A data-driven approach to managing electric vehicle charging infrastructure in parking lots

Abstract

Underdeveloped charging infrastructure is one of the main barriers to widespread electric vehicle (EV) adoption. Transforming parking lots into EV-enabled parking lots that provide parking and charging services is a solution to address the need for charging stations. Two challenges arise in this context: (1) how many parking spots should receive EV chargers and (2) how to appropriately define the pricing scheme for the charging service. We tackle these challenges by proposing a novel framework based on discrete-event simulations and queueing theory. Our framework can estimate the ideal number of EV chargers and the charging price. These estimates can be used to determine the profitability and payback period for transforming traditional parking lots into EV-enabled parking lots. We illustrate the use of our framework in a real-world setting involving the city of Melbourne, Australia. When doing so, we derive a new methodology to measure the range anxiety phenomenon. • We study how to optimally design EV-enabled parking lots. • We propose a framework based on discrete-event simulations and queueing theory. • Our framework can estimate the optimal number of EV chargers and the charging price. • We illustrate the use of our framework in a real-world setting.