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

被引:0
作者
Leonardo Rydin Gorjão
Richard Jumar
Heiko Maass
Veit Hagenmeyer
G. Cigdem Yalcin
Johannes Kruse
Marc Timme
Christian Beck
Dirk Witthaut
Benjamin Schäfer
机构
[1] Forschungszentrum Jülich,Institute for Theoretical Physics
[2] Institute for Energy and Climate Research-Systems Analysis and Technology Evaluation (IEK-STE),Karlsruhe Institute of Technology
[3] University of Cologne,Department of Physics
[4] Institute for Automation and Applied Informatics,Network Dynamics, Center for Advancing Electronics Dresden (cfaed) and Institute for Theoretical Physics
[5] Istanbul University,School of Mathematical Sciences
[6] Technical University of Dresden,undefined
[7] Queen Mary University of London,undefined
来源
Nature Communications | / 11卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
相关论文
共 50 条
[41]   Language bindings for spatio-temporal database programming in tripod [J].
Griffiths, T ;
Paton, NW ;
Fernandes, AAA ;
Jeong, SH ;
Djafri, N .
KEY TECHNOLOGIES FOR DATA MANAGEMENT, 2004, 3112 :216-233
[42]   Storing Spatio-Temporal Data in XML Native Database [J].
Liu, Xiaohua ;
Wan, Youchuan .
2010 2ND INTERNATIONAL WORKSHOP ON DATABASE TECHNOLOGY AND APPLICATIONS PROCEEDINGS (DBTA), 2010,
[43]   Initial spatio-temporal domain expansion of the Modelfest database [J].
Carney, Thom ;
Mozaffari, Sahar ;
Sun, Sean ;
Johnson, Ryan .
HUMAN VISION AND ELECTRONIC IMAGING XVIII, 2013, 8651
[44]   A design support environment for spatio-temporal database applications [J].
Story, PA ;
Worboys, MF .
SPATIAL INFORMATION THEORY: A THEORETICAL BASIS FOR GIS, 1995, 988 :413-430
[45]   A spatio-temporal binary grid-based clustering model for seismicity analysis [J].
Vijay, Rahul Kumar ;
Nanda, Satyasai Jagannath ;
Sharma, Ashish .
PATTERN ANALYSIS AND APPLICATIONS, 2024, 27 (01)
[46]   Application of Grid Management in Spatio-temporal Prediction of Crime [J].
Zhang Tianyi ;
Ran Yibing ;
Wei Dong .
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021), 2021, :2745-2749
[47]   Spatio-temporal properties of letter crowding [J].
Chung, Susana T. L. .
JOURNAL OF VISION, 2016, 16 (06)
[48]   Scaling properties of the spatio-temporal distribution of earthquakes: a multifractal approach applied to a Californian catalogue [J].
Godano, C ;
Tosi, P ;
Derubeis, V ;
Augliera, P .
GEOPHYSICAL JOURNAL INTERNATIONAL, 1999, 136 (01) :99-108
[49]   Spatio-temporal properties of multipartite entanglement [J].
Patera, Giuseppe ;
Kolobov, Mikhail I. .
QUANTUM OPTICS, 2010, 7727
[50]   Fluid Analysis of Spatio-Temporal Properties of Agents in a Population Model [J].
Bortolussi, Luca ;
Tschaikowski, Max .
Analytical and Stochastic Modelling Techniques and Applications, 2016, 9845 :92-106