Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals
<p>This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with wake wind field reconstruction techniques. The first approach consists of incorporating wind measurements of the wake f...
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Copernicus Publications
2021-06-01
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Series: | Wind Energy Science |
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doaj-ff182237e5464beeb35ae2fad6be79352021-06-07T11:38:11ZengCopernicus PublicationsWind Energy Science2366-74432366-74512021-06-01684186610.5194/wes-6-841-2021Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievalsD. Conti0V. Pettas1N. Dimitrov2A. Peña3Department of Wind Energy, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, DenmarkStuttgart Wind Energy (SWE), University of Stuttgart, Allmandring 5b, 70569 Stuttgart, GermanyDepartment of Wind Energy, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, DenmarkDepartment of Wind Energy, Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark<p>This study proposes two methodologies for improving the accuracy of wind turbine load assessment under wake conditions by combining nacelle-mounted lidar measurements with wake wind field reconstruction techniques. The first approach consists of incorporating wind measurements of the wake flow field, obtained from nacelle lidars, into random, homogeneous Gaussian turbulence fields generated using the Mann spectral tensor model. The second approach imposes wake deficit time series, which are derived by fitting a bivariate Gaussian shape function to lidar observations of the wake field, on the Mann turbulence fields. The two approaches are numerically evaluated using a virtual lidar simulator, which scans the wake flow fields generated with the dynamic wake meandering (DWM) model, i.e., the <i>target</i> fields. The lidar-reconstructed wake fields are then input into aeroelastic simulations of the DTU 10 <span class="inline-formula">MW</span> wind turbine for carrying out the load validation analysis. The power and load time series, predicted with lidar-reconstructed fields, exhibit a high correlation with the corresponding target simulations, thus reducing the statistical uncertainty (realization-to-realization) inherent to engineering wake models such as the DWM model. We quantify a reduction in power and loads' statistical uncertainty by a factor of between 1.2 and 5, depending on the wind turbine component, when using lidar-reconstructed fields compared to the DWM model results. Finally, we show that the number of lidar-scanned points in the inflow and the size of the lidar probe volume are critical aspects for the accuracy of the reconstructed wake fields, power, and load predictions.</p>https://wes.copernicus.org/articles/6/841/2021/wes-6-841-2021.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
D. Conti V. Pettas N. Dimitrov A. Peña |
spellingShingle |
D. Conti V. Pettas N. Dimitrov A. Peña Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals Wind Energy Science |
author_facet |
D. Conti V. Pettas N. Dimitrov A. Peña |
author_sort |
D. Conti |
title |
Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
title_short |
Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
title_full |
Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
title_fullStr |
Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
title_full_unstemmed |
Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
title_sort |
wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals |
publisher |
Copernicus Publications |
series |
Wind Energy Science |
issn |
2366-7443 2366-7451 |
publishDate |
2021-06-01 |
description |
<p>This study proposes two methodologies for improving the accuracy of wind
turbine load assessment under wake conditions by combining nacelle-mounted
lidar measurements with wake wind field reconstruction techniques. The first
approach consists of incorporating wind measurements of the wake flow field,
obtained from nacelle lidars, into random, homogeneous Gaussian turbulence
fields generated using the Mann spectral tensor model. The second approach
imposes wake deficit time series, which are derived by fitting a bivariate
Gaussian shape function to lidar observations of the wake field, on the Mann
turbulence fields. The two approaches are numerically evaluated using a
virtual lidar simulator, which scans the wake flow fields generated with the
dynamic wake meandering (DWM) model, i.e., the <i>target</i> fields. The
lidar-reconstructed wake fields are then input into aeroelastic simulations of
the DTU 10 <span class="inline-formula">MW</span> wind turbine for carrying out the load validation
analysis. The power and load time series, predicted with lidar-reconstructed
fields, exhibit a high correlation with the corresponding target
simulations, thus reducing the statistical uncertainty
(realization-to-realization) inherent to engineering wake models such as the
DWM model. We quantify a reduction in power and loads' statistical uncertainty
by a factor of between 1.2 and 5, depending on the wind turbine component, when
using lidar-reconstructed fields compared to the DWM model results. Finally,
we show that the number of lidar-scanned points in the inflow and the size of
the lidar probe volume are critical aspects for the accuracy of the
reconstructed wake fields, power, and load predictions.</p> |
url |
https://wes.copernicus.org/articles/6/841/2021/wes-6-841-2021.pdf |
work_keys_str_mv |
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