Accelerating renewable energy deployment requires a substantial increase
in installed wind power capacity. In its updated Roadmap 2010, the
European Strategy Forum on Research Infrastructures (ESFRI) has
identified 50 new research infrastructures or major upgrades of existing
ones. Under the Innovation Union initiative, the EU set itself the
challenge of launching the construction of 60 % of these priority
European research infrastructures by 2015.
The EU-funded project 'WindScanner.eu - The European windscanner facility' (
WINDSCANNER)
aims to maintain European technological leadership in high-resolution
remote sensing methodologies for full-scale real atmospheric wind and
turbulence measurements.
WINDSCANNER involves a system that generates 3D detailed maps of
wind conditions around either a single wind turbine or across a farm
covering several square kilometres. Researchers are using laser-based
devices called light detection and ranging (LIDARs). These send laser
beams out into the air, and when they hit particles they are reflected
back to the scanner. Information on these reflected beams provides
information about wind conditions.
The WINDSCANNER facility should provide a number of important
services for the scientific community. These include joint training and
educational programmes for operating the WINDSCANNER system and a
strategic approach for planning and implementing measurement campaigns.
The first measurement campaign is being prepared at a test site in
Germany, with six LIDARs that operate in parallel coupled to the 3D
WINDSCANNER system.
Once completed, WINDSCANNER is expected to play a pivotal role in
upgrading the European nodes with modern LIDAR technology. Furthermore,
it should also help each of the European Energy Research Alliance (EERA)
countries build their own national node facilities. Comprehensive
databases will gather all of the wind data and provide site-specific
information on wind conditions before on- and offshore wind turbines are
created. The WINDSCANNER facility aspires to improve the modelling of
local flow conditions, streamline wind turbines and reduce the costs of
wind production.