Posters - WindEurope Technology Workshop 2022
Resource Assessment & Analysis of Operating Wind Farms 2022
23-24 June • Brussels


Come meet the poster presenters to ask them questions and discuss their work

Check the programme for our poster viewing moments. For more details on each poster, click on the poster titles to read the abstract.

PO080: CFD-based LiDAR flow curvature correction in complex terrain

Ru LI, Research engineer, Meteodyn


The remote sensing devices, especially Doppler LiDAR, are widely used in wind resource assessment as supplementary measurement technique to mast-mounted cup anemometers. The LiDAR helps to reduce the wind measurement incertitude at hub height with low cost and high mobility. But the LiDAR measurement uncertainty in complex terrains is known. The Doppler LiDAR directly measures the wind speed of sent lasers into the atmosphere, called the radial velocity. Then, a flow curvature reconstruction process is applied to convert the radial velocities to the wind flow speed. This reconstruction process assumes a homogeneous wind flow or uses a simple wind flow model to estimate the flow variation, which challenges the performance of LiDAR in complex terrains. Using Computational Fluid Dynamics (CFD)-based method to improve the LiDAR performance has been proposed. Meteodyn WT, a CFD-based wind simulation software, models the wind flow in complex terrains and provides the detailed wind flow characters, the inflow angles and wind deviation. A correction of raw LiDAR measurement technique taking into account the LiDAR geometry, plus the simulated inflow angles and wind deviations at LiDAR beam heights and in the directions of sent laser, is developed by Meteodyn to convert the raw LiDAR measurement to the wind flow speed. Molas B300, a Doppler LiDAR manufactured by Movelaser is installed on the ridge of a hill, close to a met mast during a wind measurement campaign. The site displays an altitude of 220m above sea level. Considering the roughness and atmospheric stability, the LiDAR corrections from Meteodyn WT with 36 wind direction sectors being every 10-degree step, are applied to the LiDAR wind speed data to obtain the corrected wind speed series. The corrected LiDAR wind speed data is compared with the met mast wind speed data served as reference. The results show that the corrected LiDAR wind speed data allows to reduce the measurement errors less than 2% for 90% of the sectors, even less than 1% for 50% of the sectors. It can be concluded that the LiDAR correction is a promising solution to improve the LiDAR performance in complex terrain.