A Stochastic Programming Model for Depot Charging Capacity Assessment of Electric Commercial Fleets Considering Operational Variabilities

The growing focus on electrifying commercial fleets reflects a crucial effort toward combating carbon emissions in transportation. However, transitioning to electric fleets poses significant challenges for depot operators and stakeholders who must decide on the size and configuration of charging infrastructure. This paper introduces a two-stage stochastic linear program, designed to determine the minimum power capacity requirements for the depot infrastructure, explicitly accounting for operational variability and uncertainties in the vehicle initial State-of-Charge and trip requirements. A set of scenarios is generated that encapsulates the operational dynamics of a commercial fleet. The model's effectiveness is validated using real-world timetable data from VIA Metropolitan Transit, a mass transit bus agency operating in San Antonio, Texas. Results highlight the sensitivity of planning problems to the fleet's operational schedule, underscoring the significance of modeling of fleet operational dynamics to accurately assess power requirements and associated costs.