Distributed Control and Optimization of Virtual Inertia in Power Systems

Ajay Pratap Yadav; Mohammed M. Olama; Ali Riza Ekti; Nils M. Stenvig

doi:10.1109/PESGM52009.2025.11225356

Distributed Control and Optimization of Virtual Inertia in Power Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The integration of renewable energy sources into power grids through inverter-based resources (IBRs) reduces system inertia, leading to faster frequency dynamics and potential grid instability. This paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources during system disturbances, enhancing both system stability and economic performance. Furthermore, we integrate this approach with the traditional inertia placement problem, demonstrating its suitability for existing frameworks. We validate its effectiveness in a 4-bus test system and a two-area 8-bus test system, showcasing its potential for scalable, dynamic inertia management in low-inertia grids.

Original language	English
Title of host publication	2025 IEEE Power and Energy Society General Meeting, PESGM 2025
Publisher	IEEE Computer Society
ISBN (Electronic)	9798331509958
DOIs	https://doi.org/10.1109/PESGM52009.2025.11225356
State	Published - 2025
Event	2025 IEEE Power and Energy Society General Meeting, PESGM 2025 - Austin, United States Duration: Jul 27 2025 → Jul 31 2025

Publication series

Name	IEEE Power and Energy Society General Meeting
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2025 IEEE Power and Energy Society General Meeting, PESGM 2025
Country/Territory	United States
City	Austin
Period	07/27/25 → 07/31/25

Funding

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doepublic-access-plan).

Keywords

Power system inertia
inverter-based resources
optimization
swing equation
virtual inertia

Access to Document

10.1109/PESGM52009.2025.11225356

Cite this

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title = "Distributed Control and Optimization of Virtual Inertia in Power Systems",

abstract = "The integration of renewable energy sources into power grids through inverter-based resources (IBRs) reduces system inertia, leading to faster frequency dynamics and potential grid instability. This paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources during system disturbances, enhancing both system stability and economic performance. Furthermore, we integrate this approach with the traditional inertia placement problem, demonstrating its suitability for existing frameworks. We validate its effectiveness in a 4-bus test system and a two-area 8-bus test system, showcasing its potential for scalable, dynamic inertia management in low-inertia grids.",

keywords = "Power system inertia, inverter-based resources, optimization, swing equation, virtual inertia",

author = "Yadav, \{Ajay Pratap\} and Olama, \{Mohammed M.\} and Ekti, \{Ali Riza\} and Stenvig, \{Nils M.\}",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE Power and Energy Society General Meeting, PESGM 2025 ; Conference date: 27-07-2025 Through 31-07-2025",

year = "2025",

doi = "10.1109/PESGM52009.2025.11225356",

language = "English",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2025 IEEE Power and Energy Society General Meeting, PESGM 2025",

}

Yadav, AP , Olama, MM , Ekti, AR & Stenvig, NM 2025, Distributed Control and Optimization of Virtual Inertia in Power Systems. in 2025 IEEE Power and Energy Society General Meeting, PESGM 2025. IEEE Power and Energy Society General Meeting, IEEE Computer Society, 2025 IEEE Power and Energy Society General Meeting, PESGM 2025, Austin, United States, 07/27/25. https://doi.org/10.1109/PESGM52009.2025.11225356

Distributed Control and Optimization of Virtual Inertia in Power Systems. / Yadav, Ajay Pratap ; Olama, Mohammed M.; Ekti, Ali Riza et al.
2025 IEEE Power and Energy Society General Meeting, PESGM 2025. IEEE Computer Society, 2025. (IEEE Power and Energy Society General Meeting).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Distributed Control and Optimization of Virtual Inertia in Power Systems

AU - Yadav, Ajay Pratap

AU - Olama, Mohammed M.

AU - Ekti, Ali Riza

AU - Stenvig, Nils M.

PY - 2025

Y1 - 2025

N2 - The integration of renewable energy sources into power grids through inverter-based resources (IBRs) reduces system inertia, leading to faster frequency dynamics and potential grid instability. This paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources during system disturbances, enhancing both system stability and economic performance. Furthermore, we integrate this approach with the traditional inertia placement problem, demonstrating its suitability for existing frameworks. We validate its effectiveness in a 4-bus test system and a two-area 8-bus test system, showcasing its potential for scalable, dynamic inertia management in low-inertia grids.

AB - The integration of renewable energy sources into power grids through inverter-based resources (IBRs) reduces system inertia, leading to faster frequency dynamics and potential grid instability. This paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources during system disturbances, enhancing both system stability and economic performance. Furthermore, we integrate this approach with the traditional inertia placement problem, demonstrating its suitability for existing frameworks. We validate its effectiveness in a 4-bus test system and a two-area 8-bus test system, showcasing its potential for scalable, dynamic inertia management in low-inertia grids.

KW - Power system inertia

KW - inverter-based resources

KW - optimization

KW - swing equation

KW - virtual inertia

UR - https://www.scopus.com/pages/publications/105025204109

U2 - 10.1109/PESGM52009.2025.11225356

DO - 10.1109/PESGM52009.2025.11225356

M3 - Conference contribution

AN - SCOPUS:105025204109

T3 - IEEE Power and Energy Society General Meeting

BT - 2025 IEEE Power and Energy Society General Meeting, PESGM 2025

PB - IEEE Computer Society

T2 - 2025 IEEE Power and Energy Society General Meeting, PESGM 2025

Y2 - 27 July 2025 through 31 July 2025

ER -

Distributed Control and Optimization of Virtual Inertia in Power Systems

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