Quantifying electric vehicle-grid-integration potential by behavior heterogeneity

By 2030, surging electric vehicle (EV) adoption rates approaching 30% threaten to overload 23% of urban distribution transformers beyond safe operation thresholds during evening peak periods. While coordinated charging strategies demonstrate technical feasibility for peak load shifting, the behavioral economics mechanism governing user participation remains poorly understood. This study develops a novel methodology for assessing user participation potential in vehicle-grid integration (VGI) systems, with its operational validity empirically demonstrated through price incentive trials conducted at a large city's charging facilities. Empirical results demonstrate progressive enhancement of user participation willingness from 28.05% to 31.37% and 34.88% as incentive levels increase from 0.1 to 0.3 Chinese Yuan per kilowatt-hour (CNY/kW h). When subsidies remain below 50% of total charging costs, measured willingness reaches 54%-58%, resulting in a peak-valley difference of 7.70% in the aggregated EV load profile—offering a critical mitigation mechanism against grid stress induced by exponential EV adoption. This work equips policymakers with charging behaviorally optimized pricing frameworks and validated scalability projections, establishing decision-support tools for cost-effective VGI and the integration of sustainable energy technologies in urban energy systems.