Bidirectional charging (V2G) can reduce local distribution-grid peaks, but its value depends on how much flexibility is actually

available when the network is constrained. This paper presents an integrated assessment framework that combines a spatially

explicit Urban Digital Twin, a behavioural participation model, and low-voltage grid simulation. Representative mobility data

are embedded with urban-model information to generate a synthetic population with building- and household-level mobility

attributes. A Random Utility Model translates contract attributes, including guaranteed driving range, minimum plug-in dura-

tion, and remuneration, into household-specific participation probabilities. An event-based plug-in model then converts these

probabilities into vehicle connection, charging, and discharging profiles.

The resulting profiles are evaluated in winter scenarios with different V2G participation rates, charging-point and heat-pump

penetration levels, and heat-pump operating patterns. The analysis quantifies impacts on transformer loading, line utilisation,

voltage-related constraints, and the present value of grid-reinforcement and flexibility costs. The results show that V2G reduces

the most critical peaks when participating vehicles are connected during periods of coincident EV and heat-pump demand. Low

participation or short connection windows, however, sharply limits the realised benefit even when the installed battery capacity

is unchanged. Higher compensation increases flexibility costs, while the additional reduction in reinforcement needs remains

limited. V2G therefore provides the greatest value when it is targeted at locally constrained feeders and evaluated using realistic

participation and availability patterns rather than technical potential alone.