Pulsed Doppler Lidar wind profile measurement process in complex terrain

1. Pulsed Doppler Lidar wind profilemeasurement process in complex terrain Matthieu Boquet, Bruno Ribstein, Rémy Parmentier, Jean-Pierre Cariou LEOSPHERE SAS – Centre Scientifique d’Orsay - France

2. Agenda • Pulsed Lidar volume measurement principle • Simple & complex terrain • CFD modeling example • Optimization • Conclusions

3. Pulsed Lidar principle How Does the WindCubeTM retrieve wind Velocity vertical profiles?

4. Volume measurement aerosols s=v.cos(a) • Radial velocity along a LOS • Pulse FWHM probed sample • Conically scanning • dc=height*tanθ • Sequentially scanning • 4sec complete rotation a v q Laser shooting direction

5. Wind velocity vertical profile • 4 radial velocities  3 wind velocity components • Hypothesis: • Same wind inside the probed volume • Same wind at the 4 probed domains • Stationary atmosphere • Comparison with anemometers point measurement

6. Terrain influence How WELL DOES the WindCubeTM retrieve wind Velocity vertical profiles?

7. Flat terrain • Inferior to 1% relative difference between Lidar and cup anemometer

8. Forested area and gentle slope • About -2% relative difference between Lidar and sonic anemometer Terrain slope over 10° WindCubeTM Forest

9. Mountainous terrain • About -5% relative difference between Lidar and cup anemometer

10. CFD Modeling analysis USING a cfd modeling of a complex terrain to better understand the lidar and anemometer differences?

11. CFD modeling • MERCURE/Aria Technologies software • Adapted to complex topography • Fine meshing • 2x2x1km box • ~10x10x5m cells • Stationary  not a time variation study • Fair enough to study Lidar wind velocity retrieval process under various local complex flow • MatLab analysis • Lidar measurement process simulation

12. Spanish site North-Westwind WindCube Met mast North-Westwind

13. Wind distribution at 80m height North-westwind

14. Lidar vs. cup Underestimation <-5% Overestimation >5% North-West Wind

15. Back to the Lidar equations • Considering first order wind speed variation • Introducing wind speed gradient • θ being the zenithal angle, d=height*tanθ is the probed volume to center distance • In 2D:

16. Vertical wind speed gradient dependency

17. Geometrical Optimisation How can we modify the lidar measurement process to get closer to cup?

18. Reducing the scanning cone • Probing a smaller volume then more homogeneous: • Often but not always true • Difference depends on altitude and vertical wind speed gradient • Other issue: smaller horizontal wind speed projection  higher noise perturbation • No magical scanning cone angle • Dangerous below 15° and above 30°

19. 30° vs. 15° • 30° • 15°

20. Multiplying the lines of sight • Consider vertical wind speed linear variations • A line of sight LOSi gives the radial velocity Si: With And Thus • No LOS brings info on Wi

21. Conclusion • Point and volume measurement • Vertical wind speed inhomogeneity • Scanning cone angle 15°-30° • More lines of sight are not more useful info • Experimental set up difficult

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