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Article

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

1
Ecole Centrale, Hydrodynamics, Energetics and Atmospheric Environment Research Laboratory, 1 Rue de la Noë, 44300 Nantes, France
2
CSTB, Climatology, Aerodynamics, Pollution and Purification Department, 11 Rue Henri Picherit, 44300 Nantes, France
*
Author to whom correspondence should be addressed.
Academic Editor: Alfredo Peña
Remote Sens. 2021, 13(15), 2973; https://doi.org/10.3390/rs13152973
Received: 1 June 2021 / Revised: 21 July 2021 / Accepted: 23 July 2021 / Published: 28 July 2021
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® 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® compared with cup anemometers from a met mast and a fixed WindCube v2® 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. View Full-Text
Keywords: floating wind LIDAR system; Doppler Beam Swinging (DBS); turbulence intensity; motion-induced error; model-based correction floating wind LIDAR system; Doppler Beam Swinging (DBS); turbulence intensity; motion-induced error; model-based correction
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MDPI and ACS Style

Désert, T.; Knapp, G.; Aubrun, S. Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System. Remote Sens. 2021, 13, 2973. https://doi.org/10.3390/rs13152973

AMA Style

Désert T, Knapp G, Aubrun S. Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System. Remote Sensing. 2021; 13(15):2973. https://doi.org/10.3390/rs13152973

Chicago/Turabian Style

Désert, Thibault, Graham Knapp, and Sandrine Aubrun. 2021. "Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System" Remote Sensing 13, no. 15: 2973. https://doi.org/10.3390/rs13152973

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