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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Main Authors: D. Conti, V. Pettas, N. Dimitrov, A. Peña
Format: Article
Language:English
Published: Copernicus Publications 2021-06-01
Series:Wind Energy Science
Online Access:https://wes.copernicus.org/articles/6/841/2021/wes-6-841-2021.pdf
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spelling 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
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