CC BY-NC-ND 4.0Gschwendtner, ChristineChristineGschwendtnerKnoeri, ChristofChristofKnoeriStephan, AnnegretAnnegretStephan2023-07-132023-07-132023https://doi.org/10.24406/publica-937https://publica.fraunhofer.de/handle/publica/43698410.1016/j.isci.2023.10593710.24406/publica-937Electrification is one of the main decarbonization strategies for transportation.While uncontrolled electric vehicle (EV) charging can challenge the electricity system, controlled EV charging can offer flexibility. Using an agent-based model, we simulate combinations of two elements of EV charging, plug-in behaviors and controlled-charging processes, and measure flexibility goals with four metrics: total load shift, increase in midday load, peak reduction, and flatness of the load curve. We reveal trade-offs between these flexibility goals, which indicate that the most beneficial combinations are specific to spatial areas and their flexibility goals. Furthermore, we find that controlled-charging processes show higher impact on the flexibility metrics than plug-in behaviors, particularly with high EV and charging-station diffusion, but less so in rural areas. Incentivizing beneficial combinations can increase the flexibility potential of EV charging and potentially avoid grid reinforcements.enEnergy modelingEnergy policyEnergy resourcesEnergy transportationjournal article