"车-路-网"耦合下含多类型充电桩协同的充电站规划

徐婷婷, 龙羿, 胡晓锐, 李顺, 秦天喜, 张谦

电力建设 ›› 2025

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电力建设 ›› 2025

"车-路-网"耦合下含多类型充电桩协同的充电站规划

  • 徐婷婷1, 龙羿1, 胡晓锐1, 李顺1, 秦天喜2, 张谦2
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A Cooperative Planning Method for Multi-Type Charging Pile Station Based on Vehicle-Road-Network Coupling

  • XU Tingting1, LONG Yi1, HU Xiaorui1, LI Shun1, QIN Tianxi2, ZHANG Qian2
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摘要

【目的】为在电动汽车快速发展背景下响应其呈现的多元化充电需求,研究多类型充电桩协同的充电站规划方法。【方法】本文从电动汽车、交通网和电网的角度,首先,基于图论的思想,建立了车-路-网耦合下的充电站选址定容规划方法;然后详细表征了电动汽车车主的选桩特性,选取慢速充电桩(Slow charging post, SCP)、快速充电桩(Fast charging post, FCP)、移动充电桩(Mobile charging Post, MCP)和超级快速充电桩(Ultra -fast charging post,UCP)作为规划的主要设施,以年化社会总成本最小为目标,建立了含多类充电桩和多条件场景约束的充电站规划模型;再基于条件场景变换和二阶锥松弛方法将规划问题转化为混合整数二阶锥规划问题,并通过Gurobi求解器进行求解;最后,仿真结果有效验证了本文所提模型的高效益和有效性。【结果】结果表明,充分考虑SCP、FCP、UCP和MCP的规划结果最优,且MCP的引入有效发挥了充电需求高峰的应急作用,减少了17.82%的规划成本。【结论】本文所构建的充电站规划模型中,电动汽车车主能够在多类型充电桩中按照一定原则进行选桩,且多类型充电桩的协同配置比单一类型充电桩的规划配置更具有灵活性,能够在满足充电需求的条件下节省年化社会总成本。

Abstract

[Objective] In response to the increasingly diversified charging demands arising from the rapid development of electric vehicle (EV), this paper investigates a planning method for charging stations based on the collaboration of multiple types of charging posts. [Methods] From the perspectives of EVs, transportation networks, and power grids, a siting and sizing planning method for charging stations under vehicle-road-grid coupling is first established based on graph theory. The charging behavior characteristics of EV users are then explicitly modeled, and four types of charging posts—Slow Charging Post (SCP), Fast Charging Post (FCP), Mobile Charging Post (MCP), and Ultra-fast Charging Post (UCP)—are selected as the main facilities. A planning model is constructed with the objective of minimizing the annualized total social cost, incorporating constraints from multiple scenario conditions and multiple charging post types. The planning problem is then reformulated as a Mixed-Integer Second-Order Cone Programming (MISOCP) problem via scenario transformation and second-order cone relaxation techniques, and solved using the Gurobi optimizer. [Results] Simulation results demonstrate the high efficiency and effectiveness of the proposed model. The results indicate that the planning solution considering SCP, FCP, UCP, and MCP is optimal. Notably, the integration of MCPs provides effective emergency response during peak charging demand periods and reduces the overall planning cost by 17.82%. [Conclusions] In the proposed planning model, EV users can select among multiple types of charging posts based on specific principles. The coordinated configuration of diverse charging posts offers greater flexibility compared to single-type configurations, enabling the satisfaction of charging demands while reducing the annualized total social cost.

关键词

车-路-网耦合 / 充电站规划 / 多类充电桩 / 多条件场景约束 / 条件场景变换 / 二阶锥松弛

Key words

vehicle-road-network coupling / charging station planning / multi-category charging piles / multi-conditional scenario constraints / conditional scene transformation / second-order cone relaxation

引用本文

导出引用
徐婷婷, 龙羿, 胡晓锐, 李顺, 秦天喜, 张谦. "车-路-网"耦合下含多类型充电桩协同的充电站规划[J]. 电力建设. 2025
XU Tingting, LONG Yi, HU Xiaorui, LI Shun, QIN Tianxi, ZHANG Qian. A Cooperative Planning Method for Multi-Type Charging Pile Station Based on Vehicle-Road-Network Coupling[J]. Electric Power Construction. 2025

