Abstract Manager

Wildfire evacuations increasingly pose challenges for communities, particularly as electric vehicle (EV) adoption grows and strains existing infrastructure. This study developed a simple agent-based model (ABM) to simulate EV charging behaviour during an emergency evacuation scenario in Canmore, Alberta. Through a stated preference survey, 1,371 responses were collected from wildfire-prone populations in Alberta and British Columbia over the summer of 2023. Stated EV user behaviours regarding initial charging actions were incorporated from the survey into the model. To assess spatiotemporal patterns, the ABM simulated vehicle movements, charging station usage, and electricity demand over a 24-hour evacuation period, based on real-world charging infrastructure and user-reported behaviours. Results found that charging station congestion and electricity demand sharply peaked within the first few hours of evacuation, with imbalanced utilization between stations and significant delays for users with non-adaptive charging behaviours. Scenario testing further revealed that increased charging speeds at stations and expanded assumptions of time-minimizing behaviour from all station-charging users did not result in significant differences in patterns. However, increased EV adoption would substantially heighten strain on the electrical grid, emphasizing the need for coordinated infrastructure upgrades. Strategies such as enhancing access to fast charging stations, distributing infrastructure more evenly, and enabling real-time information sharing can significantly reduce queuing delays and improve evacuation efficiency.