Small-Signal Stability Support From Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems

Lizhi Ding, Yuhua Du, Xiaonan Lu, Shuan Dong, Andy Hoke, Jin Tan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The growth of inverter-based resources (IBRs) in modern power systems can challenge system stability since they do not natively provide inertia, prompting a need to develop new methods to address the potential instabilities. In this paper, a dynamically configurable grid-forming (GFM) and grid-following (GFL) control is proposed, which enables inverters to flexibly transition to support system needs. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small-signal stability margin. In addition, a holistic and detailed small-signal model for a distribution feeder that captures the dynamics from both synchronous generators (SGs) and IBRs is also derived and used to evaluate the effectiveness of the proposed GFM/GFL controls to augment the system small-signal stability margin. Case studies with varying levels of IBRs were implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publication2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728193878
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States
Duration: 9 Oct 202213 Oct 2022

Publication series

Name2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022

Conference

Conference2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/TerritoryUnited States
CityDetroit
Period9/10/2213/10/22

Keywords

  • grid-following control
  • grid-forming control
  • operation mode transition
  • small-signal stability analysis

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