Beck, Hauke and Kühn, Martin (2019) Temporal Up-Sampling of Planar Long-Range Doppler LiDAR Wind Speed Measurements Using Space-Time Conversion. Remote Sensing, 11 (7). p. 867. ISSN 2072-4292

- Published Version

Volltext (11Mb)


Measurement campaigns in wind energy research are becoming increasingly complex, which has exacerbated the difficulty of taking optimal measurements using light detection and ranging (LiDAR) systems. Compromises between spatial and temporal resolutions are always necessary in the study of heterogeneous flows, like wind turbine wakes. Below, we develop a method for space-time conversion that acts as a temporal fluid-dynamic interpolation without incurring the immense computing costs of a 4D flow solver. We tested this space-time conversion with synthetic LiDAR data extracted from a large-eddy-simulation (LES) of a neutrally stable single-turbine wake field. The data was synthesised with a numerical LiDAR simulator. Then, we performed a parametric study of 11 different scanning velocities. We found that temporal error dominates the mapping error at low scanning speeds and that spatial error becomes dominant at fast scanning speeds. Our space-time conversion method increases the temporal resolution of the LiDAR data by a factor 2.4 to 40 to correct the scan-containing temporal shift and to synchronise the scan with the time code of the LES data. The mean-value error of the test case is reduced to a minimum relative error of 0.13% and the standard-deviation error is reduced to a minimum of 0.6% when the optimal scanning velocity is used. When working with the original unprocessed LiDAR measurements, the space-time-conversion yielded a maximal error reduction of 69% in the mean value and 58% in the standard deviation with the parameters identified with our analysis.

Item Type: Article
Additional Information: Publiziert mit Hilfe des DFG-geförderten Open Access-Publikationsfonds der Carl von Ossietzky Universität Oldenburg.
Uncontrolled Keywords: improvement; synchronisation; statistics; wakes; scanning measurements; flow solver
Subjects: Science and mathematics > Physics
Science and mathematics > Earth sciences and geology
Divisions: Faculty of Mathematics and Science > Institute of Physics (IfP)
Scientific Centers > ForWind Center for Wind Energy Research
Date Deposited: 17 Mar 2020 13:52
Last Modified: 17 Mar 2020 13:52
URN: urn:nbn:de:gbv:715-oops-45397
DOI: 10.3390/rs11070867

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...