Study on Optimal Charging and Discharging Strategies for Electric Vehicle Clusters Taking into Account Power Peak Shaving

ZHAO Linxin; LI Chengxin; GUI Jiangyi; LIU Lin

PDF(1169 KB)

Electric Power Construction ›› 2025

Study on Optimal Charging and Discharging Strategies for Electric Vehicle Clusters Taking into Account Power Peak Shaving

ZHAO Linxin¹, LI Chengxin¹, GUI Jiangyi², LIU Lin¹

Author information +

History +

Abstract

[Objective] In a “source-grid-load-storage” system incorporating renewable energy, an electric vehicle (EV) cluster charging and discharging strategy optimization model is established to optimize the revenues of EV users and load aggregators participating in peak shaving ancillary services, considering the peak shaving demand levels across different time periods. [Methods] First, the peak shaving demand for each time period under renewable energy production scenarios is assessed. Second, based on the level of peak shaving demand in each time period, an optimization model for the charging and discharging strategy of the EV cluster is developed with the objective of maximizing the total expected revenue for both load aggregators and EV users. Finally, to prevent peak load occurrences after participating in peak shaving services, the charging and discharging strategy for subsequent time periods is optimized with the goal of minimizing load fluctuations. [Results] Case analysis demonstrates that the proposed charging and discharging strategy can assist in smoothing electricity load during peak periods, maximize the total expected revenue for load aggregators and EV users, and mitigate the occurrence of load peaks after participating in peak shaving services. [Conclusions] The proposed strategy in this paper significantly improves the benefits of EV users and load aggregators compared to the strategy without considering participation in peak shaving service, and the load fluctuations in the subsequent period of peak shaving is significantly reduced, which verifies the practicality and effectiveness of the proposed method.

Key words

source-grid-load-storage system / the revenues of EV users and load aggregators / peak shaving ancillary services / electric vehicle (EV) cluster charging and discharging strategy optimization / load peaks

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

ZHAO Linxin, LI Chengxin, GUI Jiangyi, LIU Lin. Study on Optimal Charging and Discharging Strategies for Electric Vehicle Clusters Taking into Account Power Peak Shaving[J]. Electric Power Construction. 2025

