上海交通大学学报

上海交通大学学报 >

2025 , Vol. 59 >Issue 9: 1304 - 1314

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2023.564

新型电力系统与综合能源

多种充电模式协同的规模化电动汽车分层充电方法

  • 刘永江 ,
  • 郭杉 ,
  • 贾俊青 ,
  • 刘小恺 ,
  • 蔡文超 ,
  • 曾龙
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  • 1 内蒙古电力(集团)有限责任公司, 呼和浩特 010010
    2 内蒙古电力科学研究院, 呼和浩特 010020
    3 上海交通大学 电子信息与电气工程学院, 上海 200240
刘永江(1977—),正高级工程师,从事综合能源系统优化调度研究.
曾 龙,博士后;E-mail:zenglong2404@qq.com.

收稿日期: 2023-11-10

  修回日期: 2024-01-06

  录用日期: 2024-01-10

  网络出版日期: 2024-01-24

基金资助

内蒙古自治区“揭榜挂帅”项目(2022JBGS0043)

收起

Electric Vehicles Hierarchical Charging Method Considering Multiple Modes Coordination

  • LIU Yongjiang ,
  • GUO Shan ,
  • JIA Junqing ,
  • LIU Xiaokai ,
  • CAI Wenchao ,
  • ZENG Long
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  • 1 Inner Mongolia Power (Group) Co., Ltd., Hohhot 010010, China
    2 Inner Mongolia Power Science Research Institute, Hohhot 010020, China
    3 School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 2023-11-10

  Revised date: 2024-01-06

  Accepted date: 2024-01-10

  Online published: 2024-01-24

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摘要

针对规模化电动汽车(EV)随机充电负荷冲击电网的问题,提出了一种多充电模式协同的规模化EV分层充电方法.通过利用不同充电方式特点,避免充电负荷集中于电力负荷高峰时间段.针对内蒙古某地区电力负荷曲线,考虑当地可再生能源丰富特点,基于K-means和肘部法则聚类成当地5类典型电力负荷曲线.考虑EV通过充电桩充电和换电站换电池,分别建立充电站充电模型和换电站电池交换模型,同时建立规模化EV分层能量交换模型.在上层中,根据用户特征以及充电方式成本,基于粒子群算法对EV与充电方式进行匹配;在下层中,考虑电力价格、用户需求、充电站运行情况和快、慢充特点,利用MATLAB自带优化工具箱优化充电站内EV、电池充电优化方案.实验仿真表明,本文所提方法采取的不同充电方式协同可实现充电方式优势互补,有效避免了充电负荷集中于电力负荷高峰时间段,可持续、经济地满足EV用户充电需求;但是单以电力价格作为EV充电负荷的引导信号,有可能加剧当地电力负荷曲线峰谷差和扰动情况.

关键词： 电动汽车; 充电桩; 电池交换; 充电模式协同; 分层优化

本文引用格式

刘永江 , 郭杉 , 贾俊青 , 刘小恺 , 蔡文超 , 曾龙 . 多种充电模式协同的规模化电动汽车分层充电方法[J]. 上海交通大学学报, 2025 , 59(9) : 1304 -1314 . DOI: 10.16183/j.cnki.jsjtu.2023.564

Abstract

To alleviate the adverse effect of large-scale electric vehicles (EVs) random charging, an EV hierarchical charging method considering multiple modes coordination is proposed in this paper, which avoids the large-scale charging load centralized in a certain period by coordinating diverse charging modes. Considering the load characteristics such as the output of renewable power generation, the power load curves of an area in Inner Mongolia Autonomous Region are clustered into five typical power load curves based on the K-means clustering algorithm and elbow method. According to the characteristics of EV charging and battery swapping (BS) modes, the charging station models and EV hierarchical power exchange model are established. At the upper level, the users’ requirements and charging costs are considered, and EVs are matched with the charging mode based on the particle swarm optimization algorithm. At the lower level, the electric price and charging station operation conditions are considered, and the charging schemes in the charging/BS station are optimized based on the optimization toolbox in the MATLAB software platform. Extensive case studies are conducted to validate the effectiveness of the proposed method, where a large number of EVs charge continuously with cost efficiency. However, relying solely on electricity price as the control signal for EV charging load may exacerbate the valley-to-peak disparity and instability of the local power load curve.

Key words： electric vehicle (EV); electric vehicle charger; battery swapping (BS); charging modes coordination; hierarchical optimization

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