A Unified Formulation for the Computation of the Six-Degrees-of-Freedom-Motion-Induced Errors in Floating Doppler Wind LiDARs

This work presents an analytical formulation to assess the six-degrees-of-freedom-motion-induced error in floating Doppler wind LiDARs (FDWLs). The error products derive from the horizontal wind speed bias and apparent turbulence intensity. Departing from a geometrical formulation of the FDWL attitude and of the LiDAR retrieval algorithm, the contributions of the rotational and translational motion to the FDWL-measured total error are computed. Central to this process is the interpretation of the velocity–azimuth display retrieval algorithm in terms of a first-order Fourier series. The obtained 6 DoF formulation is validated numerically by means of a floating LiDAR motion simulator and experimentally in nearshore and open-sea scenarios in the framework of the Pont del Petroli and IJmuiden campaigns, respectively. Both measurement campaigns involved a fixed and a floating ZephIRTM 300 LiDAR. The proposed formulation proved capable of estimating the motion-induced FDWL horizontal wind speed bias and returned similar percentiles when comparing the FDWL with the fixed LiDAR. The estimations of the turbulence intensity increment statistically matched the FDWL measurements under all motional and wind scenarios when clustering the data as a function of the buoy’s mean tilt amplitude, mean translational-velocity amplitude, and mean horizontal wind speed.

[1]  F. Rocadenbosch,et al.  Enhanced Dual Filter for Floating Wind Lidar Motion Correction: The Impact of Wind and Initial Scan Phase Models , 2022, Remote. Sens..

[2]  J. Mann,et al.  Quantification of motion-induced measurement error on floating lidar systems , 2022, Atmospheric Measurement Techniques.

[3]  X. Yue,et al.  Calibration of Phased-Array High-Frequency Radar on an Anchored Floating Platform , 2022, Remote. Sens..

[4]  F. Rocadenbosch,et al.  Assessing Obukhov Length and Friction Velocity from Floating Lidar Observations: A Data Screening and Sensitivity Computation Approach , 2022, Remote. Sens..

[5]  Francesc Rocadenbosch,et al.  A Robust Adaptive Unscented Kalman Filter for Floating Doppler Wind-LiDAR Motion Correction , 2021, Remote. Sens..

[6]  Sandrine Aubrun,et al.  Quantification and Correction of Wave-Induced Turbulence Intensity Bias for a Floating LIDAR System , 2021, Remote. Sens..

[7]  A. Apituley,et al.  A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw , 2021, 2105.11859.

[8]  Francesc Rocadenbosch,et al.  Estimation of Wave Period from Pitch and Roll of a Lidar Buoy , 2021, Sensors.

[9]  Weimin Huang,et al.  HF Radar Ocean Surface Cross Section for the Case of Floating Platform Incorporating a Six-DOF Oscillation Motion Model , 2021, IEEE Journal of Oceanic Engineering.

[10]  H. Kawabata,et al.  Field Measurements of Wind Characteristics Using LiDAR on a Wind Farm with Downwind Turbines Installed in a Complex Terrain Region , 2020, Energies.

[11]  Jakob Mann,et al.  Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar , 2020, Remote. Sens..

[12]  Francesc Rocadenbosch,et al.  Estimation of the Motion-Induced Horizontal-Wind-Speed Standard Deviation in an Offshore Doppler Lidar , 2018, Remote. Sens..

[13]  Wei Yu,et al.  Validating a simulation environment for floating lidar systems , 2018, Journal of Physics: Conference Series.

[14]  Francesc Rocadenbosch,et al.  Performance evaluation of a floating lidar buoy in nearshore conditions , 2017 .

[15]  Julia Gottschall,et al.  Floating lidar as an advanced offshore wind speed measurement technique: current technology status and gap analysis in regard to full maturity , 2017 .

[16]  Joaquim Sospedra Iglesias,et al.  Novel multipurpose buoy for offshore wind profile measurements EOLOS platform faces validation at ijmuiden offshore metmast , 2015 .

[17]  G. Wolken-Möhlmann,et al.  About offshore resource assessment with floating lidars with special respect to turbulence and extreme events , 2014 .

[18]  Charlotte Bay Hasager,et al.  Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China , 2014 .

[19]  Pierre H. Flamant,et al.  0.355-micrometer direct detection wind lidar under testing during a field campaign in consideration of ESA's ADM-Aeolus mission , 2013 .

[20]  John L. Schroeder,et al.  Measuring a Utility-Scale Turbine Wake Using the TTUKa Mobile Research Radars , 2012 .

[21]  Robert M. Banta,et al.  Doppler Lidar–Based Wind-Profile Measurement System for Offshore Wind-Energy and Other Marine Boundary Layer Applications , 2012 .

[22]  Steven Lang,et al.  LIDAR and SODAR Measurements of Wind Speed and Direction in Upland Terrain for Wind Energy Purposes , 2011, Remote. Sens..

[23]  J. Peinke,et al.  Atmospheric turbulence and its influence on the alternating loads on wind turbines , 2011 .

[24]  Bob Palais,et al.  A Disorienting Look at Euler's Theorem on the Axis of a Rotation , 2009, The American mathematical monthly.

[25]  Rebecca J. Barthelmie,et al.  Review of Methodologies for Offshore Wind Resource Assessment in European Seas , 2008 .

[26]  Pierre H. Flamant,et al.  Experimental Validation of Wind Profiling Performed by the Airborne 10-μm Heterodyne Doppler Lidar WIND , 2001 .

[27]  Rebecca J. Barthelmie,et al.  Meteorological aspects of offshore wind energy: Observations from the Vindeby wind farm , 1996 .

[28]  S. Vogt,et al.  SODAR — A useful remote sounder to measure wind and turbulence , 1995 .

[29]  Harold Jeffreys,et al.  On the Formation of Water Waves by Wind , 1925 .

[30]  M. Plancherel,et al.  Contribution À ĽÉtude de la reprÉsentation D’une fonction arbitraire par des intÉgrales dÉfinies , 1910 .

[31]  G. Wolken-Möhlmann,et al.  Results and conclusions of a floating-lidar offshore test , 2014 .

[32]  Ioannis Antoniou,et al.  Lidar profilers in the context of wind energy–a verification procedure for traceable measurements , 2012 .

[33]  R. Barthelmie,et al.  Can Satellite Sampling of Offshore Wind Speeds Realistically Represent Wind Speed Distributions , 2003 .