Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
  Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben
Zeitschriftenartikel

Data-Driven Model of the Power-Grid Frequency Dynamics

MPG-Autoren
/persons/resource/persons173689

Timme,  Marc
Max Planck Research Group Network Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

/persons/resource/persons191488

Schäfer,  Benjamin
Department of Dynamics of Complex Fluids, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (beschränkter Zugriff)
Für Ihren IP-Bereich sind aktuell keine Volltexte freigegeben.
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PuRe verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Gorjao, L. R., Anvari, M., Kantz, H., Beck, C., Witthaut, D., Timme, M., et al. (2020). Data-Driven Model of the Power-Grid Frequency Dynamics. IEEE Access, 8, 43082-43097. doi:10.1109/ACCESS.2020.2967834.


Zitierlink: https://hdl.handle.net/21.11116/0000-0008-B5C5-D
Zusammenfassung
The energy system is rapidly changing to accommodate the increasing number of renewable
generators and the general transition towards a more sustainable future. Simultaneously, business models
and market designs evolve, affecting power-grid operation and power-grid frequency. Problems raised by
this ongoing transition are increasingly addressed by transdisciplinary research approaches, ranging from
purely mathematical modelling to applied case studies. These approaches require a stochastic description of
consumer behaviour, fluctuations by renewables, market rules, and how they influence the stability of the
power-grid frequency. Here, we introduce an easy-to-use, data-driven, stochastic model for the power-grid
frequency and demonstrate how it reproduces key characteristics of the observed statistics of the Continental
European and British power grids. Using data analysis tools and a Fokker–Planck approach, we estimate
parameters of our deterministic and stochastic model. We offer executable code and guidelines on how to
use the model on any power grid for various mathematical or engineering applications.