Jakob Mann’s research while affiliated with Technical University of Denmark and other places

We determine the impact of floating turbine motion on turbulence measurements from a four-beam lidar by emulating its scanning configuration and retrievals within atmospheric turbulence boxes. Since the elevation angle of the lidar beams is small and the two bottom lidar beams point closely to the horizontal plane, we also evaluate the turbulence estimation abilities of a two-beam lidar. For the two-beam nacelle lidar, the variance of the individual beams is close to the target u -variance and closer than that we compute by reconstructing the u -velocity component with the two lidar beams radial velocities. By using floating turbine motion measurements from Hywind, we show that the floating turbine motion impacts turbulence estimations of the nacelle lidar. Roll does not have a clear impact on nacelle-lidar turbulence, whereas both the beam and the u -reconstructed variances increase with pitch amplitude.

Ultrasonic anemometers mounted on rotary-wing drones have the potential to provide a cost-efficient alternative to the classical meteorological mast-mounted counterpart for atmospheric boundary layer research. However, the propeller-induced flow may degrade the accuracy of free-stream wind velocity measurements by wind sensors mounted on drones – a fact that needs to be investigated for optimal sensor placement. Computational fluid dynamics (CFD) simulations are an alternative to experiments for studying characteristics of the propeller-induced flow but require validation. Therefore, we performed an experiment using three short-range continuous-wave Doppler lidars (light detection and ranging; DTU WindScanners) to measure the complex and turbulent three-dimensional wind field around a hovering drone at low ambient wind speeds. Good agreement is found between experimental results and those obtained using CFD simulations under similar conditions. Both methods conclude that the disturbance zone (defined as a relative deviation from the mean free-stream velocity by more than 1 %) on a horizontal plane located at 1 D (rotor diameter D of 0.71 m) below the drone extends about 2.8 D upstream from the drone center for the horizontal wind velocity and more than 7 D for the vertical wind velocity. By comparing wind velocities along horizontal lines in the upstream direction, we find that the velocity difference between the two methods is ≤ 0.1 ms-1 (less than a 4 % difference relative to the free-stream velocity) in most cases. Both the plane and line scan results validate the reliability of the simulations. Furthermore, simulations of flow patterns in a vertical plane at the ambient speed of 1.3 ms-1 indicate that it is difficult to accurately measure the vertical wind component with less than a 1 % distortion using drone-mounted sonic anemometers.

Application of lidars in civil engineering is evolving in many areas, for instance in planning and estimating design loads for long-span bridges. The use of the lidar technology in the wind tunnel provides a new option for turbulence measurements around model scale structures. The paper presents a wind tunnel test campaign using a combination of two continuous wave lidars and Cobra probes to study the flow conditions downstream of a bridge deck model, within and outside of the wake region. The measurements took place in a boundary layer flow at the wind tunnel facility of Politecnico di Milano where the performance of the two lidars for studying bridge aerodynamics was tested and is herein validated by reference Cobra probe measurements. The wake characteristics around the bridge deck are explored with the aim of improving the understanding of the nature of the wind forces acting on a bridge girder and demonstrating the potential of the remote sensing technology for wind tunnel studies relevant to bridge design.

Rain measurements based on the remote sensing technique play an important role in many fields. In this paper, the DTU-developed continuous-wave SpinnerLidar, deployed on top of a wind turbine, is used to investigate the feasibility of rain measurement. Considering the wind-driven effect on raindrops, a retrieval method is proposed to obtain the rain vector velocity, rain drop size distribution (DSD), and rain intensity from the combined Doppler spectrum of precipitation and wind based on a nacelle-mounted Doppler lidar. To evaluate the performance of the rain identification method, the rain vector velocities and wind speeds identified from the SpinnerLidar are compared with those from the disdrometer and the sonic anemometers, respectively. The results indicate that a nacelle-mounted wind lidar has the ability to observe the rainfall velocity even with low elevation angles of about 20° - 30° of the laser beams. The multi-peak structure produced by raindrops in the Doppler lidar spectrum was reported for the first time, which may be attributed to the wide range of sizes of raindrops and snowflakes, and their different corresponding falling velocities. Additionally, the rain and wind spectra retrieved from the SpinnerLidar are in good agreement with those calculated from the rain drop size and speed distributions from the disdrometer combined with backscattering models, and the probability density function of wind speeds measured by the sonic anemometer, respectively, on both clear and rainy days. Finally, the errors of the DSD and rain intensity estimation related to the rain attenuation effect, rain echo signals beyond the Rayleigh length of continuous-wave lidar, and the two assumptions underlying the proposed method were analyzed and discussed. The results indicated that under typical atmospheric conditions, the absolute value of the error induced by the two assumptions is mainly less than 0.5 m/s, fluctuating between 0.1 to 0.3 m/s.

