Using Partial-Charging Strategies to Adapt EV Charging Stations to Dynamic Queuing Conditions: An Agent-Based Modeling

Modern electric vehicle (EV) charging stations must increase their adaptability to dynamic demand patterns driven by users’ heterogeneous charging behaviors, which often result in high spatial–temporal fluctuations. This study develops an agent-based model to accurately evaluate the potential of partial-charging strategy in addressing this issue, taking into account the influence of drivers’ heterogeneous waiting patience. The simulating results indicate that the operational efficiency of the charging station and the level of crowding are most sensitive to changes in vehicle arrival rates and the total number of charging stations. However, individual-level heterogeneity in waiting patience emerges as the core factor preventing limitless queuing increase. Compared with other strategies, the partial-charging strategy improves the turnover of charging stations by reducing per-vehicle charging duration, allowing stations to adapt to varying charging demand conditions without capacity expansions. Setting the charging threshold at 80% state of charge allows the stations to efficiently serve twice the demand level as under full-charging strategy, while a 70% threshold may increase this adaptability by approximately 2.5 times. This study provides structured recommendations for the strategic and adaptive deployment of the partial-charging strategy in alleviating queue-related inefficiencies of charging stations.