Open database analysis of scaling and spatio-temporal properties of power grid frequencies

Leonardo Rydin Gorjão, Richard Jumar, Heiko Maass, Veit Hagenmeyer, G. Cigdem Yalcin, Johannes Kruse, Marc Timme, Christian Beck, Dirk Witthaut and Benjamin Schäfer ()
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Leonardo Rydin Gorjão: Forschungszentrum Jülich, Institute for Energy and Climate Research-Systems Analysis and Technology Evaluation (IEK-STE)
Richard Jumar: Institute for Automation and Applied Informatics
Heiko Maass: Institute for Automation and Applied Informatics
Veit Hagenmeyer: Institute for Automation and Applied Informatics
G. Cigdem Yalcin: Istanbul University
Johannes Kruse: Forschungszentrum Jülich, Institute for Energy and Climate Research-Systems Analysis and Technology Evaluation (IEK-STE)
Marc Timme: Technical University of Dresden
Christian Beck: Queen Mary University of London
Dirk Witthaut: Forschungszentrum Jülich, Institute for Energy and Climate Research-Systems Analysis and Technology Evaluation (IEK-STE)
Benjamin Schäfer: Queen Mary University of London

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract The electrical energy system has attracted much attention from an increasingly diverse research community. Many theoretical predictions have been made, from scaling laws of fluctuations to propagation velocities of disturbances. However, to validate any theory, empirical data from large-scale power systems are necessary but are rarely shared openly. Here, we analyse an open database of measurements of electric power grid frequencies across 17 locations in 12 synchronous areas on three continents. The power grid frequency is of particular interest, as it indicates the balance of supply and demand and carries information on deterministic, stochastic, and control influences. We perform a broad analysis of the recorded data, compare different synchronous areas and validate a previously conjectured scaling law. Furthermore, we show how fluctuations change from local independent oscillations to a homogeneous bulk behaviour. Overall, the presented open database and analyses constitute a step towards more shared, collaborative energy research.

Date: 2020
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DOI: 10.1038/s41467-020-19732-7

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