Data-Driven Model of the Power-Grid Frequency Dynamics

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Leonardo Rydin Gorjao - , Jülich Research Centre, University of Cologne (Author)
  • Mehrnaz Anvari - , Max-Planck-Institute for the Physics of Complex Systems (Author)
  • Holger Kantz - , Max-Planck-Institute for the Physics of Complex Systems (Author)
  • Christian Beck - , Queen Mary University of London (Author)
  • Dirk Witthaut - , Jülich Research Centre, University of Cologne (Author)
  • Marc Timme - , Chair of Network Dynamics (cfaed), Max Planck Institute for Dynamics and Self-Organization (Author)
  • Benjamin Schafer - , Chair of Network Dynamics (cfaed), Queen Mary University of London, Max Planck Institute for Dynamics and Self-Organization (Author)

Abstract

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.

Details

Original languageEnglish
Pages (from-to)43082-43097
Number of pages16
JournalIEEE access
Volume8
Publication statusPublished - 2020
Peer-reviewedYes

External IDs

ORCID /0000-0002-5956-3137/work/142242413

Keywords

Keywords

  • control systems, data-driven model, Fokker-Planck equation, parameter estimation, power-grid frequency, Stochastic modelling, swing equation

Library keywords