Evaluating the impact of motion compensation on turbulence intensity measurements from continuous-wave and pulsed floating lidars

Abstract. Floating lidar systems (FLSs) play a crucial role in offshore wind resource assessment, offering a cost-effective and flexible alternative to traditional meteorological masts. While wind speed and wind direction measurements from FLSs demonstrate high accuracy without further in-depth correction required, platform motion introduces systematic overestimation of turbulence intensity (TI), requiring compensation to ensure reliability. This study presents the first published report of an offshore deployment of a pulsed FLS operating at 5 Hz effective sampling frequency with full deterministic motion compensation. A side-by-side comparison was conducted with a continuous-wave (cw) FLS of the same platform type under identical offshore conditions. Both systems were benchmarked against a met mast cup anemometer reference, with a fixed cw lidar included for plausibility checks. Performance was evaluated using a comprehensive multi-metric framework, including regression analyses, absolute and relative error measures (MBE, MRBE, RMSE, RRMSE), representative TI error (Q90 error), and quantile-based distribution analysis. While it is well established that deterministic motion compensation improves TI estimates from floating cw lidars, this study demonstrates for the first time that the same approach, when applied to pulsed systems operating at 5 Hz, yields TI bias convergence with floating cw lidars relative to a met mast reference under identical offshore conditions. After compensation, floating cw and pulsed TI bias converged towards the cup reference with no systematic ranking, while the pulsed system showed a modest but consistent advantage in scatter-based metrics. A central finding is that effective sampling frequency is a decisive configuration parameter for pulsed systems: empirical evidence demonstrates that a 5 Hz operation adequately resolves turbulence and motion timescales, achieving industry-relevant TI accuracy. In contrast, 1 Hz undersamples these processes and consistently overestimates TI, whereas 50 Hz cw scanning provides no decisive benefit beyond 5 Hz. These results establish deterministic motion compensation as a transparent and effective baseline for offshore FLS turbulence assessment. For pulsed deployments, a 5 Hz configuration is sufficient, while residual scatter remains the main limitation. Future work should refine the compensation algorithm by accounting for lidar sensitivities and improving sensor synchronization, while broadening validation across platform types, sea states, and lidar configurations. Another important direction is the systematic comparison of different motion-compensation types under identical sea-state and platform-response conditions. Sensitivity studies of motion characteristics, atmospheric stability, and lidar parameters are also needed. Machine learning post-processing may be explored as a complementary tool to further reduce dispersion.

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Publication Details

Journal
Wind energy science
Published
2025-11-27
DOI
https://doi.org/10.5194/wes-10-2791-2025
Primary Topic
Wind Energy Research and Development
Type
article
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article

Evaluating the impact of motion compensation on turbulence intensity measurements from continuous-wave and pulsed floating lidars

Gerrit Wolken‐Möhlmann, Warren Watson, Julia Gottschall
Wind energy science
Wind Energy Research and Development
article

Evaluating the impact of motion compensation on turbulence intensity measurements from continuous-wave and pulsed floating lidars

Gerrit Wolken‐Möhlmann, Warren Watson, Julia Gottschall
article en

Abstract

Abstract. Floating lidar systems (FLSs) play a crucial role in offshore wind resource assessment, offering a cost-effective and flexible alternative to traditional meteorological masts. While wind speed and wind direction measurements from FLSs demonstrate high accuracy without further in-depth correction required, platform motion introduces systematic overestimation of turbulence intensity (TI), requiring compensation to ensure reliability. This study presents the first published report of an offshore deployment of a pulsed FLS operating at 5 Hz effective sampling frequency with full deterministic motion compensation. A side-by-side comparison was conducted with a continuous-wave (cw) FLS of the same platform type under identical offshore conditions. Both systems were benchmarked against a met mast cup anemometer reference, with a fixed cw lidar included for plausibility checks. Performance was evaluated using a comprehensive multi-metric framework, including regression analyses, absolute and relative error measures (MBE, MRBE, RMSE, RRMSE), representative TI error (Q90 error), and quantile-based distribution analysis. While it is well established that deterministic motion compensation improves TI estimates from floating cw lidars, this study demonstrates for the first time that the same approach, when applied to pulsed systems operating at 5 Hz, yields TI bias convergence with floating cw lidars relative to a met mast reference under identical offshore conditions. After compensation, floating cw and pulsed TI bias converged towards the cup reference with no systematic ranking, while the pulsed system showed a modest but consistent advantage in scatter-based metrics. A central finding is that effective sampling frequency is a decisive configuration parameter for pulsed systems: empirical evidence demonstrates that a 5 Hz operation adequately resolves turbulence and motion timescales, achieving industry-relevant TI accuracy. In contrast, 1 Hz undersamples these processes and consistently overestimates TI, whereas 50 Hz cw scanning provides no decisive benefit beyond 5 Hz. These results establish deterministic motion compensation as a transparent and effective baseline for offshore FLS turbulence assessment. For pulsed deployments, a 5 Hz configuration is sufficient, while residual scatter remains the main limitation. Future work should refine the compensation algorithm by accounting for lidar sensitivities and improving sensor synchronization, while broadening validation across platform types, sea states, and lidar configurations. Another important direction is the systematic comparison of different motion-compensation types under identical sea-state and platform-response conditions. Sensitivity studies of motion characteristics, atmospheric stability, and lidar parameters are also needed. Machine learning post-processing may be explored as a complementary tool to further reduce dispersion.

Wind energy scienceVol. 10(11)
University of Bremen (DE), Fraunhofer Institute for Wind Energy Systems (DE)
Openalex Percentile: Top 52%
Wind Energy Research and Development
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