基于补偿机制的电动汽车区域多维补电优化调度策略

doi:10.11930/j.issn.1004-9649.202404112

中国电力 ›› 2025, Vol. 58 ›› Issue (4): 119-130.DOI: 10.11930/j.issn.1004-9649.202404112

• 大规模新能源汽车与城乡电网融合互动 • 上一篇下一篇

基于补偿机制的电动汽车区域多维补电优化调度策略

袁建华¹^,²(), 张天宇¹^,²(), 陈广生¹^,², 黄淘¹^,²

1. 三峡大学电气与新能源学院，湖北宜昌　443002
2. 梯级水电站运行与控制湖北省重点实验室（三峡大学），湖北宜昌　443002

收稿日期:2024-04-24 录用日期:2024-07-23 发布日期:2025-04-23 出版日期:2025-04-28
作者简介:
袁建华（1978），男，通信作者，博士，副教授，从事光电子技术应用、微电网运行与控制研究，E-mail：sd.yjh@mail.sdu.edu.cn
张天宇（2000），男，硕士研究生，从事电动汽车调度及电池调度研究，E-mail：19862515059@163.com
基金资助:
湖北省输电线路工程技术研究中心基金项目（2022KXL03）。

Optimization and Scheduling Strategy for Regional Multi-dimensional Charging of Electric Vehicles Based on Compensation Mechanism

YUAN Jianhua¹^,²(), ZHANG Tianyu¹^,²(), CHEN Guangsheng¹^,², HUANG Tao¹^,²

1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
2. Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station (China Three Gorges University), Yichang 443002, China

Received:2024-04-24 Accepted:2024-07-23 Online:2025-04-23 Published:2025-04-28
Supported by:
This work is supported by Research Fund of Hubei Provincial Transmission Line Engineering Technology Research Center (No.2022KXL03).

摘要/Abstract

摘要：

针对多补电区域、多补电方式条件下电动汽车无序补电的现象，为保障补电服务商经济性及消纳高效性的同时兼顾用户补电满意度，提出一种基于补偿机制的电动汽车区域多维补电优化调度策略。首先，基于电量和时间冗余情况进行集群划分，基于补电补偿及时间压力建立补偿感知模型，综合考虑用户花费、时间消耗及结束补电量，进一步构建用户满意度模型及基于后悔定理的用户补电方案决策模型；其次，建立充换电站电池日内滚动补能模型；最后，建立优化调度模型，以最大化补电服务商收益和最小化区域消纳偏差为目标，对补电补偿进行优化。Matlab仿真验证表明，与对比策略相比，所提策略方法增加了补电服务商收益，降低了区域消纳偏差，同时保证了用户对补电方案的满意度。

关键词: 区域多维补电, 后悔理论, 补电补偿, 用户满意度, 多目标优化

Abstract:

To improve the power supply service provider’s economic efficiency and user’s satisfaction under the background of electric vehicle (EV) charging-disorder in varied charging settings, this paper proposes a compensation-based optimization and scheduling strategy for regional multi-dimensional charging of electric vehicles. Firstly, clusters are formed based on energy consumption patterns and temporal flexibility, and a compensation perception model is established based on charging compensation and time pressure. A user satisfaction model and a regret theory-based user charging decision model are developed with consideration of charging cost, time and quantity of users. And then, a daily rolling energy replenishment model is established for batteries at BCSS. Finally, an optimization scheduling model is created to optimize the charging compensation for maximizing the provider’s revenue and minimizing the regional consumption imbalances. The proposed strategy, verified through Matlab simulation, boosts the power supply service provider’s revenue and slashs the regional consumption deviation, while maintaining the user’s satisfaction with the charging solution.

Key words: regional multi-dimensional charging, regret theory, charging compensation, user satisfaction, multi-objective optimization

袁建华, 张天宇, 陈广生, 黄淘. 基于补偿机制的电动汽车区域多维补电优化调度策略[J]. 中国电力, 2025, 58(4): 119-130.

