| 引用本文: | 金志刚,胡 怡,李 根,岳顺民.面向“代客加电”服务的电动汽车充电引导策略[J].电力系统保护与控制,2022,50(14):76-84.[点击复制] |
| JIN Zhigang,HU Yi,LI Gen,YUE Shunmin.Charging guiding strategy for electric vehicles oriented to a valet charging service[J].Power System Protection and Control,2022,50(14):76-84[点击复制] |
|
| 摘要: |
| 为解决电动汽车面临的充电难题，提出面向“代客加电”服务的电动汽车充电引导策略。首先，充分考虑“代客加电”服务，对电动汽车充电引导场景及充电影响因素进行分析。其次，以最优化电动汽车用户充电经济成本、代充电服务侧利益以及充电站设备利用率为目标建立充电引导模型，并采用改进的灰狼优化算法引导电动汽车的充电行为。最后，对某城市主要城区内具有充电需求的电动汽车进行仿真。结果表明：面向“代客加电”服务的电动汽车充电引导策略能够有效减少电动汽车用户充电经济成本、代驾司机代充电过程中的时间成本以及距离成本，同时实现充电站间设备利用率均衡分布。 |
| 关键词: 电动汽车 “代客加电”服务 充电引导策略 多目标优化 改进灰狼优化算法 |
| DOI：DOI: 10.19783/j.cnki.pspc.211333 |
| 投稿时间：2021-09-29修订日期：2021-12-24 |
| 基金项目:国家自然科学基金项目资助(51677124)；天津市自然科学基金项目资助(19JCYBJC15700) |
|
| Charging guiding strategy for electric vehicles oriented to a valet charging service |
| JIN Zhigang,HU Yi,LI Gen,YUE Shunmin |
| (1. School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China;
2. Key Laboratory of the Ministry of Education on Smart Power Grids (Tianjin University), Tianjin 300072, China;
3. State Grid Tianjin Electric Power Company, Tianjin 300010, China) |
| Abstract: |
| In order to deal with the charging problems of electric vehicles (EVs), a charging guiding strategy for EVs oriented to a valet charging service is proposed. First, the EV charging guiding scenarios and the influence factors of charging are analyzed comprehensively considering the valet charging service. Secondly, a charging guiding model is established, with the aim of optimizing the EV users’ economic cost, the benefits of agent charging service providers and the utilization rate of charging station equipment. The improved grey wolf optimization is used to guide the charging behaviors of EVs. Finally, simulations of EVs with their charging requirements in a major urban area of a city are conducted. The results show that the charging guiding strategy for EVs oriented to a valet charging service can effectively reduce the charging economic cost of EV users as well as the time cost and distance cost in the process of charging for agent drivers. At the same time it realizes the balanced distribution of equipment utilization among charging stations.
This work is supported by the National Natural Science Foundation of China (No. 51677124). |
| Key words: electric vehicle valet charging service charging guiding strategy multi-objective optimization improved grey wolf optimization |
