Optimal Policies for the Management of an Electric Vehicle Battery Swap Station

Abstract

Optimizing operations at electric vehicle (EV) battery swap stations is internally motivated by the movement to make transportation cleaner and more efficient. An EV battery swap station allows EV owners to quickly exchange their depleted battery for a fully charged battery. We introduce the EV Battery-Swap Station Management Problem (EVB-SSMP), which models battery charging and discharging operations at an EV battery swap station facing nonstationary, stochastic demand for battery swaps, nonstationary prices for charging depleted batteries, and nonstationary prices for discharging fully charged batteries. Discharging through vehicle-to-grid is beneficial for aiding power load balancing. The objective of the EVB-SSMP is to determine the optimal policy for charging and discharging batteries that maximizes expected total profit over a fixed time horizon. The EVB-SSMP is formulated as a finite-horizon, discrete-time Markov decision problem and an optimal policy is found using dynamic programming. We derive structural properties, to include sufficiency conditions that ensure the existence of a monotone optimal policy. Utilizing available demand and electricity pricing data, we design and conduct two main computational experiments to obtain policy insights regarding the management of EV battery swap stations. We compare the optimal policy to two benchmark policies that are easily implementable by swap station managers. Policy insights include the relationship between the minimum battery level and the number of EVs in a local service area, the pricing incentive necessary to encourage effective discharge behavior, and the viability of EV battery swap stations under many conditions. The online appendix is available at https://doi.org/10.1287/trsc.2016.0676 .