YUAN Jianhua, ZHANG Tianyu, CHEN Guangsheng, HUANG Tao. Optimization and Scheduling Strategy for Regional Multi-dimensional Charging of Electric Vehicles Based on Compensation Mechanism[J]. Electric Power, 2025, 58(4): 119-130.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202404112

https://www.electricpower.com.cn/CN/Y2025/V58/I4/119

图/表 17

参考文献 22

1	黄学良, 刘永东, 沈斐, 等. 电动汽车与电网互动: 综述与展望[J]. 电力系统自动化, 2024, 48 (7): 3- 23. DOI
	HUANG Xueliang, LIU Yongdong, SHEN Fei, et al. Vehicle to grid: review and prospect[J]. Automation of Electric Power Systems, 2024, 48 (7): 3- 23. DOI
2	李捷, 杨冰. 电动汽车换电站参与电力市场辅助服务的经济效益研究[J]. 中国电力, 2020, 53 (12): 258- 262, 269.
	LI Jie, YANG Bing. Study on economic benefits of electric vehicle battery swapping station participating in power market auxiliary service[J]. Electric Power, 2020, 53 (12): 258- 262, 269.
3	朱继忠, 何晨可, 刘云, 等. 面向电动汽车高渗透率综合能源系统的换电模式综述与展望[J]. 南方电网技术, 2023, 17 (10): 133- 151.
	ZHU Jizhong, HE Chenke, LIU Yun, et al. Review and prospect of swapping pattern for integrated energy system with high penetration of electric vehicles[J]. Southern Power System Technology, 2023, 17 (10): 133- 151.
4	韩继明, 孔令宇, 王皓, 等. 电动汽车充换电设施规划综述[J]. 电力系统及其自动化学报, 2016, 28 (S1): 63- 67.
	HAN Jiming, KONG Lingyu, WANG Hao, et al. Review on the planning of charging facilities for electric vehicles[J]. Proceedings of the CSU-EPSA, 2016, 28 (S1): 63- 67.
5	吴翠玉, 张美霞, 陈海燕, 等. 国内外电动汽车扶持政策比较与分析[J]. 上海电力学院学报, 2016, 32 (2): 188- 192,209.
	WU Cuiyu, ZHANG Meixia, CHEN Haiyan, et al. Comparative analysis of supportive policies for electric vehicles at home and abroad[J]. Journal of Shanghai University of Electric Power, 2016, 32 (2): 188- 192,209.
6	ZHAO X, PENG B H, ZHENG C Y, et al. Closed-loop supply chain pricing strategy for electric vehicle batteries recycling in China[J]. Environment, Development and Sustainability, 2022, 24 (6): 7725- 7752. DOI
7	苏娟, 李拓, 刘峻玮, 等. 综合能源系统下虚拟储能建模方法与应用场景研究综述及展望[J]. 中国电力, 2024, 57 (6): 53- 68.
	SU Juan, LI Tuo, LIU Junwei, et al. Review and prospect of modeling method and application scenarios of virtual energy storage under integrated energy system[J]. Electric Power, 2024, 57 (6): 53- 68.
8	刘文军, 董伟杰, 陈远扬, 等. 新能源高渗透配电网柔性多状态开关的多目标优化控制策略[J]. 中国电力, 2025, 58 (1): 85- 92.
	LIU Wenjun, DONG Weijie, CHEN Yuanyang, et al. Multi-objective Optimization Control Strategy for Soft Open Point inDistribution Network with High Penetration of DG[J]. Electric Power, 2025, 58 (1): 85- 92.
9	梁振锋, 祁芙蓉, 王国阳, 等. 电动汽车有序充电优化策略综述[J]. 新型电力系统, 2023, (3): 256- 271.
	LIANG Zhenfeng, QI Furong, WANG Guoyang, et al. Review of optimization strategies for orderly charging of electric vehicles[J]. New Type Power Systems, 2023, (3): 256- 271.
10	裴振坤, 王学梅, 康龙云. 电动汽车参与电网辅助服务的控制策略综述[J]. 电力系统自动化, 2023, 47 (18): 17- 32. DOI
	PEI Zhenkun, WANG Xuemei, KANG Longyun. Review on control strategies for electric vehicles participating in ancillary services of power grid[J]. Automation of Electric Power Systems, 2023, 47 (18): 17- 32. DOI
11	侯慧, 唐俊一, 王逸凡, 等. 价格与激励联合需求响应下电动汽车长时间尺度充放电调度[J]. 电力系统自动化, 2022, 46 (15): 46- 55.
	HOU Hui, TANG Junyi, WANG Yifan, et al. Long-time-scale charging and discharging scheduling of electric vehicles under joint price and incentive demand response[J]. Automation of Electric Power Systems, 2022, 46 (15): 46- 55.
12	任峰, 向月. 辅助负荷削峰的电动出租车V2G协同策略与效益分析[J]. 电力自动化设备, 2022, 42 (2): 63- 69.
	REN Feng, XIANG Yue. V2G coordinated strategy and benefit analysis of electric taxis to assist peak load shifting[J]. Electric Power Automation Equipment, 2022, 42 (2): 63- 69.
13	崔杨, 李翼成, 付小标, 等. 基于换电服务定价策略及动态调控方法的含充换电站微电网系统双层优化调度[J]. 电网技术, 2023, 47 (5): 1998- 2011.
	CUI Yang, LI Yicheng, FU Xiaobiao, et al. Double-layer optimal scheduling of micro-grid system with charging and swapping stations based on battery swap service pricing strategy and dynamic regulation[J]. Power System Technology, 2023, 47 (5): 1998- 2011.
14	赵楠, 王俊, 黄桦, 等. 计及氢电混合动力车响应的多区域综合能源系统协调优化调度[J]. 电力自动化设备, 2023, 43 (12): 257- 264.
	ZHAO Nan, WANG Jun, HUANG Hua, et al. Coordinated optimal scheduling of multi-region integrated energy system with hydrogen-electric hybrid vehicle response[J]. Electric Power Automation Equipment, 2023, 43 (12): 257- 264.
15	傅质馨, 朱韦翰, 朱俊澎, 等. 动态路-电耦合网络下电动出租车快速充电引导及其定价策略[J]. 电力自动化设备, 2022, 42 (4): 9- 17.
	FU Zhixin, ZHU Weihan, ZHU Junpeng, et al. Fast charging guidance and pricing strategy for electric taxis based on dynamic traffic-grid coupling network[J]. Electric Power Automation Equipment, 2022, 42 (4): 9- 17.
16	孙毅, 葛明洋, 王献春, 等. 考虑补偿激励的电动汽车多区域优化调度策略[J]. 上海交通大学学报, 2024, 58 (5): 636- 646.
	SUN Yi, GE Mingyang, WANG Xianchun, et al. Multi-region optimal scheduling strategy for electric vehicles considering compensation incentives[J]. Journal of Shanghai Jiao Tong University, 2024, 58 (5): 636- 646.
17	ALHARBI W, HUMAYD A S B, PRAVEEN R P, et al. Optimal scheduling of battery-swapping station loads for capacity enhancement of a distribution system[J]. Energies, 2023, 16 (1): 186.
18	赵显秋, 徐青山, 杨永标, 等. 考虑不确定性的新型电池充换电站多时间尺度能量管理策略[J/OL]. 电网技术, 1–12[2024-12-25]. https://doi.org/10.13335/j.1000-3673. pst. 2023.0057.
	ZHAO Xianqiu, XU Qingshan, YANG Yongbiao, et al. Multi-time scale energy management strategy of novel battery charging and swapping station considering uncertainties[J/OL]. Power System Technology. 1–12[2024-12-25]. https://doi.org/10.13335/j.1000-3673. pst. 2023.0057.
19	刘永江, 郭杉, 贾俊青, 等. 多种充电模式协同的规模化电动汽车分层充电方法[J/OL]. 上海交通大学学报, 1–25[2024-12-25]. https://doi.org/10.16183/j. cnki.jsjtu.2023.564.
	LIU Yongjiang, GUO Shan, JIA Junqing, et al. Electric vehicles hierarchical charging method considering multiple modes coordination[J/OL]. Journal of Shanghai Jiao Tong University: 1–25[2024-12-25]. https://doi.org/10.16183/j. cnki.jsjtu.2023.564.
20	刘洪, 阎峻, 葛少云, 等. 考虑多车交互影响的电动汽车与快充站动态响应[J]. 中国电机工程学报, 2020, 40 (20): 6455- 6468.
	LIU Hong, YAN Jun, GE Shaoyun, et al. Dynamic response of electric vehicle and fast charging stations considering multi-vehicle interaction[J]. Proceedings of the CSEE, 2020, 40 (20): 6455- 6468.
21	BRISSAUD C, REUMONT G, SMAHA J P, et al. Structural and morphological study of damage in lead/acid batteries during cycling and floating tests[J]. Journal of Power Sources, 1997, 64 (1/2): 117- 122.
22	U. S. Department of Transportation, FeDERal Highway Administration. 2017 National Household Travel Survey[DB/OL]. URL: http: //nhts. ornl. gov.