References

[1] 孙惠, 翟海保, 吴鑫. 源网荷储多元协调控制系统的研究及应用[J]. 电工技术学报, 2021, 36(15):3264-3271.
SUN Hui, Zhai Haibao, WU Xin.Research and application of multi-energy coordinated control of generation, network, load and storage[J]. Transactions of China Electrotechnical Society, 2021, 36(15): 3264-3271.
[2] 唐文虎,聂欣昊,钱瞳,等.面向新型电力系统安全稳定的储能应用技术研究综述与展望[J].广东电力,2024,37(12):3-15.
TANG Wenhu, NlE Xinhao, QlAN Tong, et al. Review and Prospect on Application Technologies of Energy Storage for Safety and Stability of New Power System[J]. Guangdong Electric Power,2024,37(12):3-15.
[3] 赵冬梅,宋晨铭,冯向阳,等.100%新能源场景下考虑频率稳定约束的源网荷储一体化系统储能优化配置[J/OL].电工技术学报,1-16[2024-07-24].
ZHAO Dongmei, SONG Chenmin, FENG Xiangyang, et al.The Optimal Configuration of Energy Storage in the Source-Grid-Load-Storage Integrated System Considering Frequency Stability Constraints in 100% New Energy Scenarios[J/OL]. Transactions of China Electrotechnical Society,1-16[2024-07-24].
[4] 姚建国,杨胜春,王珂,等.智能电网“源-网-荷”互动运行控制概念及研究框架[J]. 电力系统自动化,2012,36(21):6-11.
YAO Jianguo, YANG Jianchun, WANG Ke, et al.Concept and research framework of smart grid “Source-Gride-Load” interactive operation and control[J]. Automation of Electric Power Systems, 2012, 36(21):6-11.
[5] 王琼,邹晴,李乐,等.基于多智能体强化学习的电动汽车充放电调控算法[J].供用电,2023,40(09):83-90.
WANG Qiong, ZOU Qing, LI Le, et al.Multi-agent reinforcement learning algorithm for charging/discharging control of electric vehicles[J]. Distribution & Utilization, 2023,40(09):83-90.
[6] 程慧琳,武剑,张晶,等.计及电动汽车充放电时空分布的输配网协同降损低碳策略研究[J].电测与仪表,2024,61(11):122-132.
CHENG Huilin,WU Jian,ZHANG Jing, LI Yanlin, SHl Benbo, LU Zhigang et al. Research on the low-carbon strategy of coordinated loss reduetion of transmissionand distribution network considering the temporal-spatialdistribution of EV charging and discharging[J]. Electrical Measurement & Instrumentation, 2024,61(11):122-132.
[7] 张琳娟,周志恒,陈婧华,等.含电动汽车的县域光伏台区储能容量优化配置研究[J].供用电,2024,41(10):101-113.
ZHANG Linjuan, ZHOU Zhiheng,CHEN Jinghua, et al.Research on optimal allocation of energy storage capacity in county photovoltaic distribution station area with electric vehicles[J]. Distribution & Utilization,2024,41(10):101-113.
[8] 吴永孝,肖辉,曾林俊,等.考虑供需双边响应的综合能源系统优化调度[J].电力建设,2024,45(10):13-23.
WU Yongxiao, XIAO Hui, ZENG Linjun, et al.Optimal Scheduling of Integrated Energy Systems Considering Bilateral
9 Response of Supply and Demand[J]. Electric Power Construction,2024,45(10):13-23.
[9] 陈文颖,刘蓓迪.基于粒子群算法的电动汽车有序充放电优化[J].山东电力技术,2023,50(01):52-58.
CHEN Wenying, LIU Beidi.Sequential Charging and Discharging Optimization of Electric Vehicles Based on Particle Swarm Optimization[J]. Shandong Electric Power, 2023,50(01):52-58.
[10] 杨康,石璐杉,周航,等.含电动汽车集群的微电网多时间尺度优化调度[J].分布式能源,2024,9(03):21-30.
YANG Kang, SHI Lushan, ZHOU Hang, et al.Multi-Time Scale Optimization Scheduling for Microgrids Containing Electric Vehicle Clusters[J]. Distributed Energy,2024,9(03):21-30.
[11] 刘浠流,陈冠霖,吴宁,等.考虑电动汽车充放电模式灵活性的配电网日前优化调度方法[J].分布式能源,2023,8(04):46-54.
LIU Xiliu, CHEN Guanlin, WU Ning, et al.Day-Ahead Optimal Scheduling Considering the Flexibility of EV Charging and Discharging Modes[J]. Distributed Energy, 2023,8(04):46-54.
[12] 侯永全,徐敦彬,袁晓冬,等.基于博弈论的含氢微网多主体能源系统优化配置[J].高压电器,2024,60(07):48-59.
