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Advances in Science and Research The open-access proceedings of the European Meteorological Society (EMS)

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Adv. Sci. Res., 14, 131-138, 2017
https://doi.org/10.5194/asr-14-131-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
29 May 2017
Weather dependent estimation of continent-wide wind power generation based on spatio-temporal clustering
Bruno U. Schyska1,2, António Couto3, Lueder von Bremen1,2, Ana Estanqueiro3, and Detlev Heinemann1,2 1Institute of Physics, Energy Meteorology group, University of Oldenburg, Oldenburg, Germany
2ForWind Center for Wind Energy Research, University of Oldenburg, Oldenburg, Germany
3Laboratório Nacional de Energia e Geologia, Energy Analysis and Networks Unit, Lisboa, Portugal
Abstract. Europe is facing the challenge of increasing shares of energy from variable renewable sources. Furthermore, it is heading towards a fully integrated electricity market, i.e. a Europe-wide electricity system. The stable operation of this large-scale renewable power system requires detailed information on the amount of electricity being transmitted now and in the future. To estimate the actual amount of electricity, upscaling algorithms are applied. Those algorithms – until now – however, only exist for smaller regions (e.g. transmission zones and single wind farms). The aim of this study is to introduce a new approach to estimate Europe-wide wind power generation based on spatio-temporal clustering. We furthermore show that training the upscaling model for different prevailing weather situations allows to further reduce the number of reference sites without losing accuracy.

Citation: Schyska, B. U., Couto, A., von Bremen, L., Estanqueiro, A., and Heinemann, D.: Weather dependent estimation of continent-wide wind power generation based on spatio-temporal clustering, Adv. Sci. Res., 14, 131-138, https://doi.org/10.5194/asr-14-131-2017, 2017.
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