参数名称	数值	参数名称	数值
$ \kappa {\text{/(kW}} \cdot {\text{k}}{{\text{m}}^{{{ - 1}}}}) $	0.15	${\nu ^{\text{T}}}/(\rm r \cdot \min{^{ - 1}})$	0.4
$ {v^{{\text{ave}}}}{\text{/(km}} \cdot {{\text{h}}^{ - 1}}{\text{)}} $	40	$\nu _{^{\text{1}}}^{\text{S}}/(\rm r \cdot \min{^{ - 1}})$	–0.96
$ {Q^{{\text{ed}}}}/\rm kW $	60	$\nu _{^2}^{\text{S}}/(\rm r \cdot \min{^{ - 1}})$	–1.522
$ {P^{{\text{cha}}}}/(\rm kW \cdot h) $	40	$ {\omega _{\text{1}}} $	0.3
$ {P^{{\text{SW}}}}/(\rm kW \cdot h) $	50	$ {\omega _{\text{2}}} $	0.4
$ {a^{{\text{chaxl}}}} $	0.9	$ {\omega _{\text{3}}} $	0.3
$ {a^{{\text{swxl}}}} $	0.9	$ {Q^{\min }}/\rm kW $	57
$ {t^{{\text{sw}}}}/\min $	5-10	$ {Q^{\max }}/{\text{kW}} $	12
$ t_{i,l}^{{\text{zb}}}/\min $	5-10	$ {N^{{\text{dz}}}} $	3
$ v $	0.6	$ \theta $	0.1
$ t_i^{\rm kx}/\min $	30-90	$ {\kappa _1} $	0.5
$ \Delta t{\text{/min}} $	15	$ {\kappa _0} $	0.3

