Uncovering the Kuramoto Model from Full-order Models of Grid-forming Inverter-based Power Networks

Olaoluwapo Ajala, Nathan Baeckeland, Sairaj Dhople, Alejandro Dominguez-Garcia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents parametric assumptions under which the classical Kuramoto model can be uncovered from full-order models of an interconnected group of gridforming inverters based on droop control, virtual synchronous machine control and/or dispatchable virtual oscillator control. The equivalence is established with reduced-order models that are derived by leveraging singular-perturbation analysis, timedomain Kron reduction of the network dynamics, and a particular control configuration that is based on the inductance-toresistance ratio of interconnecting transmission lines. Numerical results compare the phase and frequency response of the fullorder model and the reduced-order Kuramoto model.

Original languageEnglish (US)
Title of host publication60th IEEE Conference on Decision and Control, CDC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4944-4949
Number of pages6
ISBN (Electronic)9781665436595
DOIs
StatePublished - 2021
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States
Duration: Dec 13 2021Dec 17 2021

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2021-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Country/TerritoryUnited States
CityAustin
Period12/13/2112/17/21

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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