Emissions reduction potential and feasibility of vehicle-to-grid for Beijing’s future electric vehicles

<h2>Summary</h2> Electric vehicles (EVs) offer significant potential to reduce greenhouse gas (GHG) emissions from road transport. However, nighttime charging increases peak demand and thermal power reliance. This study evaluates vehicle-to-grid (V2G) as a solution by integrating GPS-based EV travel data with hourly grid modeling for 2 million EVs in Beijing. Results show V2G boosts renewable energy use in charging to 66%, up from under 4% in uncoordinated charging. V2G cuts vehicle uncoordinated charging emissions by 20.6% and reduces the grid's GHG footprint by replacing thermal power with discharging electricity. Commuter vehicles and the summer months offer the highest V2G emissions reduction potential. The study finds battery degradation manageable and highlights synergies between V2G, renewable capacity expansion, and economic incentives, while emphasizing the need for robust infrastructure and local grid networks to support large-scale EV adoption. This approach therefore offers a promising pathway to accelerate sustainable energy solutions amid increasing vehicle electrification and renewable integration.

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Publication Details

Journal
Cell Reports Physical Science
Published
2025-05-30
DOI
https://doi.org/10.1016/j.xcrp.2025.102616
Citations
4
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
2.92

Funders

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article

Emissions reduction potential and feasibility of vehicle-to-grid for Beijing’s future electric vehicles

Bowen Tian, Hongyi Wei, Ye Wu, Yifan Wen et al.
4 citations
Cell Reports Physical Science
Electric Vehicles and Infrastructure
2.92
article

Emissions reduction potential and feasibility of vehicle-to-grid for Beijing’s future electric vehicles

Bowen Tian, Hongyi Wei, Ye Wu, Yifan Wen, Ning Zhang, Haiyang Jiang, Jiahui Chen, Shaojun Zhang, Yinan Zhao, Jiaxin Xu
article en
4 citations

Abstract

<h2>Summary</h2> Electric vehicles (EVs) offer significant potential to reduce greenhouse gas (GHG) emissions from road transport. However, nighttime charging increases peak demand and thermal power reliance. This study evaluates vehicle-to-grid (V2G) as a solution by integrating GPS-based EV travel data with hourly grid modeling for 2 million EVs in Beijing. Results show V2G boosts renewable energy use in charging to 66%, up from under 4% in uncoordinated charging. V2G cuts vehicle uncoordinated charging emissions by 20.6% and reduces the grid's GHG footprint by replacing thermal power with discharging electricity. Commuter vehicles and the summer months offer the highest V2G emissions reduction potential. The study finds battery degradation manageable and highlights synergies between V2G, renewable capacity expansion, and economic incentives, while emphasizing the need for robust infrastructure and local grid networks to support large-scale EV adoption. This approach therefore offers a promising pathway to accelerate sustainable energy solutions amid increasing vehicle electrification and renewable integration.

Cell Reports Physical ScienceVol. 6(6)
North China Electric Power University (CN), University of Michigan (US), Tsinghua University (CN)
National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 9%
Electric Vehicles and Infrastructure
2.92
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