In moderate to heavy precipitation, raindrops may deteriorate the accuracy of Doppler lidar measurements of the line-of-sight wind velocity because their projected velocity in the beam direction differs greatly from that of air. Therefore, we propose a method for effectively suppressing the adverse effects of rain on velocity estimation by sampling the Doppler spectra faster than the time taken for a raindrop to transit through the beam. By using a special averaging procedure, we can suppress the strong rain signal by sampling the spectrum at 3 kHz. A proof-of-concept field measurement campaign was performed on a moderately rainy day with a maximum rain intensity of 4 mmh-1 using three ground-based continuous-wave Doppler lidars at the Risø campus of the Technical University of Denmark. We demonstrate that the rain bias can effectively be removed by normalizing the noise-flattened 3 kHz sampled Doppler spectra with their peak values before they are averaged down to 50 Hz prior to the determination of the speed. In comparison to the sonic anemometer measurements acquired at the same location, the wind velocity bias at 50 Hz (20 ms) temporal resolution is reduced from up to -1.58 ms-1 for the original raw lidar data to -0.18 ms-1 for the normalized lidar data after suppressing strong rain signals. This reduction in the bias occurs during the minute with the highest amount of rain when the focus distance of the lidar is 103.9 m and the corresponding probe length is 9.8 m. With the smallest probe length, 1.2 m, the rain-induced bias is only present at the period with the highest rain intensity and is also effectively eliminated with the procedure. Thus, the proposed method for reducing the impact of rain on continuous-wave Doppler lidar measurements of air velocity is promising and does not require much computational effort.

Ultrasonic anemometers mounted on rotary-wing drones have the potential to provide a cost-efficient alternative to the classical meteorological mast-mounted counterpart for wind energy applications. However, the propeller-induced flow may deteriorate the accuracy of free wind velocity measurements by wind sensors mounted on the drone. Therefore, we performed an experiment using three short-range continuous-wave Doppler lidars (DTU WindScanners) to measure the complex and turbulent three-dimensional wind field around a hovering drone at low ambient wind speeds. The results obtained by lidar measurements and computational fluid dynamics simulations are in good agreement. Both methods conclude that the disturbance zone on a horizontal plane 0.7 meters below the drone, extends about 2 meters upstream from the drone center for the horizontal wind velocity and more than 5 meters for the vertical wind velocity. By comparing wind velocities along horizontal lines in the upstream direction, we find that the velocity difference between the two methods is less than 0.1 ms−1 in most cases. Both plane and line scan results validate the reliability of simulations. Furthermore, simulations of flow patterns in a vertical plane at low ambient speed indicate that it is difficult to accurately measure the vertical wind component with less than 1 % distortion by drone-mounted sonic anemometers.

We investigate the characteristics of the inflow and the wake of a 6 MW floating wind turbine from the Hywind Scotland offshore wind farm, the world's first floating wind farm. We use two commercial nacelle-mounted lidars to measure the up- and downwind conditions with a fixed and a scanning measuring geometry, respectively. In the analysis, the effect of the pitch and roll angles of the nacelle on the lidar measuring location is taken into account. The upwind conditions are parameterized in terms of the mean horizontal wind vector at hub height, the shear and veer of the wind profile along the upper part of the rotor, and the induction of the wind turbine rotor. The wake characteristics are studied in two narrow wind speed intervals between 8.5–9.5 and 12.5–13.5 m s-1, corresponding to below and above rotor rated speeds, respectively, and for turbulence intensity values between 3.3 %–6.4 %. The wake flow is measured along a horizontal plane by a wind lidar scanning in a plan position indicator mode, which reaches 10 D downwind. This study focuses on the downstream area between 3 and 8 D. In this region, our observations show that the transverse profile of the wake can be adequately described by a self-similar wind speed deficit that follows a Gaussian distribution. We find that even small variations (∼1 %–2 %) in the ambient turbulence intensity can result in an up to 10 % faster wake recovery. Furthermore, we do not observe any additional spread of the wake due to the motion of the floating wind turbine examined in this study.

