Time-of-Use Pricing Enhances Vehicle-to-Grid Benefits for Power Systems and Vehicle Owners but May Undermine Decarbonization

Abstract Vehicle-to-grid (V2G) is an important flexibility management technology for lower-carbon transport and the electricity grid. However, its effectiveness relies on the temporal alignment between the price incentives and grid dynamics. To overcome the challenge of coordinating electricity pricing with V2G deployment, we integrated a Bayesian optimization framework into a unit commitment model of the 2030 Jing–Jin–Tang power grid. Results demonstrate that current static time-of-use tariffs incentivize EV fleets to discharge during midday solar peak hours. This behavior displaces zero-marginal-cost renewable generation and forces pumped storage hydropower units to absorb excess fleet discharge. Optimizing tariffs could reduce average net load, operating costs, and CO2 emissions. In summary, the synergistic interaction between V2G and dynamic pricing shows a dual effect: it reduces costs for both the grid and EV owners but, conversely, can increase CO2 emissions due to excessive EV participation. Our results demonstrate that a shift toward dynamic, carbon-aware pricing mechanisms is essential to ensure that widespread V2G deployment effectively supports decarbonization goals.

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Publication Details

Journal
Environmental Science & Technology
Published
2026-09-04
DOI
https://doi.org/10.1021/acs.est.6c03971
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00

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Time-of-Use Pricing Enhances Vehicle-to-Grid Benefits for Power Systems and Vehicle Owners but May Undermine Decarbonization

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Time-of-Use Pricing Enhances Vehicle-to-Grid Benefits for Power Systems and Vehicle Owners but May Undermine Decarbonization

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article en

Abstract

Abstract Vehicle-to-grid (V2G) is an important flexibility management technology for lower-carbon transport and the electricity grid. However, its effectiveness relies on the temporal alignment between the price incentives and grid dynamics. To overcome the challenge of coordinating electricity pricing with V2G deployment, we integrated a Bayesian optimization framework into a unit commitment model of the 2030 Jing–Jin–Tang power grid. Results demonstrate that current static time-of-use tariffs incentivize EV fleets to discharge during midday solar peak hours. This behavior displaces zero-marginal-cost renewable generation and forces pumped storage hydropower units to absorb excess fleet discharge. Optimizing tariffs could reduce average net load, operating costs, and CO2 emissions. In summary, the synergistic interaction between V2G and dynamic pricing shows a dual effect: it reduces costs for both the grid and EV owners but, conversely, can increase CO2 emissions due to excessive EV participation. Our results demonstrate that a shift toward dynamic, carbon-aware pricing mechanisms is essential to ensure that widespread V2G deployment effectively supports decarbonization goals.

Environmental Science & Technology
State Key Laboratory of Pollution Control and Resource Reuse (CN), Ford Motor Company (United Kingdom) (GB), Ford Motor Company (France) (FR), Huaneng Clean Energy Research Institute (CN), Digital Science (United States) (US), Massachusetts Institute of Technology (US), Tsinghua University (CN)
Ministry of Education of the People's Republic of China
Openalex Percentile: Top 20%
Electric Vehicles and Infrastructure
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