HOU Yongquan, XU Dunbin, YUAN Xiaodong, et al.Optimized Allocation of Hydrogen-containing Micro Grid Multi-subject Energy System Based on Game Theory[J]. High Voltage Apparatus,2024,60(07):48-59.
[13] 赵子鋆,胡湘伟,邓亚芝,等.考虑电动汽车充电与常规负荷时空相关性的配电网可开放容量评估[J].全球能源互联网,2024,7(03):283-291.
ZHAO Zijun, HU Xiangwei, DENG Yazhi, et al.Distribution Network Available Capacity Evaluation Considering the Spatiotemporal Correlation of Electric Vehicles Charging Loads and Base Loads[J]. Journal of Global Energy Interconnection,2024,7(03):283-291.
[14] 陈图南,李文萱,李云,等.“双碳”背景下碳-绿证-电力市场耦合机制综述[J].广东电力,2024,37(08):14-25.
CHEN Tunan, LI Wenxuan, LI Yun, et al.Review on Coupling Mechanism of Carbon, Green Certificate and Power Market Under the Background of Carbon Peaking and Carbon Neutrality[J]. Guangdong Electric Power,2024,37(08):14-25.
[15] 葛乐,王庆园,王明深,等.考虑充放电激励机制的电动汽车聚合商参与能量-调频市场多阶段运营策略[J/OL].电力自动化设备,1-9[2024-02-26].
GE Le, WANG Qingyuan, WANG Mingshen, et al.Multi-stage operation strategy of electric vehicle aggregator participating in energy and frequency regulation markets considering charging and discharging incentive mechanisms[J/OL]. Electric Power Automation Equipment,1-9[2024-02-26].
[16] LIU H, QI J J, WANG J H, et al.EV dispatch control for supplementary frequency regulation considering the expectation of EV owners[J]. IEEE Transactions on Smart Grid, 2018, 9(4): 3763-3772.
[17] 侯慧,何梓姻,罗超,等.计及需求响应潜力的电动汽车聚合商多主体日前投标策略[J].全球能源互联网,2024,7(02):220-227.
HOU Hui, HE Ziyin, LUO Chao, et al.Multi-agent Day-ahead Bidding Strategy of Electric Vehicle Aggregators Upon Demand Response Potential[J]. Journal of Global Energy Interconnection,2024,7(02):220-227.
[18] 戴朝华,杨帅,叶圣永,等.供需双方博弈视角下的V2G优化策略[J/OL].西南交通大学学报,1-10[2024-06-27].
DAI Chaohua, YANG Shuai, YE Shengyong, et al.V2G Optimization Strategy from the Perspective of Supply and Demand Game [J/OL]. Journal of Southwest Jiaotong University.1-10[2024-06-27].
[19] 周志恒,张琳娟,王晓冬,等.计及多种弹性资源储能潜力挖掘的居民台区优化调度策略[J/OL].南方电网技术,1-13[2024-10-13].
ZHOU Zhiheng, ZHANG Linjuan, WANG Xiaodong, et al.Optimal Scheduling Strategy of Residential Station Area Considering the Potential Mining of Energy Storage of Various Elastic Resources[J/OL]. Southern Power System Technology,1-13[2024-10-13].
[20] 李晨朝,陈佳佳,王敬华.基于主从博弈和IGDT的含电动汽车需求响应光伏园区储能优化配置[J/OL].电力建设,1-13[2024-10-17].
Ll Chenzhao, CHEN Jiajia, WANG Jinghua.Optimal Configuration of Energy Storage in Photovoltaic Park with Electric Vehicle Demand Response Based on Stackelberg Game and lGDT[J/OL]. Electric Power Construction, ,1-13[2024-10-17].
[21] 高爽,戴如鑫.电动汽车集群参与调频辅助服务市场的充电调控策略[J].电力系统自动化,2023,47(18):60-67.
GAO Shuang, DAI Ruxin.Charging control strategy for electric vehicle aggregation participating in frequency regulation ancillary service market[J]. Automation of Electric Power Systems, 2023, 47(18):60-67.
[22] 房宇轩,胡俊杰,马文帅.计及用户意愿的电动汽车聚合商主从博弈优化调度策略[J].电工技术学报,2024,39(16):5091-5103.
FANG Yuxuan, HU Junjie, MA Wenshuai.Optimal Dispatch Strategy for Electric Vehicle Aggregators Based on Stackelberg Game Theory Considering User Intention[J]. Transactions of China Electrotechnical Society, 2024, 39(16):5091-5103.
[23] 程飞,郭春林,高泽阳,等.参与电网削峰调节的电动重卡换电站调度策略[J/OL].电力系统自动化,1-11[2024-04-15].
CHENG Fei, GAO Chunlin, Gao zeyang, et al. Scheduling strategy of battery swapping stations for electric heavy duty trucks participating in power grid peak shaving regulation[J/OL].Automation of Electric Power Systems, 1-11[2024-04-15].