Remote wind sensing technologies allow for measurements in a spatial domain beyond the one accessible by anemometers fixed to a mast. Remote optical wind sensors installed at an existing bridge site can both provide new information on the wind flow upstream of the bridge and capture the disturbed flow around the structure. These possibilities are explored in the presented measurement campaign with three synchronised continuous-wave Doppler lidars at the Lysefjord bridge in Norway. In particular, the interaction between the oncoming wind flow and the bridge deck is studied in terms of the mean velocity deficit wake profile as well as the spectral turbulence characteristics. The lidar measurements are validated by comparing the lidar observations at locations undisturbed by the structure with corresponding sonic anemometer data recorded 6 m and 10 m above the deck. The consistency between the two sets of data is tested in terms of the turbulence time series, their spectral content and the statistical moments. Within the wake of the bridge, significant values of vertical velocity and inclination angles, as well as turbulence intensities are seen. Moreover, the wake region can be distinguished by its singular spectral content, cross-correlation coefficient, and coherence. The results show that the tailored configuration of the lidars succeeded in providing information on 3D turbulence around the bridge, thereby capturing the bridge aerodynamic characteristics in full-scale.

Through numerical simulations and the analysis of field measurements, we investigate the dependence of the accuracy and uncertainty of turbulence estimations on the main features of the nacelle lidars' scanning strategy, i.e., the number of measurement points, the half-cone opening angle, the focus distance and the type of the lidar system. We assume homogeneous turbulence over the lidar scanning area in front of a Vestas V52 wind turbine. The Reynolds stresses are computed via a least-squares procedure that uses the radial velocity variances of each lidar beam without the need to reconstruct the wind components. The lidar-retrieved Reynolds stresses are compared with those from a sonic anemometer at turbine hub height. Our findings from the analysis of both simulations and measurements demonstrate that to estimate the six Reynolds stresses accurately, a nacelle lidar system with at least six beams is required. Further, one of the beams of this system should have a different opening angle. Adding one central beam improves the estimations of the velocity components' variances. Assuming the relations of the velocity components' variances as suggested in the IEC standard, all considered lidars can estimate the along-wind variance accurately using the least-squares procedure and the Doppler radial velocity spectra. Increasing the opening angle increases the accuracy and reduces the uncertainty on the transverse components, while enlarging the measurement distance has opposite effects. All in all, a six-beam continuous-wave lidar measuring at a close distance with a large opening angle provides the best estimations of all Reynolds stresses. This work gives insights on designing and utilizing nacelle lidars for inflow turbulence characterization.

We investigate the characteristics of the inflow and the wake of a 6MW floating wind turbine from the Hywind Scotland offshore wind farm, the world's first floating wind farm. We use two commercial nacelle-mounted lidars to measure the up- and downwind conditions, with a fixed and a scanning measuring geometry, respectively. In the analysis, the effect of the surge and sway motion of the nacelle on the lidar measuring location is taken into account. The upwind conditions are parameterised in terms of the mean horizontal wind vector at hub height, the shear and veer of the wind profile along the upper part of the rotor and the induction of the wind turbine rotor. The wake characteristics are studied in two narrow wind speed intervals 8.5–9.5 ms-1 and 12.5–13.5 ms-1, corresponding to below and above rotor rated speeds, respectively, and for turbulence intensity values between 3.3 %–6.4 %. The wake flow is measured by a wind lidar scanning in a horizontal plan position indicator mode, which reaches ten rotor diameters downwind. This study focuses on the downstream area between 3 and 8 rotor diameters. In this region, our observations show that the transverse profile of the wake can be adequately described by a self-similar wind speed deficit, that follows a Gaussian distribution. We find that even small variations (∼1 %–2 %) of the ambient turbulence intensity can result in an up to 10 % faster wake recovery. Furthermore, we do not observe any additional spread of the wake due to the motion of the floating wind turbine.