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Estimation of the Motion-Induced Horizontal-Wind-Speed Standard Deviation in an Offshore Doppler Lidar

1
CommSensLab, Unidad de Excelencia María de Maeztu, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), E-08034 Barcelona, Spain
2
Nonlinear Dynamics, Nonlinear Optics and Lasers (DONLL), Department of Physics (DFIS), Universitat Politècnica de Catalunya (UPC), E-08222 Terrassa, Spain
3
Institut d’Estudis Espacials de Catalunya (IEEC), Universitat Politècnica de Catalunya, E-08034 Barcelona, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(12), 2037; https://doi.org/10.3390/rs10122037
Received: 30 October 2018 / Revised: 26 November 2018 / Accepted: 11 December 2018 / Published: 14 December 2018
(This article belongs to the Special Issue Remote Sensing of Atmospheric Conditions for Wind Energy Applications)
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Abstract

This work presents a new methodology to estimate the motion-induced standard deviation and related turbulence intensity on the retrieved horizontal wind speed by means of the velocity-azimuth-display algorithm applied to the conical scanning pattern of a floating Doppler lidar. The method considers a ZephIR™300 continuous-wave focusable Doppler lidar and does not require access to individual line-of-sight radial-wind information along the scanning pattern. The method combines a software-based velocity-azimuth-display and motion simulator and a statistical recursive procedure to estimate the horizontal wind speed standard deviation—as a well as the turbulence intensity—due to floating lidar buoy motion. The motion-induced error is estimated from the simulator’s side by using basic motional parameters, namely, roll/pitch angular amplitude and period of the floating lidar buoy, as well as reference wind speed and direction measurements at the study height. The impact of buoy motion on the retrieved wind speed and related standard deviation is compared against a reference sonic anemometer and a reference fixed lidar over a 60-day period at the IJmuiden test site (the Netherlands). Individual case examples and an analysis of the overall campaign are presented. After the correction, the mean deviation in the horizontal wind speed standard deviation between the reference and the floating lidar was improved by about 70%, from 0.14 m/s (uncorrected) to −0.04 m/s (corrected), which makes evident the goodness of the method. Equivalently, the error on the estimated turbulence intensity (3–20 m/s range) reduced from 38% (uncorrected) to 4% (corrected). View Full-Text
Keywords: wind energy; remote sensing; Doppler wind lidar; velocity-azimuth-display algorithm; resource assessment; offshore; turbulence intensity wind energy; remote sensing; Doppler wind lidar; velocity-azimuth-display algorithm; resource assessment; offshore; turbulence intensity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gutiérrez-Antuñano, M.A.; Tiana-Alsina, J.; Salcedo, A.; Rocadenbosch, F. Estimation of the Motion-Induced Horizontal-Wind-Speed Standard Deviation in an Offshore Doppler Lidar. Remote Sens. 2018, 10, 2037.

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