Scheduling and performance analysis under a stochastic model for electric vehicle charging stations

被引:26
|
作者
Kim, Jerim [1 ]
Son, Sung-Yong [2 ]
Lee, Jung-Min [3 ]
Ha, Hyung-Tae [3 ]
机构
[1] Yong In Univ, Dept Business Adm, Yongin 449714, Gyunggi Do, South Korea
[2] Gachon Univ, Dept Elect Engn, Sungnam Si 461701, Gyunggi Do, South Korea
[3] Gachon Univ, Dept Appl Stat, Sungnam Si 461701, Gyunggi Do, South Korea
基金
新加坡国家研究基金会;
关键词
Electric vehicles; Battery charging station; Stochastic modeling; Charge scheduling; Markov-modulated Poisson process; Performance measures; TIME;
D O I
10.1016/j.omega.2015.11.010
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Wide-spread infrastructures for electric vehicle battery charging stations are essential in order to significantly increase the implementation of electric vehicles (EVs) in the foreseeable future. Therefore, we propose a stochastic model and charge scheduling methods for an EV battery charging system. We utilize a flexible Poisson process with a hidden Markov chain for modeling the complexity of the time-varying behavior of the EV stream into the system. Relevant random factors and constraints, which include parking times, requested amounts of electricity, the number of parking lots (charging facilities), and maximal demand level, are considered within the proposed stochastic model. Performance measures for the proposed charge scheduling are analytically derived by obtaining stationary distributions of states concerning the number of inbound EVs, waiting time distributions, and the joint distributions of parking time and electricity charged during random parking times. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:278 / 289
页数:12
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