Journal Article

FZJ-2020-00073

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Wind power persistence characterized by superstatistics

Weber, J. ; Reyers, M. ; Beck, C. ; Timme, M. ; Pinto, J. G. ; Witthaut, D. (Corresponding author)FZJ* ; Schäfer, B.

2019
Macmillan Publishers Limited, part of Springer Nature [London]

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Please use a persistent id in citations: http://hdl.handle.net/2128/24324  doi:10.1038/s41598-019-56286-1

Abstract: Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or of low wind therefore essentially define the necessary amount of storage to balance the power system. While the general statistics of wind velocities have been studied extensively, persistence (waiting) time statistics of wind is far from well understood. Here, we investigate the statistics of both high- and low-wind persistence. We find heavy tails and explain them as a superposition of different wind conditions, requiring q-exponential distributions instead of exponential distributions. Persistent wind conditions are not necessarily caused by stationary atmospheric circulation patterns nor by recurring individual weather types but may emerge as a combination of multiple weather types and circulation patterns. This also leads to Fréchet instead of Gumbel extreme value statistics. Understanding wind persistence statistically and synoptically may help to ensure a reliable and economically feasible future energy system, which uses a high share of wind generation.

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Contributing Institute(s):

1. Systemforschung und Technologische Entwicklung (IEK-STE)

Research Program(s):

1. 153 - Assessment of Energy Systems – Addressing Issues of Energy Efficiency and Energy Security (POF3-153) (POF3-153)
2. CoNDyNet - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (PIK_082017) (PIK_082017)
3. CoNDyNet 2 - Kollektive Nichtlineare Dynamik Komplexer Stromnetze (BMBF-03EK3055B) (BMBF-03EK3055B)
4. VH-NG-1025 - Helmholtz Young Investigators Group "Efficiency, Emergence and Economics of future supply networks" (VH-NG-1025_20112014) (VH-NG-1025_20112014)

Appears in the scientific report 2019

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