A Universal Grid-forming Inverter Model and Simulation-based Characterization Across Timescales

D. Ramasubramanian, E. Farantatos, O. Ajala, S. Dhople, B. Johnson

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

1 Scopus citations

Abstract

The evolution of the power grid has given rise to a variety of innovations in inverter control architectures. Among these advances, a class of controllers has emerged with the aim of enabling 100% inverter-based grids and these are known as grid-forming methods. Since these strategies are still under active development, well validated models are needed by equipment manufacturers as well as system planners and operators. In particular, a system operator may be unable to determine specifications and services that are required from grid forming devices without having the ability to represent them in a simulation environment with trusted models. A universal grid forming model that is portable across multiple simulation domains will be valuable in addressing this issue. In this paper, we develop a practical implementation of such a model that has the ability to represent four different grid-forming methods in a variety of simulation software packages while accurately capturing dynamics across from microsecond to millisecond timescales.

Original languageEnglish (US)
Title of host publicationProceedings of the 56th Annual Hawaii International Conference on System Sciences, HICSS 2023
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages2631-2640
Number of pages10
ISBN (Electronic)9780998133164
StatePublished - 2023
Event56th Annual Hawaii International Conference on System Sciences, HICSS 2023 - Virtual, Online, United States
Duration: Jan 3 2023Jan 6 2023

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2023-January
ISSN (Print)1530-1605

Conference

Conference56th Annual Hawaii International Conference on System Sciences, HICSS 2023
Country/TerritoryUnited States
CityVirtual, Online
Period1/3/231/6/23

Bibliographical note

Funding Information:
This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Numbers EE0009025 and EE0002437. The views expressed herein do not necessarily represent the views of the U.S. Department of Energy or the United States Government.

Publisher Copyright:
© 2023 IEEE Computer Society. All rights reserved.

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