[24] 李军,梁嘉诚,刘克天,等.计及用户响应度的电动汽车充放电优化调度策略[J].南方电网技术,2023,17(08):123-132.
LI Jun, LIANG Jiacheng, LIU Ketian, et al.Optimal Scheduling Strategy for Electric Vehicles Charging and Discharging Considering User Responsiveness[J]. Southern Power System Technology, 2023, 17(08):123-132.
[25] 赵鹏翔,丛琳,窦真兰,等.基于综合需求响应的大学城综合能源系统尖峰负荷平抑策略[J/OL].电测与仪表:1-10[2024-06-24].
ZHAO Pengxiang, CONG Lin, DOU Zhenlan, et al.An integrated demand response-based spike load smoothing strategy for the integrated energy system of the university city[J/OL]. Electrical Measurement & Instrumentation :1-10[2024-06-24].
[26] 贾宏杰,王丹,徐宪东,等.区域综合能源系统若干问题研究[J].电力系统自动化,2015,39(07):198-207.
JIA Hongjie, WANG Dan, XU Xiandong, et al.Research on some key problems related to integrated energy systems[J]. Automation of Electric Power Systems, 2015, 39(07):198-207.
[27] 辛昊,严正,许少伦.基于多代理系统的电动汽车协调充电策略[J].电网技术,2015,39(01):48-54.
XIN Hao, YAN Zheng, XU Shao lun. Multi-agent system based coordinated charging strategy for electric vehicles[J]. Power System Technology, 2015, 39(01):48-54.
[28] 张婷婷. 考虑经济物理约束的电动汽车负荷聚合可调节容量评估[D].华北电力大学,2022.
ZHANG Tingting.Estimation of adjustable capacity of EV load aggregation considering economic and physical constraints[D]. North China Electric Power University,2022.
[29] 臧汉洲,叶宇剑,汤奕.基于内点策略优化的受约束电动汽车充放电策略[J].电网技术,2023,47(10):4170-4180.
ZANG Hanzhou, YE Yujian, TANG Yi.Constrained Electric Vehicle Charging and Discharging Strategy Based on Interior-point Policy Optimization. Power System Technology, 2023, 47(10):4170-4180.
[30] 沈赋,曹旸,徐潇源,等.高比例可再生能源电力系统惯量预测方法研究综述[J/OL].电力建设,1-15[2024-10-17].
SHEN Fu, CAO Yang, XU Xiaoyuan, et al.A Review of Inertia Prediction Methods for Power System with High Penetration Renewable Energy Sources[J/OL]. Electric Power Construction, 1-15[2024-10-17].
[31] 王守相,陈海文,李小平,等.风电和光伏随机场景生成的条件变分自动编码器方法[J]. 电网技术, 2018, 42(06):1860-1869.
WANG Shouxiang, CHEN Haiwen, LI Xiaoping, et al.Conditional variational autoencoder method for random scene Generation of wind power and photovoltaics[J]. Power System Technology, 2018, 42(06): 1860-1869 (in Chinese).
[32] 惠振国,艾澜,常鹏霞,等.计及风光出力相关性的风光水储互补系统优化调度[J/OL].水电能源科学,2024,(08):218-222[2024-07-16].
HUI Zhenguo, AI Lan, CHANG Pengxia, et al. Optimal Scheduling of Wind-Solar-Water-Storage Complementary System Considering the Correlation of Wind-Solar Output[J/OL]. Water Resources and Power, 2024, (08):218-222[2024-07-16].
[33] 李鹏,朱洪泽,骆光杰,等.基于ARMA模型的海上风机随机风场模拟[J].武汉大学学报(工学版),2024,57(01):112-120.
LI Peng, ZHU Hongze, LUO Guangjie, et al.Simulation of Stochastic Wind Field for Offshore Wind Turbines Based on ARMA Model[J]. Engineering Journal of Wuhan University, 2024, 57(01):112-120.
[34] 董文略,王群,杨莉.含风光水的虚拟电厂与配电公司协调调度模型[J].电力系统自动化,2015,39(09):75-81+207.
DONG Wenlue, WANG Qun, YANG Li. Wireless Coordination Control of Multi-functional Grid-tied Inverters in Microgrid[J]. Automation of Electric Power Systems, 2015, 39(09):75-81+207.
[35] U.S. Department of transportation, federal highway administration.2017 national household travel survey[R/OL].
[36] NEUBAUER J, WOOD E.The impact of range anxiety and home, workplace,and public charging infrastructure on simulated battery electric vehicle lifetime utility[J]. Journal of Power Sources, 2014, 257(3):12-20.