Optimization Model for Electric Vehicle (EV) Fleet Charging Location Assignment - Gonzalo Martinez Medina; Krystel K. Castillo-Villar; Omar Abbaas (IEEE Access)
This paper addresses a critical challenge that utility providers face as commercial electric vehicle (EV) fleets rapidly expand. Specifically, it focuses on optimizing charging infrastructure for medium- and heavy-duty electric vehicles while managing constrained grid capacity. Businesses’ increasing adoption of mid-size to heavy EV fleets has created a significant surge in electricity demand, often exceeding the local grid’s ability to support charging at vehicles’ base locations. Supply chain constraints that hinder timely infrastructure upgrades exacerbate this mismatch between demand and capacity. We present an optimization model for EV fleet charging location assignment that tackles this issue. Our approach considers multiple commercial fleet operators, each with a set of base locations for their vehicles. The model accounts for limited charging capacity at these bases and proposes strategically placing charging hubs in areas with excess grid capacity. We incorporate a flexible incentive framework into our model to encourage the use of these hubs and other non-base charging locations. The primary objective of this study is to optimize the allocation of charging resources for commercial EV fleets and to maintain grid stability in the face of rapidly growing demand. Our model integrates fleet operational constraints, grid limitations, and incentive structures to provide a comprehensive solution that benefits fleet operators and utility providers. To validate our approach, we perform a series of computational experiments based on realistic data from the city of San Antonio, TX, a major urban center in Texas. These simulations demonstrate the model’s effectiveness in managing peak demand, optimizing resource utilization, and providing actionable insights for infrastructure planning.