参考文献

[1] 吴佳琦,张谦,吴小汉,等.电动汽车与电网互动的关键问题研究综述[J]. 汽车工程学报,2022,12(04): 411-430.
Wu Jiaqi,Zhang Qian,Wu Xiaohan,et al.A Review of Key Issues in Electric Vehicle and Power Grid Interaction[J]. Chinese Journal of Automotive Engineering,2022,12(4):411-430.
[2] 庞松岭, 赵海龙, 张晨佳. 计及充电需求差异的电动汽车充电设施协同优化配置[J]. 电测与仪表, 2024, 61(12): 171-177.
Pang Songling, Zhao Hailong, Zhang Chenjia.Collaborative optimization configuration of electric vehicle charging facilities considering differences in charging demand[J]. Electrical Measurement & Instrumentation, 2024, 61(12):171-177.
[3] 张怡,郝思鹏. 电动汽车充电站变压器容量及储能优化配置[J]. 电测与仪表, 2023, 60(07): 19-25.
Zhang Yi, Hao Sipeng.Optimized configuration of transformer capacity and energy storage for electric vehicle charging stations[J]. Electrical Measurement & Instrumentation, 2023, 60(7): 19-25.
[4] 王伟杰,黄海宇,徐远途,等. 电动汽车参与主动配电网电压调控的策略研究[J]. 广东电力, 2023, 36(10): 93-104.
Wang Weijie, Huang Haiyu, Xu Yuantu, et al.Strategy research on electric vehicles participating in active distribution network voltage regulation[J]. Guangdong Electric Power, 2023, 36(10): 93-104.
[5] 袁晓冬,曾飞,缪惠宇,等. 电热氢综合能源系统建模及容量规划研究[J]. 高压电器,2024,60(7):34-47.
Yuan Xiaodong, Zeng Fei, Miu Huiyu, et al.Study on Modelling and Capacity Planning of Electric-thermal-Hydrogen Integrated Energy Systems[J]. High voltage apparatus, 2024, 60(7): 34-47.
[6] 林彦旭,高辉. 基于SSA-VMD-BiLSTM模型的充电站负荷预测方法[J]. 广东电力,2024,37(06): 53-61.
Lin Yanxu, Gao Hui.Load Prediction Method of Charging Station Based on SSA-VMD-BiLSTM Model[J]. Guangdong Electric Power, 2024, 37(06): 53-61.
[7] Zhang Q, Qin T, Wu J, et al.Synergistic Operation Strategy of Electric-Hydrogen Charging Station Alliance Based on Differentiated Characteristics[J]. Energy, 2024: 132132.
[8] 曾梦隆,韦钢,朱兰,等. 交直流配电网中电动汽车充换储一体站规划[J]. 电力系统自动化,2021,45(18):52-60.
Zeng Menglong, Wei Gang, Zhu Lan, et al.Planning of Electric Vehicle Charging-Swapping-Storage Integrated Station in AC/DC Distribution Network[J]. Automation of Electric Power Systems, 2021, 45(18):52-60.
[9] 刘东林,王育飞,张宇,等. 基于Huff模型的电动汽车充电站选址定容方法[J]. 电力自动化备,2023,43(11):103-110.
Liu Donglin, Wang Yufei, Zhang Yu, et al.Siting and sizing method of electric vehicle charging stations based on Huff model[J].Electric Power Automation Equipment,2023,43(11):103-110
[10] 潘含芝,于艾清,王育飞,等.均衡不同主体利益的电动汽车充电站选址定容[J]. 现代电力, 2023,40(06): 995-1004.
Pan Hanzhi, Yu Aiqing, Wang Yufei, et al.Site Selection and Capacity Determination of EV Charging Station to Balance Interests of Different Entities[J]. Modern Electric Power, 2023, 40(6): 995-1004.
[11] 葛少云,朱林伟,刘洪,等. 基于动态交通仿真的高速公路电动汽车充电站规划[J]. 电工技术学报,2018,33(13): 2991-3001.
Ge Shaoyun, Zhu Linwei, Liu Hong, et al.Optimal Deployment of Electric Vehicle Charging Stations on the Highway Based on Dynamic Traffic Simulation. Transactions of China Electrotechnical Society, 2018, 33(13): 2991-3001.
[12] 孙雨乐,漆淘懿,赵宇明,等. 路网耦合下计及电动汽车V2G潜力的充电站选址定容研究[J]. 综合智慧能源,2024,46(01): 1-10.
Sun Yule, Qi Taoyi, Zhao Yuming, et al.Siting and sizing of electric vehicle charging stations under the coupling of transport and power networks considering V2G potential[J]. Integrated Intelligent Energy, 2024, 46(1): 1-10.
