电动汽车智能充放电控制与应用综述

doi:10.12096/j.2096-4528.pgt.20022

发电技术 ›› 2021, Vol. 42 ›› Issue (2): 180-192.DOI: 10.12096/j.2096-4528.pgt.20022

电动汽车智能充放电控制与应用综述

贺瑜环¹(), 杨秀媛¹^,*(), 陈麒宇²(), 卜思齐³(), 徐智蔷⁴(), 肖天颖⁵^,⁶()

¹ 北京信息科技大学自动化学院, 北京市海淀区 100192
² 中国电力科学研究院有限公司, 北京市海淀区 100192
³ 香港理工大学电机工程学系, 香港特别行政区九龙 999077
⁴ 英国南安普顿大学物理工程学院, 英国南安普顿 SO17 1BJ
⁵ 中国科学院电工研究所, 北京市海淀区 100190
⁶ 中国科学院大学, 北京市海淀区 100049

收稿日期:2020-04-09 出版日期:2021-04-30 发布日期:2021-04-29
通讯作者: 杨秀媛
作者简介:贺瑜环(1995), 女, 硕士研究生, 研究方向为控制理论与控制工程及新能源发电, 910169459@qq.com
陈麒宇(1986), 男, 博士, 高级工程师, 主要研究方向为新能源及电力系统分析与规划, chenqiyu@epri.sgcc.com.cn
卜思齐(1984), 男, 博士, 副教授, 博士生导师, 主要从事电力电子化和智能化电力系统稳定控制分析与运行规划研究, siqi.bu@polyu.edu.hk
徐智蔷(1977), 女, 博士, 研究员, 研究方向为电力电缆及其在电力物联网中应用, zhq.xu@soton.ac.uk
肖天颖(1992), 女, 博士研究生, 研究方向为分布式能源与主动配电网, tianyingxiao@mail.iee.ac.cn
基金资助:
国家自然科学基金项目(51377011)

Review of Intelligent Charging and Discharging Control and Application of Electric Vehicles

Yuhuan HE¹(), Xiuyuan YANG¹^,*(), Qiyu CHEN²(), Siqi BU³(), Zhiqiang XU⁴(), Tianying XIAO⁵^,⁶()

¹ School of Automation, Beijing Information Science & Technology University, Haidian District, Beijing 100192, China
² China Electric Power Research Institute, Haidian District, Beijing 100192, China
³ Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong S. A. R., China
⁴ School of Physical Sciences and Engineering, University of Southampton, Southampton SO17 1BJ, UK
⁵ Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing 100190, China
⁶ University of Chinese Academy of Sciences, Haidian District, Beijing 100049, China

Received:2020-04-09 Published:2021-04-30 Online:2021-04-29
Contact: Xiuyuan YANG
Supported by:
National Natural Science Foundation of China(51377011)

摘要/Abstract

摘要：

随着电动汽车规模的增大，电动汽车接入电网对电力系统运行与控制的影响不容忽视。电动汽车作为一种可控负荷，对其进行充放电控制可以有效削弱充电负荷带来的不利影响，同时还能起到削峰填谷、促进新能源消纳的作用，这将成为电力系统运行控制的一种重要手段。给出了充电负荷建模需要考虑的因素，总结了建立电动汽车负荷预测模型的方法。归纳了电动汽车参与电网调度的可行方法，并分析了不同方法的特点。同时，为了提高电动汽车参与调度的积极性，介绍了用区块链完成电动汽车电力交易的架构与方法。最后，对尚未解决的问题和可能的研究方向进行了讨论。

关键词: 电动汽车, 充电负荷, 智能控制, 区块链, 电力系统

Abstract:

With the increasing integration scale of electric vehicles, their impact on the operation and control of the power system cannot be ignored. As a controllable load, the charging and discharging control of electric vehicles can effectively weaken the adverse effects brought by the charging load, and can also play a role of peak-shaving and valley-filling, and promote the consumption of new energy, which will become an important means of power system operation control. The factors to be considered in charging load modeling were firstly given, and the methods for establishing electric vehicle load forecasting models were summarized. Then, the feasible methods of electric vehicle participating in power grid dispatching were reviewed, and the characteristics of different methods were revealed. At the same time, in order to promote the willingness of electric vehicles to participate in dispatching, the architecture and methods of using blockchain to complete electric vehicle power trading were introduced. Finally, the unsolved problems and possible research directions were discussed.

Key words: electric vehicle, charging load, intelligent control, blockchain, power system

中图分类号:

TM73

贺瑜环, 杨秀媛, 陈麒宇, 卜思齐, 徐智蔷, 肖天颖. 电动汽车智能充放电控制与应用综述[J]. 发电技术, 2021, 42(2): 180-192.

Yuhuan HE, Xiuyuan YANG, Qiyu CHEN, Siqi BU, Zhiqiang XU, Tianying XIAO. Review of Intelligent Charging and Discharging Control and Application of Electric Vehicles[J]. Power Generation Technology, 2021, 42(2): 180-192.

图/表 11

表1 不同类型电池性能对比

Tab. 1 Performance comparison of different types of batteries

性能	锂离子电池	镍镉电池	镍氢电池
工作电压/V	3.7	1.2	1.2
电池容量	高	低	中
质量比能量/(W·h/kg)	100~160	45	60
体积比能量/(W·h/L)	280	160	210
循环寿命/次	500~1 000	300~700	200~600
放电率/(%/月)	2~5	15~30	25~35
低温性能	较差	优	优
高温性能	优	一般	差
记忆效应	无	有	无

表2 不同类型电动汽车性能对比

Tab. 2 Performance comparison of different types of electric vehicles

性能	比亚迪E6	荣威Ei5	宝马i3	Model X
最大功率/kW	120	85	125	487
电池容量/(kW·h)	82.0	52.5	42.2	100.0
快充时间/h	1.50	0.67	0.70	1.00
慢充时间/h	8.0	8.5	4.9	10.0
续航里程/km	400	420	340	575
最大扭矩/(N·m)	450	255	250	404

图1 基于蒙特卡罗模拟的电动汽车充电负荷计算流程图

Fig.1 Calculation flow chart of electric vehicle charging load based on Monte Carlo simulation

图2 基于出行链的电动汽车充电负荷计算流程图

Fig.2 Calculation flow chart of electric vehicle charging load based on travel chain

图3 基于车-路-网模型的电动汽车充电负荷计算流程图

Fig.3 Calculation flow chart of electric vehicle charging load based on vehicle-road-network model

图4 电动汽车与电网交互示意图

Fig.4 Diagram of interaction between electric vehicle and power grid

图5 基于集中式控制的电动汽车管理框架

Fig.5 Electric vehicle management framework based on centralized control

图6 分布式控制策略流程图

Fig.6 Flow chart of distributed control strategy

图7 基于分层式控制的电动汽车管理框架

Fig.7 Electric vehicle management framework based on distributed control

图8 基于区块链的电动汽车电力交易架构示意图

Fig.8 Schematic diagram of electric vehicle electric power transaction architecture based on blockchain

图9 基于区块链的电动汽车电力交易流程图

Fig.9 Schematic diagram of electric vehicle electric power transaction process based on blockchain

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电动汽车智能充放电控制与应用综述

Review of Intelligent Charging and Discharging Control and Application of Electric Vehicles

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