Rozenn Wagner

Testing and comparison of lidars for profile and turbulence measurements in wind energy

Lidar profilers are beginning to gain a foothold in wind energy. Both of the currently available commercially systems have been extensively tested at the Hovsore facility in Denmark and valuable insights have been gained. The extensively instrumented facility will be described and some examples of the results given, illustrating the strength and weaknesses of the two contrasting profilers.

Lidar Scanning of Momentum Flux in and above the Atmospheric Surface Layer

Abstract Methods to measure the vertical flux of horizontal momentum using both continuous wave and pulsed Doppler lidar profilers are evaluated. The lidar measurements are compared to momentum flux observations performed with sonic anemometers over flat terrain at Hovsore, Denmark, and profile-derived vertical momentum flux observations at the Horns Rev wind farm in the North Sea. Generally, the momentum fluxes are reduced because of the finite measuring volume of the instruments, and the filtering is crudely accounted for theoretically. The essential parameter for the estimation of the reduction is the ratio of the turbulence scale to the size of the measuring volume. For the continuous wave lidar the reduction can largely be compensated by averaging Doppler spectra instead of radial velocities.

Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Operational since 2004, the National Centre for Wind Turbines at Høvsøre, Denmark has become a reference research site for wind-power meteorology. In this study, we review the site, its instrumentation, observations, and main research programs. The programs comprise activities on, inter alia, remote sensing, where measurements from lidars have been compared extensively with those from traditional instrumentation on masts. In addition, with regard to wind-power meteorology, wind-resource methodologies for wind climate extrapolation have been evaluated and improved. Further, special attention has been given to research on boundary-layer flow, where parametrizations of the length scale and wind profile have been developed and evaluated. Atmospheric turbulence studies are continuously conducted at Høvsøre, where spectral tensor models have been evaluated and extended to account for atmospheric stability, and experiments using microscale and mesoscale numerical modelling.

Comparison of 3D turbulence measurements using three staring wind lidars and a sonic anemometer

Three pulsed lidars were used in staring, non-scanning mode, placed so that their beams crossed close to a 3D sonic anemometer. The goal is to compare lidar volume averaged wind measurement with point measurement reference sensors and to demonstrate the feasibility of performing 3D turbulence measurements with lidars. The results show a very good correlation between the lidar and the sonic times series. The variance of the velocity measured by the lidar is attenuated due to spatial filtering, and the amount of attenuation can be predicted theoretically.

Rotor equivalent wind speed for power curve measurement-comparative exercise for IEA Wind Annex 32

A comparative exercise has been organised within the International Energy Agency (IEA) Wind Annex 32 in order to test the Rotor Equivalent Wind Speed (REWS) method under various conditions of wind shear and measurement techniques. Eight organisations from five countries participated in the exercise. Each member of the group has derived both the power curve based on the wind speed at hub height and the power curve based on the REWS. This yielded results for different wind turbines, located in diverse types of terrain and where the wind speed profile was measured with different instruments (mast or various lidars). The participants carried out two preliminary steps in order to reach consensus on how to implement the REWS method. First, they all derived the REWS for one 10 minute wind speed profile. Secondly, they all derived the power curves for one dataset. The main point requiring consensus was the definition of the segment area used as weighting for the wind speeds measured at the various heights in the calculation of the REWS. This comparative exercise showed that the REWS method results in a significant difference compared to the standard method using the wind speed at hub height in conditions with large shear and low turbulence intensity.

Remote sensing used for power curves

: Power curve measurement for large wind turbines requires taking into account more parameters than only the wind speed at hub height. Based on results from aerodynamic simulations, an equivalent wind speed taking the wind shear into account was defined and found to reduce the power standard deviation in the power curve significantly. Two LiDARs and a SoDAR are used to measure the wind profile in front of a wind turbine. These profiles are used to calculate the equivalent wind speed. The comparison of the power curves obtained with the three instruments to the traditional power curve, obtained using a cup anemometer measurement, confirms the results obtained from the simulations. Using LiDAR profiles reduces the error in power curve measurement, when these are used as relative instrument together with a cup anemometer. Results from the SoDAR do not show such promising results, probably because of noisy measurements resulting in distorted profiles.

