Lidar Scanning of Induction Zone Wind Fields over Sloping Terrain

Mikkelsen, Torben; Sjöholm, Mikael; Astrup, Poul; Peña, Alfredo; Larsen, Gunner Chr.; Dooren, Marijn Floris van; Sekar, Anantha Padmanabhan Kidambi

doi:10.1088/1742-6596/1452/1/012081

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…The ground-based short-range WindScanner system developed by DTU Wind and Energy Systems consists of three synchronized coherent CW Doppler lidars (Fig. 3), which are capable of accurately retrieving wind vectors and measuring turbulence, see Sjöholm et al (2009) for the original 3-inch system and Mikkelsen et al (2020) for the newest system with 6-inch optics used in this investigation. The wedge-shaped dual-prism scanner heads enable the lidars to agilely and rapidly steer the laser beams in any direction within ±61 • of the manually adjustable center axis (Mikkelsen et al, 2008).…”

Section: The Windscanner Systemmentioning

confidence: 99%

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Jin,

Ghirardelli,

Mann

et al. 2023

Preprint

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Abstract. 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.

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Section: The Windscanner Systemmentioning

confidence: 99%

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Jin,

Ghirardelli,

Mann

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The short-range WindScanner lidar system with three cw lidars (Fig. 2) which is developed by DTU Wind and Energy Systems, was used to measure the wind field (Vasiljević et al, 2017;Mikkelsen et al, 2020). The three WindScanners employ a dual-prism beam scanner, enabling them to orient the beam in any direction within ±61 • of the adjustable center axis (Sjöholm et al, 2014;Mikkelsen et al, 2008).…”

Section: Windscanner Lidar Systemmentioning

confidence: 99%

Suppression of precipitation bias on wind velocity from continuous-wave Doppler lidars

Jin

Mann

Angelou

et al. 2023

Preprint

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Abstract. In moderate to heavy precipitation, rain droplets may deteriorate Doppler lidars' accuracy for measuring the line-of-sight wind velocity because their projected velocity on the beam direction differs greatly from that of air. Therefore, we propose a method of effectively filtering away the adverse effects of rain on velocity estimation by sampling the Doppler spectra faster than the rain drops' beam transit time. By using a special averaging procedure, we can suppress the rain signal by sampling the spectrum at 3 kHz. On a moderately rainy day with a maximum rain intensity of 4 mm/h, three ground-based continuous-wave Doppler lidars were used to conduct a field measurement campaign 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 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 is reduced from up to −1.58 m/s of the conventional lidar data to −0.18 m/s of the normalized lidar data. This significant reduction of the bias occurs at the minute with the highest amount of rain when the measurement distance of the lidar is 103.9 m with a corresponding probe length being 9.8 m. With the smallest probe length, 1.2 m, the rain-induced bias was only present at the period with the highest rain intensity and was 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, without requiring much computational effort.

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“…However, due to technical challenges associated with installing a wind lidar in the spinner of a wind turbine, the SpinnerLidar in most field studies performed was installed on the nacelle of a wind turbine. For example, Mikkelsen et al [16] used a SpinnerLidar mounted on the nacelle of a wind turbine to acquire spatially distributed measurements of the upwind wind field. Using these observations, they studied the mean wind shear and the induction zone of a wind turbine.…”

Section: Introductionmentioning

confidence: 99%

Data Reliability Enhancement for Wind-Turbine-Mounted Lidars

Angelou

Sjöholm

2022

Remote Sensing

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Wind lidars can be used on wind turbines to monitor the inflow for power curve verification and for control purposes. In these applications, the lidar is most often placed on the nacelle behind the rotating blades, which occasionally intercept the line-of-sight measurements, resulting in decreased data availability or biased wind measurements. Distinguishing the wind from the blade signals is challenging for continuous-wave Doppler lidar observations. Here, we present a method that provides a more effective filtering than a typical filter relying on the strength of the backscattered signal. The method proposed is based on modelling the radial speed contribution generated by the wind turbine blades, and we present the results of a case study using a scanning wind lidar installed on the nacelle of an 850 kW wind turbine. We show that using the methodology proposed, we can optimize the identification of wind measurements, and thus, the data reliability of wind-turbine-mounted continuous-wave Doppler lidars is enhanced. Furthermore, the method is useful also for assessing the location and the alignment of a nacelle wind lidar in relation to a wind turbine’s rotor, which improves the accuracy of the inflow data and allows for a more efficient monitoring of the performance of a wind turbine.

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Lidar Scanning of Induction Zone Wind Fields over Sloping Terrain

Cited by 8 publications

References 3 publications

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Suppression of precipitation bias on wind velocity from continuous-wave Doppler lidars

Data Reliability Enhancement for Wind-Turbine-Mounted Lidars

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