Articles | Volume 4, issue 4
https://doi.org/10.5194/wes-4-563-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-4-563-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Oct 2019
Research article |
| 18 Oct 2019
| 18 Oct 2019
Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems
Institute for Integrated Energy Systems, University of Victoria, British Columbia, Canada
Martin Dörenkämper
Fraunhofer Institute for Wind Energy Systems, Oldenburg, Germany
Gerald Steinfeld
Institute of Physics-Energy Meteorology, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
Curran Crawford
Institute for Integrated Energy Systems, University of Victoria, British Columbia, Canada
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Short summary
Airborne wind energy systems aim to operate at altitudes above conventional wind turbines where reliable high-resolution wind data are scarce. Wind measurements and computational simulations both have advantages and disadvantages when assessing the wind resource at such heights. This article investigates whether assimilating measurements into the model generates a more accurate wind data set up to 1100 m. These wind data sets are used to estimate optimal AWES operating altitudes and power.
Airborne wind energy systems aim to operate at altitudes above conventional wind turbines where...
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