面向用户行驶计划的电动汽车充电调度策略

doi:10.11772/j.issn.1001-9081.2016.08.2332

计算机应用 ›› 2016, Vol. 36 ›› Issue (8): 2332-2334.DOI: 10.11772/j.issn.1001-9081.2016.08.2332

面向用户行驶计划的电动汽车充电调度策略

曾鸣, 冷甦鹏, 张科

电子科技大学通信与信息工程学院, 成都 611731

收稿日期:2016-02-17 修回日期:2016-04-18 出版日期:2016-08-10 发布日期:2016-08-10
通讯作者: 曾鸣
作者简介:曾鸣(1989-),女,江西吉安人,博士研究生,主要研究方向:车辆入电网系统、资源分配、拍卖理论、匹配理论;冷甦鹏(1973-),男,四川攀枝花人,教授,博士,主要研究方向:智能电网、社交网络、车联网、认知无线电网络;张科(1978-),男,四川成都人,讲师,博士研究生,主要研究方向:智能电网、车联网、认知无线电网络。网络出版时间2016-05-1113:47:12。
基金资助:
国家自然科学基金资助项目（61374189）；中央高校基本科研业务费资助项目（ZYGX2013J009）。

Electric vehicle charging scheduling scheme oriented to traveling plan

ZENG Ming, LENG Supeng, ZHANG Ke

School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China

Received:2016-02-17 Revised:2016-04-18 Online:2016-08-10 Published:2016-08-10
Supported by:
This work is supported by the National Natural Science Foundation of China (61374189), the Fundamental Research Funds for the Central Universities (ZYGX2013J009).

摘要/Abstract

摘要： 充电站（桩）尚未普及以及电动汽车有限的行驶里程，使得大多数汽车用户关于是否选择电动汽车犹豫不决。为了减少用户对于电动汽车有限电池容量的担心，并且降低因频繁充电以及偏离原定行驶路线绕路进行充电所增加的电动汽车使用费用，提出一种基于匹配理论面向用户行驶计划的电动汽车充电调度方案TPCS。首先，分别根据电动汽车用户的行驶计划和对各充电站的电量需求构建电动汽车用户与充电站的偏好表；然后，建立电动汽车用户与充电站之间的多对一匹配模型；最后，以系统总效用为优化目标进行充电站接口分配。数值仿真结果显示，与随机分配（RCS）算法和仅考虑电动汽车效用分配（OEVS）算法相比，TPCS算法将系统总效用较RCS算法最多提高了39.3%，较OEVS算法最多提高了5%；而在电动汽车充电需求轻负载时，TPCS算法始终保证用户满意度在90%以上，高于RCS算法。所提算法能够有效地提高系统总效用和用户满意度，同时降低计算复杂度。

关键词: 充电调度, 行驶计划, 车辆入电网, 匹配理论, 偏好表

Abstract: Due to the deficiency of ubiquitous charging stations (or stakes) and short driving distances of Electric Vehicle (EV), many people are hesitant to use EV. To reduce users' anxiety about limited battery capacity and lower fees due to frequent charging and making detour to charge, a matching theoretic Traveling Plan-aware Charging Scheduling (TPCS) scheme was proposed. Firstly, preference lists of EV users and charging stations were constructed respectively according to traveling plans of EV and their electricity demand at each charging station. Secondly, a many-to-one matching model was established between EV users and charging stations. Finally, interfaces of charging stations were allocated to optimize the system total utility. Compared with the Random Charging Scheduling (RCS) algorithm and Only utility of Electric Vehicle concerned Scheduling (OEVS) algorithm, the system total utility of TPCS was increased at most by 39.3% and 5% respectively. In addition, TPCS guaranteed the satisfactory ratio of EV users to be above 90% when charging demand of EV users was light, which is higher than that of RCS. The proposed algorithm can effectively improve the system total utility and satisfactory ratio of EV users, and reduce the computational complexity.

Key words: charging scheduling, traveling plan, Vehicle-to-Grid (V2G), matching theory, preference list

中图分类号:

TP393.07

曾鸣, 冷甦鹏, 张科. 面向用户行驶计划的电动汽车充电调度策略[J]. 计算机应用, 2016, 36(8): 2332-2334.

ZENG Ming, LENG Supeng, ZHANG Ke. Electric vehicle charging scheduling scheme oriented to traveling plan[J]. Journal of Computer Applications, 2016, 36(8): 2332-2334.

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面向用户行驶计划的电动汽车充电调度策略

Electric vehicle charging scheduling scheme oriented to traveling plan

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