Abstract
The electrification of transport will significantly increase electricity demand, potentially amplifying peak loads and infrastructure requirements if charging remains uncontrolled. Conversely, Electric Vehicles can provide distributed flexibility to support renewable integration and reduce system costs. This study develops a multi-node, multi-period capacity-expansion model using PyPSA, integrating detailed hourly EV mobility and availability profiles generated with emobpy. The charging scenarios are interpreted sequentially, with SC as the near-market, low-cost first stage and V2G carrying an explicit capital-cost premium for bidirectional infrastructure as an additional capability built on top of SC. Results indicate that coordinated charging significantly influences optimal investment pathways. At 30 % participation, SC reduces total annual system costs by 1.3 % by 2050 compared to Dumb charging, mainly through lower stationary battery deployment (10 % in 2050, and up to 92 % in earlier years) and reduced renewable curtailment (13 % in 2050, and up to 48 % in earlier years). Adding bidirectional capability on top of SC lowers the 2050 system cost by a further 2.0 % (141.0 versus 144.0 billion EUR, i.e., 3.3 % versus Dumb charging), while reducing stationary battery capacity by 39.7 % and renewable curtailment by 13.9 TWh relative to SC, as EV fleets substitute part of grid-scale storage and enhance renewable utilization.