exceptional year and fears that it might be an indicator of continuing climate change. The result of this discussion is that 2010 can only be seen as an outlier if one assumes that the past decades represent a constant wind climate. A linear regression, however, suggests that this assumption may not be correct and that 2010 may have been a low-wind year but consistent with generally observed fluctuations around a changing wind climate.

U2 - 10.1016/j.renene.2012.08.047

DO - 10.1016/j.renene.2012.08.047

M3 - Article

VL - 50

SP - 1014

EP - 1026

JO - Renewable Energy

JF - Renewable Energy

SN - 0960-1481

IS - -

ER -