[13] Wang X, Shahidehpour M, Jiang C, et al.Coordinated planning strategy for electric vehicle charging stations and coupled traffic-electric networks[J]. IEEE Transactions on Power Systems, 2018, 34(1): 268-279.
[14] Hu D, Liu Z W, Chi M.Multiple periods location and capacity optimization of charging stations for electric vehicle[C]//2019 China-Qatar International Workshop on Artificial Intelligence and Applications to Intelligent Manufacturing (AIAIM). IEEE, 2019: 17-21.
[15] 刘志强,张谦,朱熠,等. 计及车-路-站-网融合的电动汽车充电负荷时空分布预测[J]. 电力系统自动化,2022,46(12):36-45.
Liu Zhiqiang, Zhang Qian, Zhu Yi, et al.Spatial-Temporal Distribution Prediction of Charging Loads for Electric Vehicles Considering Vehicle-Road-Station-Grid Integration[J]. Automation of Electric Power Systems, 2022, 46(12):36-45.
[16] 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(3): 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(3): 21-30.
[17] 杨楠,梁金正,丁力,等.考虑改造扩建和安全效能成本的光储一体化充电站规划方法[J]. 电网技术, 2023,47(09): 3557-3569.
Yang Nan, Liang Jinzheng, Ding Li, et al.Integrated Optical Storage Charging Considering Reconstruction Expansion and Safety Efficiency Cost. Power System Technology. 2023, 47(9): 3557-3567.
[18] 肖白,高峰.含不同容量充电桩的电动汽车充电站选址定容优化方法[J]. 电力自动化设备,2022, 42(10): 157-166.
Xiao Bai,Gao Feng.Optimization method of electric vehicle charging stations' site selection and capacity determination considering charging piles with different capacities[J].Electric Power Automation Equipment,2022,42(10): 157-166.
[19] 胡晓伟,宋帅,邱振洋,等.寒区电动公交充电站选址及定容规划研究[J]. 交通运输系统工程与息,2024,24(02):281-292.
Huxiaowei, Song Shuai, Qiu Zhenyang, et al. Location and Capacity Planning of Electric Bus Charging Station in Cold Regions[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 281-292.
[20] Luo C, Huang Y F, Gupta V.Placement of EV charging stations—Balancing benefits among multiple entities[J]. IEEE Transactions on Smart Grid, 2017, 8(2): 759-768.
[21] 董晓红,穆云飞,于力,等.考虑配网潮流约束的高速公路快速充电站校正规划方法[J]. 电力自动化备, 2017,37(06): 124-131.
Dong Xiaohong, Mu Yunfei, Yu Li, et al.Freeway FCS planning and correction considering power-flow constraints of distribution network[J].Electric Power Automation Equipment,2017,37(6): 124-131.
[22] 蔡海青,代伟,赵静怡,等. 基于多参数规划的电动汽车充电站有效容量评估方法[J]. 中国电力, 2022,55(11): 175-183.
Cai Haiqing, Dai Wei, Zhao Jingyi, et al.Available Capacity Evaluation Method of Electric Vehicle Charging Stations Based on Multi-parametric Programming[J]. Electric Power, 2022, 55(11): 175-183.
[23] 卢慧,谢开贵,邵常政,等.考虑燃油车和电动汽车动态混合交通流的电动汽车充电站规划. 高电压技术. 2023,49(3): 1150-1160.
Lu Hui, Xie Kaigui, Shao Changzheng, et al.Charging Station Planning with the Dynamic and Mixed Traffic Flow of Gasoline and Electric Vehicles. High Voltage Engineering. 2023, 49(3): 1150-1160.
[24] 张美霞,张倩倩,杨秀,等.基于交通-电力均衡耦合的电动汽车快充站与配电网联合规划[J]. 电力系统保护与控制,2023,51(11): 51-63.
Zhang Meixia, Zhang Qianqian, Yang Xiu, et al.Joint planning of electric vehicle fast charging stations and distribution network based on atraffic-electricity equilibrium coupling model[J]. Power System Protection and Control,2023,51(11):51-63
[25] 王阳,刘希喆. 光储充电站经济调度规划与容量配置分析[J]. 南方电网技术, 2022,16(11): 1-8.
