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Advances in Science and Research Contributions in Applied Meteorology and Climatology
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Volume 14
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.
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

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 Bruno U. Schyska et al.
  • 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.

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