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Article

Modeling of the German Wind Power Production with High Spatiotemporal Resolution

1
Department of Bioenergy, Helmholtz Centre for Environmental Research GmbH—UFZ, Permoserstraße 15, 04318 Leipzig, Germany
2
Bioenergy Systems Department, DBFZ Deutsches Biomasseforschungszentrum gGmbH, Torgauer Str. 116, 04347 Leipzig, Germany
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Kainz and Luis Ramirez Camargo
ISPRS Int. J. Geo-Inf. 2021, 10(2), 104; https://doi.org/10.3390/ijgi10020104
Received: 21 December 2020 / Revised: 10 February 2021 / Accepted: 14 February 2021 / Published: 23 February 2021
(This article belongs to the Collection Spatial and Temporal Modelling of Renewable Energy Systems)
Wind power has risen continuously over the last 20 years and covered almost 25% of the total German power provision in 2019. To investigate the effects and challenges of increasing wind power on energy systems, spatiotemporally disaggregated data on the electricity production from wind turbines are often required. The lack of freely accessible feed-in time series from onshore turbines, e.g., due to data protection regulations, makes it necessary to determine the power generation for a certain region and period with the help of numerical simulations using publicly available plant and weather data. For this, a new approach is used for the wind power model which utilizes a sixth-order polynomial for the specific power curve of a turbine. After model validation with measured data from a single wind turbine, the simulations are carried out for an ensemble of 25,835 onshore turbines to determine the German wind power production for 2016. The resulting hourly resolved data are aggregated into a time series with daily resolution and compared with measured feed-in data of entire Germany which show a high degree of agreement. Such electricity generation data from onshore turbines can be applied to optimize and monitor renewable power systems on various spatiotemporal scales. View Full-Text
Keywords: wind power; satellite-based weather data; spatiotemporal modeling; power generation wind power; satellite-based weather data; spatiotemporal modeling; power generation
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MDPI and ACS Style

Lehneis, R.; Manske, D.; Thrän, D. Modeling of the German Wind Power Production with High Spatiotemporal Resolution. ISPRS Int. J. Geo-Inf. 2021, 10, 104. https://doi.org/10.3390/ijgi10020104

AMA Style

Lehneis R, Manske D, Thrän D. Modeling of the German Wind Power Production with High Spatiotemporal Resolution. ISPRS International Journal of Geo-Information. 2021; 10(2):104. https://doi.org/10.3390/ijgi10020104

Chicago/Turabian Style

Lehneis, Reinhold, David Manske, and Daniela Thrän. 2021. "Modeling of the German Wind Power Production with High Spatiotemporal Resolution" ISPRS International Journal of Geo-Information 10, no. 2: 104. https://doi.org/10.3390/ijgi10020104

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