Wang Yang, Liu Xizhe.Economic Dispatching Planning and Capacity Allocation Analysis of Photovoltaic-Storage Charging Station[J]. Southern Power System Technology, 2022, 16(11):1-8.
[26] 林思瑶,马晓,贺坤,等. 不确定环境下基于动态税和电动汽车时空灵活性的配电网阻塞管理方法[J]. 山东电力技术,2025,52(01): 12-27.
Lin Siyao, Ma Xiao, He Kun Et Al. Distribution Networks Congestion Management Based on Dynamic Tariff and Temporal-spatial Flexibility of Electric Vehicles Under Uncertainty[J]. Shandong Electric Power, 2025, 52(01): 12-27.
[27] 周燕,刘卫民,陈帆,等.不同光伏渗透率下考虑需求响应的配电网储能双层规划[J].高压电器,2024,60(10):64-77.
Zhou Yan, Liu Weimin, Chen Fan, et al.Bi-level Planning of Energy Storage in Distribution Network Considering Demand Response Under Different Penetration Rates of Photovoltaic[J]. High voltage apparatus, 2024, 60(10): 64-77.
[28] 赵子鋆,彭清文,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(3):283-291.
Zhao Zijun, Peng Qingwen, 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(3):283-291.
[29] 吴豫,董智,赵阳,等. 基于LSTM算法的配电网分布式电源和电动汽车充电站联合优化规划[J]. 供用电,2023,40(06): 64-74.
Wu Yu, Dong Zhi, Zhao Yang, et al.Joint optimization planning of distribution network DG and EV charging station based on LSTM algorithm[J]. Distribution & Utilization,2023,40(6):64-74.
[30] 黄婧杰,李金成,刘科明,等. 含CVaR及增广ε-约束法的多目标光储充电站容量优化配置[J]. 南方电网技术,2023,17(10): 94-103.
Huang Jingjie, Li Jincheng, Liu Keming, et al.Optimal Allocation of Multi-Objective Photovoltaic Energy Storage Charging Station Capacity with CVaR and Augmented ε-Constraint Method[J]. Southern Power System Technology,2023,17(10):94-103.
[31] Liu X.Bi-level planning method of urban electric vehicle charging station considering multiple demand scenarios and multi-type charging piles[J]. Journal of Energy Storage, 2022, 48: 104012.
[32] Yin W, Ji J, Qin X.Study on optimal configuration of EV charging stations based on second-order cone[J]. Energy, 2023, 284: 128494.
[33] 刘昊邦,马辉,熊致知. 基于Voronoi图重心内插法的虚拟惯量配置[J]. 电力系统自动化, 2020,44(03): 66-73.
Liu Haobang, Ma Hui, Xiong Zhizhi.Virtual Inertia Configuration Based on Voronoi Diagram and Center of Gravity Interpolation[J]. Automation of Electric Power Systems, 2020, 44(3):66-73.
[34] 麻秀范,王皓, 李颖,等. 基于变权Voronoi图和混合粒子群算法的电动汽车充电站规划[J]. 电工技术学报, 2017, 32(19): 160-169.
Ma Xiufan, Wang Hao, Li Ying, et al.Optimal Planning of Charging Stations for Electric Vehicle Based on Weight-Changed Voronoi Diagram and Hybrid Particle Swarm Optimization Algorithm. Transactions of China Electrotechnical Society, 2017, 32(19): 160-169.
[35] Huang W, Sun K, Qi J, et al.Optimal allocation of dynamic var sources using the Voronoi diagram method integrating linear programing[J]. IEEE Transactions on Power Systems, 2017, 32(6): 4644-4655.
[36] Luo L, Gu W, Zhou S, et al.Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities[J]. Applied energy, 2018, 226: 1087-1099.
[37] Zhang H, Hu Z, Xu Z, et al.An integrated planning framework for different types of PEV charging facilities in urban area[J]. IEEE Transactions on Smart Grid, 2016, 7(5): 2273-2284.

基金

国家自然科学基金项目(52277081); 国网重庆市电力公司重点科技项目资助(52200023008)

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