Optimal EV Charging Decisions Considering Charging Rate Characteristics and Congestion Effects

被引:0
作者
Yi, Lihui [1 ]
Wei, Ermin [1 ,2 ]
机构
[1] Northwestern Univ, Dept Elect & Comp Engn, Evanston, IL 60208 USA
[2] Northwestern Univ, Dept Ind Engn & Management Sci, Evanston, IL 60208 USA
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2024年 / 11卷 / 05期
基金
美国国家科学基金会;
关键词
Batteries; Charging stations; Costs; Electric vehicle charging; Data models; Vehicles; Numerical models; Electric vehicles; charging stations; varying charging rate; endogenous congestion cost; differential equation; SYSTEM; GAME;
D O I
10.1109/TNSE.2024.3424443
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the rapid growth in demand for electric vehicles (EVs), corresponding charging infrastructures are expanding. These charging stations are located at various places with different congestion levels. EV drivers face an important decision in choosing between charging stations to reduce their overall time costs. However, existing literature either assumes a flat charging rate and hence overlooks the physical characteristics of an EV battery where charging rate is typically reduced as the battery charges, or ignores the effect of other drivers on an EV's decision making process. In this paper, we consider both the predetermined exogenous wait cost and the endogenous congestion induced by other drivers' strategic decisions, and propose a differential equation based approach to find the optimal strategies. We analytically characterize the equilibrium strategies and find that co-located EVs may make different decisions depending on the charging rate and/or remaining battery levels. Through numerical experiments, we investigate the impact of charging rate characteristics, modeling parameters and the consideration of endogenous congestion levels on the optimal charging decisions. Finally, we apply real-world data and find that some EV users with slower charging rates may benefit from the participation of fast-charging EVs.
引用
收藏
页码:5045 / 5057
页数:13
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