电动汽车
计算机科学
充电站
纳什均衡
能源管理
博弈论
时间范围
能量(信号处理)
模拟
汽车工程
数学优化
工程类
功率(物理)
数学
统计
物理
数理经济学
量子力学
作者
Amro Alsabbagh,Brian Wu,Chengbin Ma
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2021-04-01
卷期号:17 (4): 2422-2431
被引量:46
标识
DOI:10.1109/tii.2020.3003669
摘要
This article proposes a charging management of electric vehicles (EVs) that considers time anxieties and different behaviors of EV customers. The time anxiety concept is newly presented to address some uncertain events that may happen meanwhile charging of EVs, affect their charging patterns, and prevent them from meeting their energy demands. The working principle of the concept relies on prioritizing the charging before the event occurrences, and thus changing the EV charging patterns. Based on this concept, four different EV customer behaviors are proposed and their influences are investigated. The EV charging problem is formulated as a generalized nash equilibrium (NE) game, in which each EV minimizes its charging cost given its charging requirements and the charging facility constraints. The solution is developed on the basis of receding horizon optimization and reached iteratively in a distributed manner. Detailed simulation and comparison results are introduced to verify the effectiveness of the proposed charging management with the different time-anxiety-based EV customer behaviors.
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