Abstract
Abstract. Wind data collection in the atmospheric boundary layer benefits from short-term wind speed measurements using unmanned aerial vehicles. Fixed-wing and rotary-wing devices with diverse anemometer technology have been used in the past to provide such data, but the accuracy still has the potential to be increased. A lightweight drone for carrying an industry-standard precision sonic anemometer was developed. Accuracy tests have been performed with the isolated anemometer at high tilt angles in a calibration wind tunnel, with the drone flying in a large wind tunnel and with the full system flying at different heights next to a bistatic lidar reference. The propeller-induced flow deflects the air to some extent, but this effect is compensated effectively. The data fusion shows a substantial reduction of crosstalk (factor of 13) between ground speed and wind speed. When compared with the bistatic lidar in very turbulent conditions, with a 10 s averaging interval and with the unmanned aerial vehicle (UAV) constantly circling around the measurement volume of the lidar reference, wind speed measurements have a bias between −2.0 % and 4.2 % (root-mean-square error (RMSE) of 4.3 % to 15.5 %), vertical wind speed bias is between −0.05 and 0.07 m s−1 (RMSE of 0.15 to 0.4 m s−1), elevation bias is between −1 and 0.7∘ (RMSE of 1.2 to 6.3∘), and azimuth bias is between −2.6 and 7.2∘ (RMSE of 2.6 to 8.0∘). Key requirements for good accuracy under challenging and dynamic conditions are the use of a full-size sonic anemometer, a large distance between anemometer and propellers, and a suitable algorithm for reducing the effect of propeller-induced flow. The system was finally flown in the wake of a wind turbine, successfully measuring the spatial velocity deficit and downwash distribution during forward flight, yielding results that are in very close agreement to lidar measurements and the theoretical distribution. We believe that the results presented in this paper can provide important information for designing flying systems for precise air speed measurements either for short duration at multiple locations (battery powered) or for long duration at a single location (power supplied via cable). UAVs that are able to accurately measure three-dimensional wind might be used as a cost-effective and flexible addition to measurement masts and lidar scans.
Highlights
1.1 Wind speed measurementsMeasurements of wind characteristics are important in the environmental science of the atmospheric boundary layer (ABL)
The correlation coefficient for ground speed and wind speed is 0.164, indicating that there is no relevant linear relationship between these variables. These analyses indicate that the fusion algorithm results in a wind speed measurement that is mostly independent of ground speed and unmanned aerial vehicle (UAV) motion/rotation in general
Despite a short sampling time per height (10 min) we find this relation in our measurements (Pearson’s r of −0.79, we take the average of TILidar and TIUAV to approximate the true Turbulence intensity (TI))
Summary
Measurements of wind characteristics are important in the environmental science of the atmospheric boundary layer (ABL). They are crucial for predictions of meteorological processes Wagner et al, 2009), understanding wake interactions with the ABL in large wind farms (Kumer et al, 2015; Lungo, 2016; Li et al, 2016) and as boundary conditions for simulations of gas dispersion in the ABL Popular systems for getting the required wind velocity data in different regions of the ABL are traditional mast-mounted anemometers The methods are suitable for measurements of different ranges of temporal and spatial scales, they result in complementary. W. Thielicke et al.: Accurate drone-based wind measurements data and are often subject to comparisons Thielicke et al.: Accurate drone-based wind measurements data and are often subject to comparisons (e.g. Barthelmie et al, 2014)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
