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Unlocking vehicle-to-grid potential of load shifting in China’s megacities considering comprehensive real-world behaviors

Abstract:
Global decarbonization necessitates large-scale electrification, bringing load stability challenges to urban grids. While Vehicle-to-grid (V2G) technology using private plug-in electric vehicles (P-PEVs) can balance the loads, its potential at megacity-level remains unclear due to the complexity of fine-grained, user-centric modelling. Here, we propose a Mobility and V2G Coupled (MOVC) framework, which depicts individual P-PEV travel-charge behaviors and evaluates user V2G concerns regarding willingness, compensation, and battery degradation. The framework analyzes 480,000 P-PEVs in Shenzhen, China, revealing a 2300 MW peak-shaving capacity, reducing peak-valley ratios by 73%. V2G strategies that prioritize user satisfaction hardly sacrifice the load shifting performance, but reduce battery degradation costs and compensation costs by 30-40% and 5-13% respectively. A forward-looking scenario considering fully-deployed quick charging (QC) in four China’s megacities reveals 0%-12% lower peak-valley ratios with more inequal V2G scheduling (4%-95% higher standard deviation). This study enlightens megacity-level V2G potential evaluations and their policy-making considering real-world behaviors.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41467-025-65073-8

Authors

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Role:
Author
ORCID:
0009-0007-0594-4106
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Sub department:
Engineering Science
Role:
Author
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Role:
Author
ORCID:
0000-0001-5249-432X


Publisher:
Nature Research
Journal:
Nature Communications More from this journal
Volume:
16
Issue:
1
Article number:
10087
Publication date:
2025-11-18
Acceptance date:
2025-10-07
DOI:
EISSN:
2041-1723
ISSN:
2041-1723


Language:
English
Pubs id:
2330159
UUID:
uuid_61ef6806-d64a-4161-9cb0-af097001b36d
Local pid:
pubs:2330159
Source identifiers:
3483485
Deposit date:
2025-11-18
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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