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Reason: The data set is under conversion to the FAIR data format. In mean time, the dataset is freely accessible through a MySQL database hosted at DTU Wind Energy. To gain the access to the database send your requests to the dataset authors.
A data set for comparison of sector-scan and dual-Doppler retrievals of horizontal wind speed and wind direction made using multiple scanning lidars
Any type of resource available online.
Acquiring actual wind velocities at potential wind farm sites is an important way of reducing the uncertainty in estimates obtained from meso-scale models. Since costs of offshore meteorological masts are high, ground based scanning lidars installed on-shore could be a cost-attractive way of acquiring necessary information about the wind velocity in near-coastal regions (up to about 10km). One important decision is whether to use one sector-scanning scanning lidar or two separated scanning lidars employing dual-Doppler to derive the horizontal wind velocity and direction. Acquiring actual wind velocities at potential wind farm sites is an important way of reducing the uncertainty in estimates obtained from meso-scale models.
As the name implies, a sector-scanning lidar measures the radial velocity of the wind in a sector using a plan-position-indicator (PPI) trajectory. Assuming horizontal homogeneity, the different radial velocities can be regarded as different projections of the same horizontal velocity and from this the horizontal velocity can be derived. The homogeneity assumption can be avoided if the dual-Doppler velocity retrieval technique is applied where two separated scanning lidars acquire intersecting radial velocities at the area of interest. This two radial velocities represent different projections of the same velocity and the horizontal velocity and direction from them can be easily calculated.
For near-shore and flat coastal areas the flow tends to be horizontally homogeneous, and thus it is expected that the single-Doppler retrieval techniques might estimate horizontal velocities and wind directions sufficiently accurate for wind resource assessment, avoiding the cost and complication of two separated lidars. In order to validate such assumption, an experiment with the long-range WindScanner system, which consists of three scanning lidars coordinated by a remote master computer, took place at the flat coastal site of Høvsøre, Denmark. Two scanning lidars were configured in a staring mode, where they intersected the laser beams next to the cup anemometer and wind vane mounted at 116-m on a met mast. The third lidar was configured to perform PPI scans of 45 ̊ and 60 ̊ degrees at the fixed elevation, acquiring the radial velocities around the same cup anemometer and wind vane.
The data users can apply dual-Doppler retrieval technique on the measurements produced from the two lidars in the staring mode, while the single-Doppler retrieval technique can be applied on the measurements from the lidar which performed PPI scans.
The dataset includes also measurements from the 116-m mast for the period when the long-range WindScanner system operated. The mast measurements may be used to validate the single- and dual- Doppler retrievals.
Consult a list of references provided as links in References metadata field below for more details about :
(1) The long-range WindScanner system and first comparison between single- and dual- Doppler retrievals from the aforementioned measurement campaign
(2) Høvsøre site and 116-m mast
(3) EWEA Offshore presentation of the measurements campaign
Related publications metadata field includes a link to the master thesis which explored the described dataset in more details.
Danish Agency for Science, Technology and Innovation grant no. 2136-08-0022
Related publications (DOI or link to DTU Orbit, DTU Findit)
DateStart date:2014-04-30 Stop date: 2014-05-15
- Siting;>Wind Mapping
- Siting;>Resource assessment
- Siting;>Design conditions;>Other
- Not applicable
- Measurements;>Field experiment
- Validation;>Uncertainty analysis
- Terrain type;>Flat
- Meteorological data