23rd Conference of the International Federation of Operational Research Societies
Abstract Submission

1096. Electric Vehicle Fleet and Charging Infrastructure Planning

Invited abstract in session HD-22: Applications of Game Theory in Operations Management , cluster Game Theory and Operations Management.

Thursday, 14:15-15:45
Room: FENH202

Authors (first author is the speaker)

1. Francisco Castro
UCLA
2. Siva Theja
Georgia Tech
3. Sushil Varma
Georgia Tech

Abstract

We analyze an optimal electric vehicle (EV) fleet and charging infrastructure capacity planning problem in a spatial setting. As customer requests arrive, the system operator must determine the minimum number of vehicles and chargers along with a matching and charging policy maximizing the service level. We provide a sharp characterization of the fleet size and the charging infrastructure requirements as the demand grows. While a system with negligible charging times needs a 2/3-staffing rule on top of the nominal capacity, an EV system has a fundamentally different scaling. Due to charging times, the nominal capacity of the system is increased, but this extra capacity allows for an optimal EV dispatching policy to result in an extra fleet requirement translating into a decreased staffing rule anywhere between 1/2 and 2/3, depending on the number of charging stations and the size of the EV battery packs. We propose the Power-of-d dispatching policy, achieving this performance by selecting the d closest vehicles to a trip request and choosing the one with the highest battery level, thus optimizing the trade-off between the pickup distance and balancing the state of charge across the fleet. Our study provides valuable guidelines for determining the optimal fleet and charging infrastructure capacity for an EV-based on-demand transportation system.

Keywords

Status: accepted

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