Generic Methodology for Field Calibration of Nacelle-Based Wind Lidars

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtained through a methodology applicable to any type of existing and upcoming nacelle lidar technology. The generic methodology consists in calibrating all the inputs of the wind field reconstruction algorithms of a lidar. These inputs are the line-of-sight velocity and the beam position, provided by the geometry of the scanning trajectory and the lidar inclination. The line-of-sight velocity is calibrated in atmospheric conditions by comparing it to a reference quantity based on classic instrumentation such as cup anemometers and wind vanes. The generic methodology was tested on two commercially developed lidars, one continuous wave and one pulsed systems, and provides consistent calibration results: linear regressions show a difference of ∼0.5% between the lidar-measured and reference line-of-sight velocities. A comprehensive uncertainty procedure propagates the reference uncertainty to the lidar measurements. At a coverage factor of two, the estimated line-of-sight velocity uncertainty ranges from 3.2% at 3 m · s − 1 to 1.9% at 16 m · s − 1 . Most of the line-of-sight velocity uncertainty originates from the reference: the cup anemometer uncertainty accounts for ∼90% of the total uncertainty. The propagation of uncertainties to lidar-reconstructed wind characteristics can use analytical methods in simple cases, which we demonstrate through the example of a two-beam system. The newly developed calibration methodology allows robust evaluation of a nacelle lidar’s performance and uncertainties to be established. Calibrated nacelle lidars may consequently be further used for various wind turbine applications in confidence.

Remotely measuring the wind using turbine-mounted lidars: Application to power performance testing

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtained through a methodology applicable to any type of existing and upcoming nacelle lidar technology. The generic methodology consists in calibrating all the inputs of the wind field reconstruction algorithms of a lidar. These inputs are the line-of-sight velocity and the beam position, provided by the geometry of the scanning trajectory and the lidar inclination. The line-of-sight velocity is calibrated in atmospheric conditions by comparing it to a reference quantity based on classic instrumentation such as cup anemometers and wind vanes. The generic methodology was tested on two commercially developed lidars, one continuous wave and one pulsed systems, and provides consistent calibration results: linear regressions show a difference of ∼0.5% between the lidar-measured and reference line-of-sight velocities. A comprehensive uncertainty procedure propagates the reference uncertainty to the lidar measurements. At a coverage factor of two, the estimated line-of-sight velocity uncertainty ranges from 3.2% at 3 m·s−1 to 1.9% at 16 m·s−1. Most of the line-of-sight velocity uncertainty originates from the reference: the cup anemometer uncertainty accounts for ∼90% of the total uncertainty. The propagation of uncertainties to lidar-reconstructed wind characteristics can use analytical methods in simple cases, which we demonstrate through the example of a two-beam system. The newly developed calibration methodology allows robust evaluation of a nacelle lidar’s performance and uncertainties to be established. Calibrated nacelle lidars may consequently be further used for various wind turbine applications in confidence.

Nacelle power curve measurement with spinner anemometer and uncertainty evaluation

The objective of this investigation was to verify the feasibility of using the spinner anemometer calibration and nacelle transfer function determined on one reference turbine, to assess the power performance of a second identical turbine. An experiment was set up with a met-mast in a position suitable to measure the power curve of the two wind turbines, both equipped with a spinner anemometer. An IEC 61400-12-1 compliant power curve was then measured for both turbines using the met-mast. The NTF (Nacelle Transfer Function) was measured on the reference turbine and then applied to both turbines 5 to calculate the free wind speed. For each of the two wind turbines, the power curve (PC) was measured with the met-mast and the nacelle power curve (NPC) with the spinner anemometer. Four power curves (two PC and two NPC) were compared in terms of AEP (Annual Energy Production) for a Rayleigh wind speed probability distribution. For each turbine, the NPC agreed with the corresponding PC within 0.10% of AEP for the reference turbine and within 0,38% for the second turbine, for a mean wind speed of 8 m/s. 10