Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System

Floating LIDAR systems (FLS) are a cost-effective way of surveying the wind energy potential of an offshore area. However, as turbulence intensity estimates are strongly affected by wave-induced buoy motion, it is essential to correct them. In this study, we quantify the turbulence intensity measure...

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Main Authors: Thibault Désert, Graham Knapp, Sandrine Aubrun
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/13/15/2973
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spelling doaj-72dfc0b2b423488f8820132e9b0d08f42021-08-06T15:30:41ZengMDPI AGRemote Sensing2072-42922021-07-01132973297310.3390/rs13152973Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR SystemThibault Désert0Graham Knapp1Sandrine Aubrun2Ecole Centrale, Hydrodynamics, Energetics and Atmospheric Environment Research Laboratory, 1 Rue de la Noë, 44300 Nantes, FranceCSTB, Climatology, Aerodynamics, Pollution and Purification Department, 11 Rue Henri Picherit, 44300 Nantes, FranceEcole Centrale, Hydrodynamics, Energetics and Atmospheric Environment Research Laboratory, 1 Rue de la Noë, 44300 Nantes, FranceFloating LIDAR systems (FLS) are a cost-effective way of surveying the wind energy potential of an offshore area. However, as turbulence intensity estimates are strongly affected by wave-induced buoy motion, it is essential to correct them. In this study, we quantify the turbulence intensity measurement error of a WindCube v2<sup>®</sup> mounted on a 12-ton anchored buoy as a function of met-ocean conditions, and we construct a subsequently applied correction method suitable for 10-min wind LIDAR data storage. To this end, we build a model to simulate the effect of buoyancy movements on the LIDAR’s wind measurements. We first apply the model to understand the mechanisms responsible for the wind LIDAR measurement error. The effect of the buoy’s rotational and translational motions on the radial wind speed measurements of the individual beams is first studied. Second, the temporality induced by the LIDAR operation is taken into account; the effect of motion subsampling and the interaction between the different measurement beam positions. From this model, a correction method is developed and successfully applied to a 13-week experimental campaign conducted off the shores of Fécamp (Normandie, France) involving the buoy-mounted WindCube v2<sup>®</sup> compared with cup anemometers from a met mast and a fixed WindCube v2<sup>®</sup> on a platform. The correction improves the linear regression against the fixed LIDAR turbulence intensity measurements, shifting the offset from ~0.03 to ~0.005 without post-processing the remaining peaks.https://www.mdpi.com/2072-4292/13/15/2973floating wind LIDAR systemDoppler Beam Swinging (DBS)turbulence intensitymotion-induced errormodel-based correction
collection DOAJ
language English
format Article
sources DOAJ
author Thibault Désert
Graham Knapp
Sandrine Aubrun
spellingShingle Thibault Désert
Graham Knapp
Sandrine Aubrun
Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
Remote Sensing
floating wind LIDAR system
Doppler Beam Swinging (DBS)
turbulence intensity
motion-induced error
model-based correction
author_facet Thibault Désert
Graham Knapp
Sandrine Aubrun
author_sort Thibault Désert
title Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
title_short Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
title_full Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
title_fullStr Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
title_full_unstemmed Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System
title_sort quantification and correction of wave-induced turbulence intensity bias for a floating lidar system
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2021-07-01
description Floating LIDAR systems (FLS) are a cost-effective way of surveying the wind energy potential of an offshore area. However, as turbulence intensity estimates are strongly affected by wave-induced buoy motion, it is essential to correct them. In this study, we quantify the turbulence intensity measurement error of a WindCube v2<sup>®</sup> mounted on a 12-ton anchored buoy as a function of met-ocean conditions, and we construct a subsequently applied correction method suitable for 10-min wind LIDAR data storage. To this end, we build a model to simulate the effect of buoyancy movements on the LIDAR’s wind measurements. We first apply the model to understand the mechanisms responsible for the wind LIDAR measurement error. The effect of the buoy’s rotational and translational motions on the radial wind speed measurements of the individual beams is first studied. Second, the temporality induced by the LIDAR operation is taken into account; the effect of motion subsampling and the interaction between the different measurement beam positions. From this model, a correction method is developed and successfully applied to a 13-week experimental campaign conducted off the shores of Fécamp (Normandie, France) involving the buoy-mounted WindCube v2<sup>®</sup> compared with cup anemometers from a met mast and a fixed WindCube v2<sup>®</sup> on a platform. The correction improves the linear regression against the fixed LIDAR turbulence intensity measurements, shifting the offset from ~0.03 to ~0.005 without post-processing the remaining peaks.
topic floating wind LIDAR system
Doppler Beam Swinging (DBS)
turbulence intensity
motion-induced error
model-based correction
url https://www.mdpi.com/2072-4292/13/15/2973
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