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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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WES | Articles | Volume 4, issue 4
Wind Energ. Sci., 4, 563–580, 2019
https://doi.org/10.5194/wes-4-563-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Wind Energ. Sci., 4, 563–580, 2019
https://doi.org/10.5194/wes-4-563-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 18 Oct 2019

Research article | 18 Oct 2019

Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems

Markus Sommerfeld et al.
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Markus Sommerfeld on behalf of the Authors (30 Jun 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (21 Aug 2019) by Jakob Mann
RR by Rogier Floors (30 Aug 2019)
ED: Publish subject to technical corrections (06 Sep 2019) by Jakob Mann
ED: Publish subject to technical corrections (06 Sep 2019) by Jakob Mann(Chief Editor)
AR by Markus Sommerfeld on behalf of the Authors (12 Sep 2019)  Author's response    Manuscript
Publications Copernicus
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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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