Planning resilient electric bus operations in cold regions: An agent-based simulation–optimization framework

The transition to electric transit bus fleets in cold-climate cities requires a comprehensive understanding of how charging strategies, extreme temperatures, and grid constraints influence energy demand and operating costs. This study presents a novel agent-based simulation and optimization framework that generates realistic operational scenarios for electric bus fleets by integrating vehicle dynamics, energy consumption, weather variability, and charging strategies. The framework identifies the minimum feasible fleet size and charger configuration required to meet operational constraints and determines cost-optimal charging schedules. A case study in Quebec City, Canada, evaluates two charging strategies (slow and fast) under mild and winter conditions. Results show that winter increases energy demand by up to 30%, requiring additional vehicles and chargers to sustain service reliability. While fast charging reduces upfront investment, its high contracted power costs make it more expensive over time. On the other hand, slow charging is more capital-intensive but yields lower operational costs and smoother grid integration. In this context, the developed framework supports climate-aware, economically robust planning for transit agency fleet electrification.