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Weber J, Reyers M, Beck C, Timme M, Pinto JG, Witthaut D, Schäfer B. Wind Power Persistence Characterized by Superstatistics. Sci Rep 2019; 9:19971. [PMID: 31882778 PMCID: PMC6934744 DOI: 10.1038/s41598-019-56286-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 11/21/2019] [Indexed: 11/18/2022] Open
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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Affiliation(s)
- Juliane Weber
- Forschungszentrum Jülich, Institute for Energy and Climate Research - Systems Analysis and Technology Evaluation (IEK-STE), 52428, Jülich, Germany
- Institute for Theoretical Physics, University of Cologne, Köln, 50937, Germany
| | - Mark Reyers
- Institute for Geophysics and Meteorology, University of Cologne, Köln, 50937, Germany
| | - Christian Beck
- Queen Mary University of London, School of Mathematical Sciences, Mile End Road, London, E1 4NS, UK
| | - Marc Timme
- Chair for Network Dynamics, Center for Advancing Electronics Dresden (cfaed) and Institute for Theoretical Physics, Technical University of Dresden, 01062, Dresden, Germany
| | - Joaquim G Pinto
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Dirk Witthaut
- Forschungszentrum Jülich, Institute for Energy and Climate Research - Systems Analysis and Technology Evaluation (IEK-STE), 52428, Jülich, Germany.
- Institute for Theoretical Physics, University of Cologne, Köln, 50937, Germany.
| | - Benjamin Schäfer
- Queen Mary University of London, School of Mathematical Sciences, Mile End Road, London, E1 4NS, UK.
- Chair for Network Dynamics, Center for Advancing Electronics Dresden (cfaed) and Institute for Theoretical Physics, Technical University of Dresden, 01062, Dresden, Germany.
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Aghamohammadi C, Crutchfield JP. Minimum memory for generating rare events. Phys Rev E 2017; 95:032101. [PMID: 28415193 DOI: 10.1103/physreve.95.032101] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Indexed: 11/07/2022]
Abstract
We classify the rare events of structured, memoryful stochastic processes and use this to analyze sequential and parallel generators for these events. Given a stochastic process, we introduce a method to construct a process whose typical realizations are a given process' rare events. This leads to an expression for the minimum memory required to generate rare events. We then show that the recently discovered classical-quantum ambiguity of simplicity also occurs when comparing the structure of process fluctuations.
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Affiliation(s)
- Cina Aghamohammadi
- Complexity Sciences Center and Department of Physics, University of California at Davis, One Shields Avenue, Davis, California 95616, USA
| | - James P Crutchfield
- Complexity Sciences Center and Department of Physics, University of California at Davis, One Shields Avenue, Davis, California 95616, USA
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