Self-controlling resource management model for electric vehicle fast charging stations with priority service

Abstract

Along with the increasing number of electric vehicles (EVs) on the roads, the demand for public fast-charging stations is growing. Long charging times for EVs may lead to congestion in charging stations, queues, and increased waiting times. Different vehicle owners have different sensitivities to waiting time and price. User prioritization is an effective solution for satisfying users with different requests. In this study, we develop a self-controlling resource management model for EV fast-charging stations that provide prioritized service. The model aims to control the delay times of express and normal vehicle classes such that the ratio of their average delay times tracks a target relative delay rate in real time. Each station can determine and change its target relative delay rate according to its policy. The model manages the allocation of resources to user classes in real time through a control mechanism to track the target. The control mechanism uses a simulation model to predict the outcomes of its actions. Numerical studies demonstrate that the model successfully achieves the relative delay target in both steady state and real time under different conditions. The model is applicable to most systems with a dynamically varying workload and a priority-based service goal.