A system-level sustainability assessment of electric vehicle-based demand flexibility for reducing gas-backed peak electricity demand

Demand flexibility from electric vehicles (EVs) is a well-established concept, but its combined behavioural, economic, and environmental value remains context dependent. The proposed methodology presents a system-level sustainability assessment of EV-based demand flexibility for reducing gas-backed peak electricity demand, using the UK electricity system as an empirical scenario. The framework combines probabilistic EV readiness modelling, incentive-responsive participation, peak-load reduction, grid cost savings, and lifecycle CO2e accounting. Using March 2025 UK demand data and projected long-term EV flexibility assumptions, the model estimates a conditional system-level reduction potential of approximately 18–27% in residual gas-backed peak demand across the evaluated technological-capability scenarios. This range is contingent on the specified behavioural-participation and incentive-response assumptions and adequate local network hosting capacity, and should not be interpreted as an immediately achievable UK-system reduction. The findings indicate how EV-based demand flexibility can contribute to peak-load reduction, grid cost efficiency, and lifecycle emissions mitigation under the specified behavioural, incentive, technological, and network-hosting assumptions. The proposed framework offers a scalable approach for evaluating the sustainability impact of EV integration in future low-carbon energy systems. Developed a behaviour-aware, simulation-based ETM-enabled V2G assessment framework.Estimated conditional residual natural-gas peak-demand reduction potential of approximately 18–27% under the specified scenarios.Integrated behavioral, operational, environmental, and economic evaluation.Demonstrated lifecycle CO₂e mitigation during evening peak-demand windows.Achieved positive net grid cost savings using selective EV incentive dispatch. Developed a behaviour-aware, simulation-based ETM-enabled V2G assessment framework. Estimated conditional residual natural-gas peak-demand reduction potential of approximately 18–27% under the specified scenarios. Integrated behavioral, operational, environmental, and economic evaluation. Demonstrated lifecycle CO₂e mitigation during evening peak-demand windows. Achieved positive net grid cost savings using selective EV incentive dispatch.