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. • Integrates agent-based simulation with optimization for fleet planning. • Winter conditions increase energy demand by 30% and fleet size by 4%. • Fast charging creates steep 20 MW power peaks, increasing OPEX. • Slow charging lowers the 10-year total cost of ownership by 7%. • Cold climates require up to 35% more chargers to sustain reliability.
Manzolli et al. (Wed,) studied this question.