参数名称	数值	参数名称	数值
$ \kappa {\text{/(kW}} \cdot {\text{k}}{{\text{m}}^{{{ - 1}}}}) $	0.15	${\nu ^{\text{T}}}/(\rm r \cdot \min{^{ - 1}})$	0.4
$ {v^{{\text{ave}}}}{\text{/(km}} \cdot {{\text{h}}^{ - 1}}{\text{)}} $	40	$\nu _{^{\text{1}}}^{\text{S}}/(\rm r \cdot \min{^{ - 1}})$	–0.96
$ {Q^{{\text{ed}}}}/\rm kW $	60	$\nu _{^2}^{\text{S}}/(\rm r \cdot \min{^{ - 1}})$	–1.522
$ {P^{{\text{cha}}}}/(\rm kW \cdot h) $	40	$ {\omega _{\text{1}}} $	0.3
$ {P^{{\text{SW}}}}/(\rm kW \cdot h) $	50	$ {\omega _{\text{2}}} $	0.4
$ {a^{{\text{chaxl}}}} $	0.9	$ {\omega _{\text{3}}} $	0.3
$ {a^{{\text{swxl}}}} $	0.9	$ {Q^{\min }}/\rm kW $	57
$ {t^{{\text{sw}}}}/\min $	5-10	$ {Q^{\max }}/{\text{kW}} $	12
$ t_{i,l}^{{\text{zb}}}/\min $	5-10	$ {N^{{\text{dz}}}} $	3
$ v $	0.6	$ \theta $	0.1
$ t_i^{\rm kx}/\min $	30-90	$ {\kappa _1} $	0.5
$ \Delta t{\text{/min}} $	15	$ {\kappa _0} $	0.3

项目	峰	平	谷
项目	08:00—12:00 17:00—21:00	12:00—17:00 21:00—24:00	00:00-8:00
快充电价	1.532	0.831	0.534
换电电价	2.080	2.080	2.080
DER 电价	0.430	0.300	0.180
购电电价	0.630	0.410	0.300

项目	峰	平	谷
项目	08:00—12:00 17:00—21:00	12:00—17:00 21:00—24:00	00:00-8:00
快充电价	1.532	0.831	0.534
换电电价	2.080	2.080	2.080
DER 电价	0.430	0.300	0.180
购电电价	0.630	0.410	0.300

策略	消纳水平偏差	策略	消纳水平偏差
对比策略1	0.3907	对比策略3	0.3112
对比策略2	0.2317	本文策略	0.2207

基于补偿机制的电动汽车区域多维补电优化调度策略

Optimization and Scheduling Strategy for Regional Multi-dimensional Charging of Electric Vehicles Based on Compensation Mechanism

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 17

参考文献 22

相关文章 15

编辑推荐

Metrics

策略	总花费(p.u.)	总补电量(p.u.)	总耗时长(p.u.)	均获补偿	满意度
策略1	1912.9	2895.8	2364.7	10.05	–0.4849
策略2	1773.7	2881.2	2567.3	11.58	–0.5122
策略3	2131.5	2876.4	1549.9	17.98	–0.2825
本文	1987.6	2873.1	1479.6	20.47	–0.2085

策略	补电收益	电池损耗	购电成本	消纳补偿	均总收益
策略1	12.0582	0.1097	4.1487	4.0248	3.9415
策略2	11.0130	0.0621	3.7359	4.8597	4.0248
策略3	12.3792	0.1736	4.4326	4.7608	4.1779
本文	12.1611	0.1739	4.0376	5.0515	4.3336

