Beck, Hauke and Kühn, Martin (2019) Reconstruction of Three-Dimensional Dynamic Wind-Turbine Wake Wind Fields with Volumetric Long-Range Wind Doppler LiDAR Measurements. Remote Sensing, 11 (22). p. 2665. ISSN 2072-4292

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This paper presents a method for reconstructing the wake wind field of a wind turbine based on planar light detection and ranging (LiDAR) scans crossing the wake transversally in the vertical and horizontal directions. Volumetric measurements enable the study of wake characteristics in these two directions. Due to a lack of highly resolved wind speed measurements as reference data, we evaluate the reconstruction in a synthetic environment and determine the reconstruction errors. The wake flow of a multi-megawatt wind turbine is calculated within a 10-min large-eddy simulation (LES) for high-thrust loading conditions. We apply a numerical LiDAR simulator to this wake wind field to achieve realistic one-dimensional velocity data. We perform a nacelle-based set-up with combined plan position indicator and range height indicator scans with eight scanning velocities each. We temporally up-sample the synthetic LiDAR data with a weighted combination of forward- and backward-oriented space–time conversion to retrospectively extract high-resolution wake characteristic dynamics. These dynamics are used to create a dynamic volumetric wake deficit. Finally, we reconstruct the dynamic wake wind field in three spatial dimensions by superposing an ambient wind field with the dynamic volumetric wake deficit. These results demonstrate the feasibility of wake field reconstruction using long-range LiDAR measurements.

Item Type: Article
Additional Information: Publiziert mit Hilfe des DFG-geförderten Open Access-Publikationsfonds der Carl von Ossietzky Universität Oldenburg.
Uncontrolled Keywords: LiDAR simulator, wind-field propagation, measurement synchronization, space–time conversion, wake model, error analysis
Subjects: Social sciences > Natural resources, energy and environment
Science and mathematics > Physics
Divisions: Faculty of Mathematics and Science > Institute of Physics (IfP)
Scientific Centers > ForWind Center for Wind Energy Research
Date Deposited: 20 Mar 2020 09:54
Last Modified: 20 Mar 2020 09:54
URN: urn:nbn:de:gbv:715-oops-46173
DOI: 10.3390/rs11222665

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