This study investigates depot charging capacity planning and charging schedule optimization for heavy-duty electric vehicle fleets, explicitly incorporating grid-aware infrastructure considerations. As fleet electrification expands, uncoordinated charging demand can intensify peak loads, increase electricity costs, and impose additional stress on power systems, underscoring the need for integrated planning approaches. A two-phase optimization framework is proposed that jointly determines depot charging infrastructure capacity and time-dependent charging schedules by accounting for peak demand charges, infrastructure installation costs, and operational expenses, while incorporating temporal fleet usage patterns and grid load conditions. A case study is conducted to evaluate optimal charger capacity portfolios and operational schedules under representative tariff structures. The results demonstrate that coordinated depot charging can substantially reduce peak demand and total system costs, including both infrastructure investment and operating expenses, compared with uncoordinated charging strategies. While scenarios with higher power charging infrastructure lead to increased peak demand charges, these impacts can be effectively mitigated through optimized scheduling. Overall, the findings highlight that grid-aware depot charging planning enhances both cost efficiency and power system resilience, providing quantitative evidence to support infrastructure investment decisions and policy design for large-scale fleet electrification. • Propose a mathematical model for depot charging management with charger sizing. • Demand-side management provides advantages for both the power grid and fleet owners. • Analyzing the effects of charger types on peak demand and total expenses. • Economic analysis shows 21%–53% operational cost savings vs conventional buses. • Lower-rate chargers are cost-effective with optimal charging plans.
Moon et al. (2026) studied this question.