编号	空闲时间/min	需求电量/kW	补电区域	补电方式
5	42	36.7	1	换电
16	54	38.2	1	换电
34	73	33.3	3	快充
47	61	31.1	3	快充

编号	补电方式	最优补电区域	时间后悔值	价格后悔值	补电量后悔值	总后悔值
5	充电	2	28.5	0	8.8	37.3
5	换电	1	0	12.1	0	12.1
16	充电	3	31.5	0	7.4	38.9
16	换电	1	0	9.6	0	9.6
34	充电	3	24.5	0	0	24.5
34	换电	1	0	31.5	0	31.5
47	充电	3	21.5	0	0	21.5
47	换电	1	0	32.6	0	32.6

EV数量	服务商收益/万元	消纳偏差	用户满意度	均花费/ 元	均获补偿/元
0.75倍	3.3258	0.3143	–0.1871	43.41	22.23
初始	4.3336	0.2207	–0.2085	42.78	20.47
1.25倍	5.2026	0.2836	–0.1902	42.93	21.66
1.5倍	6.3218	0.3208	–0.1776	44.28	22.13

[1]	刘文军, 董伟杰, 陈远扬, 何书耘, 陈剑, 贾东强. 新能源高渗透配电网柔性多状态开关的多目标优化控制策略[J]. 中国电力, 2025, 58(1): 85-92.
[2]	赵会茹, 姚满宇, 李兵抗, 谢光龙, 丁智华, 胡臻达. 考虑乡村振兴贡献度的农网项目投资决策模型[J]. 中国电力, 2024, 57(6): 181-192.
[3]	任鑫, 王渡, 金亚飞, 王志刚. 基于能耗、经济性及碳排放的热电联产机组运行优化[J]. 中国电力, 2023, 56(4): 201-210.
[4]	祁升龙, 李磊, 何玉鹏, 朱林, 王放, 邹红波. 基于BSSSO算法的无功补偿容量优化方法[J]. 中国电力, 2023, 56(1): 106-111.
[5]	蒋从伟, 欧庆和, 吴仲超, 张健, 杨澍, 朱佳男, 艾芊. 基于联盟博弈的多微网共享储能联合配置与优化[J]. 中国电力, 2022, 55(12): 11-21.
[6]	方彤, 蒋东方, 杨洋, 袁铁江. 基于NSGA-II和熵权法的氢综合能源系统商业运营模式[J]. 中国电力, 2022, 55(1): 110-118.
[7]	张敏, 王金浩, 常潇, 杨超颖, 李冉, 孙昌雯, 樊瑞. 考虑可再生能源不确定性的热-电耦合微能源系统多目标鲁棒规划方法[J]. 中国电力, 2021, 54(4): 119-129,140.
[8]	卢志刚, 乞胜静, 蔡瑶, 马雨薇. 基于改进MOBCC算法的热电联合系统经济环境调度[J]. 中国电力, 2021, 54(2): 164-174.
[9]	李娜, 李朝阳, 周进, 高毅, 洪运福, 游维扬. 考虑投资均衡和效益性的中压配电网投资分配[J]. 中国电力, 2021, 54(12): 143-149.
[10]	蒋怡静, 于艾清, 黄敏丽. 考虑用户满意度的电动汽车时空双尺度有序充电引导策略[J]. 中国电力, 2020, 53(4): 122-130.
[11]	于会群, 尹申, 张浩, 时珊珊, 彭道刚, 蔡国顺. 考虑电动汽车用户满意度的微网分层优化调度策略[J]. 中国电力, 2020, 53(12): 83-91.
[12]	汪磊, 杨贺钧, 马英浩, 张大波. 考虑多重评价指标的多时段分时电价优化模型[J]. 中国电力, 2019, 52(6): 54-59.
[13]	余斌, 尹项根, 吴小忠, 汤吉鸿, 宁春海, 李辉, 朱维钧, 刘海峰, 徐浩. 输电线路在线监测的层次化通信网络规划模型[J]. 中国电力, 2019, 52(3): 161-168.
[14]	王琦, 曲燕, 白建云, 侯鹏飞, 李永茂, 冯赓. 基于GA的背压动态设定值多目标优化研究[J]. 中国电力, 2018, 51(9): 59-64.
[15]	易越, 袁志昌, 郑浩, 史梓男, 马唯婧. 多时间尺度的直流配电网运行优化[J]. 中国电力, 2018, 51(10): 64-71.

模态框（Modal）标题

基于补偿机制的电动汽车区域多维补电优化调度策略

Optimization and Scheduling Strategy for Regional Multi-dimensional Charging of Electric Vehicles Based on Compensation Mechanism

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 17

参考文献 22

相关文章 15

编辑推荐

Metrics