Flexibility estimation of electric vehicles and its impact on the future power grid

Wu, J; Li, L; Zhang, J; Xiao, B

Flexibility estimation of electric vehicles and its impact on the future power grid

Wu, J Li, L

Zhang, J Xiao, B

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Publisher:: ELSEVIER SCI LTD
Publication Type:: Journal Article
Citation:: International Journal of Electrical Power and Energy Systems, 2025, 164
Issue Date:: 2025-03-01

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Field	Value	Language
dc.contributor.author	Wu, J
dc.contributor.author	Li, L https://orcid.org/0000-0001-8485-2216
dc.contributor.author	Zhang, J
dc.contributor.author	Xiao, B
dc.date.accessioned	2025-07-16T05:22:31Z
dc.date.available	2025-07-16T05:22:31Z
dc.date.issued	2025-03-01
dc.identifier.citation	International Journal of Electrical Power and Energy Systems, 2025, 164
dc.identifier.issn	0142-0615
dc.identifier.issn	1879-3517
dc.identifier.uri	http://hdl.handle.net/10453/188449
dc.description.abstract	Electric vehicles offer environmental benefits but pose challenges to power grids during peak demand. This study introduces a method to optimize electric vehicle charging and incorporate vehicle-to-grid technology, aiming to minimize electricity costs and electric vehicle loads during peak periods. Two models are developed to evaluate electric vehicle owners’ willingness to participate in both non-vehicle-to-grid and vehicle-to-grid scenarios, providing insights into future peak demand increases and potential reductions through optimization. A case study in Texas, USA, utilizing data from the Pecan Street database, reveals that by 2030, the increase in peak electric vehicle charging demand could exceed the current levels by over 4.7 times. This surge is up to 3.16% of the total electricity demand in Texas. However, with the implementation of the proposed optimization methods, electric vehicles could potentially feed about 747 MWh of energy back into the grid, effectively transforming them from energy consumers to suppliers during high-demand periods. This demonstrates the crucial role that electric vehicles, coupled with strategic charging and vehicle-to-grid technologies, can play in not only mitigating emissions but also in enhancing grid stability and efficiency.
dc.language	English
dc.publisher	ELSEVIER SCI LTD
dc.relation.ispartof	International Journal of Electrical Power and Energy Systems
dc.relation.isbasedon	10.1016/j.ijepes.2024.110435
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Energy
dc.subject.classification	4008 Electrical engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4601 Applied computing
dc.title	Flexibility estimation of electric vehicles and its impact on the future power grid
dc.type	Journal Article
utslib.citation.volume	164
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2025-07-16T05:22:29Z
pubs.publication-status	Published
pubs.volume	164

Abstract:

Electric vehicles offer environmental benefits but pose challenges to power grids during peak demand. This study introduces a method to optimize electric vehicle charging and incorporate vehicle-to-grid technology, aiming to minimize electricity costs and electric vehicle loads during peak periods. Two models are developed to evaluate electric vehicle owners’ willingness to participate in both non-vehicle-to-grid and vehicle-to-grid scenarios, providing insights into future peak demand increases and potential reductions through optimization. A case study in Texas, USA, utilizing data from the Pecan Street database, reveals that by 2030, the increase in peak electric vehicle charging demand could exceed the current levels by over 4.7 times. This surge is up to 3.16% of the total electricity demand in Texas. However, with the implementation of the proposed optimization methods, electric vehicles could potentially feed about 747 MWh of energy back into the grid, effectively transforming them from energy consumers to suppliers during high-demand periods. This demonstrates the crucial role that electric vehicles, coupled with strategic charging and vehicle-to-grid technologies, can play in not only mitigating emissions but also in enhancing grid stability and efficiency.

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http://hdl.handle.net/10453/188449