Parameterization of the Turbulence Averaging Error by Doppler Wind Lidars: a Simulator Approach

Wind energy is a crucial component of the global energy market due to its minimal environmental impact and continuous technological advancements. Offshore wind energy, characterized by stronger and more homogeneous winds compared to onshore locations, has attracted significant interest from the industry [1]. However, the remote and inaccessible nature of offshore wind farms presents challenges for wind resource assessment. Traditional methods, such as anemometers mounted on masts, are not feasible in these environments. Doppler wind lidars (DWLs) have emerged as a viable alternative, providing cost-effective and flexible measurements of wind vectors at hub-height altitudes. DWL are highly accurate in deteriming the line-of-sight velocity. Despite this, DWLs inherently underestimate or overestimate wind turbulence, a key parameter for wind energy applications, due to the spatial and temporal averaging effect that result from the probe volume and the scanning configuration [2]. This turbulence biase can lead to over-design or increasing loads on wind turbines, significantly increasing costs.

To address this challenge, a DWL and anemometer simulator based on the Mann turbulence spectral model was developed, capable of generating high-resolution synthetic turbulent wind fields using the three Mann model parameters: turbulence length scale (​L), eddy life-time parameter (Γ), and turbulent energy dissipation rate [3]. The simulator replicates the IJmuiden offshore meteorological mast (metmast) measuring setup, allowing direct comparisons between DWL and anemometer measurements at a height of 90 m. Turbulence fields were simulated across a wide range of Mann parameter values to cover a wide range of atmospheric turbulence conditions.

The simulation results revealed that DWLs underestimate turbulence up to 50% with respect to anemometers when L approximated 0 m. Conversely, Γ had negligible influence on DWL turbulence measurements. The error in turbulence estimation by DWLs was successfully parameterized by the lturbulence length scale L, drastically reducing computational complexity while maintaining accuracy.

These findings provide a practical framework for correcting DWL turbulence measurement errors, facilitating their application in diverse atmospheric scenarios. Future work will focus on validating the parameterization with experimental data under varied atmospheric conditions and implementing the correction method to improve DWL performance in operational settings. By addressing this limitation, the results advance the reliability of offshore wind resource assessments, contributing to the broader adoption of wind energy solutions.

REFERENCES

[1] Joyce Lee and Feng Zhao, “Global wind report 2018,” Tech. Rep., Global Wind Energy Council, Apr. 2019.

[2] A. Peña, G. G. Yankova, and V. Mallini, “On the lidar-turbulence paradox and possible countermeasures,” Wind Energy Science, vol. 10, no. 1, pp. 83–102, 2025.

[3] Jakob Mann, “Wind field simulation,” Probabilistic Engineering Mechanics, vol. 13, no. 4, pp. 269–282, 1998.

 

ACKNOWLEDGEMENTS

This research is part of the project PID2021-126436OB-C21 funded by Ministerio de Ciencia e Investigación (MCIN)/Agencia Estatal de Investigación (AEI)/ 10.13039/501100011033 y FEDER “Una manera de hacer Europa” and part of the PRIN 2022 PNRR, Project P20224AT3W funded by Ministero dell’Universit`a e della Ricerca. The European Commission collaborated under projects H2020 ATMO-ACCESS (GA-101008004) and H2020 ACTRIS-IMP (GA-871115).