Towards accurate and practical drone-based wind measurements with an ultrasonic anemometer

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.

Advanced Leak Detection and Quantification of Methane Emissions Using sUAS

“…For sUAS, lightweight and accurate wind sensors are needed to provide in situ measurements that can be used in the quantification methodology. Some examples of lightweight sensors can range from five hole probes (or multi-hole probes) to ultrasonic anemometers that utilize time of flight (e.g., Anemoment (Longmont, CO, USA) Trisonica used in [107] or the Gill (Lymington, Hampshire, UK) WindMaster used on the OP-TOKopter [108]) and resonance based (FT Technologies FT742 and FT205 used in [109]) to more custom micro electrical mechanical systems (MEMS)-based solutions (such as in [110]). These wind sensors can also be applied to general wind profiling and mapping applications.…”

“…Point source measurements with TDLAS will, on average, underestimate the concentration (see [69] for more details). On the contrary, top-mounted wind sensors can provide high accuracy if translational and induced wind velocities can be removed [108].…”

“…Figure 2. Payload configuration examples of (a) boom-mounted TDLAS on a DJI M210 used in [120],© 2020 IEEE, used with permission, (b) top-mounted anemometer in a wind tunnel showcasing the effect of propellers on the streamlines used in[108], and (c) bottom-mounted RMLD used in[121].…”

Spatially distributed and simultaneous wind measurements with a fleet of small quadrotor UAS

“…For single UAS multirotor wind measurement, different approaches exist. First, external wind sensors can be installed at the UAS, such as sonic anemometers [6], [7], [8] or hot wire probes [9], [10]. The second approach is based on the on-board avionic sensors of UAS and relates the motion of the UAS to the wind [11,12,13,14,15].…”

Distributed wind measurements with multiple quadrotor unmanned aerial vehicles in the atmospheric boundary layer

“…Turbulent structures also occur in the interaction of the ABL with wind turbines. Following the review of Veers et al (2019) one of the major challenges in the science of wind energy is the understanding of the microscale wind conditions around a wind plant -this means the inflow conditions as well as the complex wake pattern behind individual turbines and their interaction in wind parks. The goal of the project presented in this study is to provide a tool for flexible measurements in this field.…”