Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.3390/ijgi11020090 |
Lizenz  |
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| Titel (primär) | Spatiotemporal modeling of the electricity production from variable renewable energies in Germany |
| Autor | Lehneis, R.
; Manske, D.
; Schinkel, B.; Thrän, D. |
| Quelle | ISPRS International Journal of Geo-Information |
| Erscheinungsjahr | 2022 |
| Department | BIOENERGIE |
| Band/Volume | 11 |
| Heft | 2 |
| Seite von | art. 90 |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Keywords | satellite-based weather data; wind power; photovoltaics; power generation |
| Abstract | In recent years, electricity production from wind turbines and photovoltaic systems has grown significantly in Germany. To determine the multiple impacts of rising variable renewable energies on an increasingly decentralized power supply, spatially and temporally resolved data on the power generation are necessary or, at least, very helpful. Because of extensive data protection regulations in Germany, especially for smaller operators of renewable power plants, such detailed data are not freely accessible. In order to fill this information gap, simulation models employing publicly available plant and weather data can be used. The numerical simulations are performed for the year 2016 and consider an ensemble of almost 1.64 million variable renewable power plants in Germany. The obtained time series achieve a high agreement with measured feed-in patterns over the investigated year. Such disaggregated power generation data are very advantageous to analyze the energy transition in Germany on a spatiotemporally resolved scale. In addition, this study also derives meaningful key figures for such an analysis and presents the generated results as detailed maps at county level. To the best of our knowledge, such highly resolved electricity data of variable renewables for the entire German region have never been shown before. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=25680 |
| Lehneis, R., Manske, D., Schinkel, B., Thrän, D. (2022): Spatiotemporal modeling of the electricity production from variable renewable energies in Germany ISPRS Int. J. Geo-Inf. 11 (2), art. 90 10.3390/ijgi11020090 |
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