Simulation study finds time-of-use vehicle-to-grid pricing lowers power system costs but increases emissions, highlighting the necessity of dynamic carbon-aware tariffs.
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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Tian et al. (2026) studied this question.
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