[1]王大伟,许宏科,代 亮,等.高速公路移动储能车调度策略[J].长安大学学报(自然科学版),2025,45(4):177-188.[doi:10.19721/j.cnki.1671-8879.2025.04.015]
 WANG Da-wei,XU Hong-ke,DAI Liang,et al.Scheduling strategy for expressway mobile energy storage vehicles[J].Journal of Chang’an University (Natural Science Edition),2025,45(4):177-188.[doi:10.19721/j.cnki.1671-8879.2025.04.015]
点击复制

高速公路移动储能车调度策略()
分享到:

长安大学学报(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
第45卷
期数:
2025年4期
页码:
177-188
栏目:
交通工程
出版日期:
2025-07-30

文章信息/Info

Title:
Scheduling strategy for expressway mobile energy storage vehicles
文章编号:
1671-8879(2025)04-0177-12
作者:
王大伟12许宏科1代 亮1李积伟1
(1. 长安大学 电子与控制工程学院,陕西 西安 710064; 2. 洛阳师范学院 物理与电子信息学院, 河南 洛阳 471934)
Author(s):
WANG Da-wei12 XU Hong-ke1 DAI Liang1 LI Ji-wei1
(1. School of Electronics and Control Engineering, Chang'an University, Xi'an 710064, Shaanxi, China; 2. College of Physics & Electronic Information, Luoyang Normal University, Luoyang 471934, Henan, China)
关键词:
交通工程 移动储能车 柔性负荷 可再生能源发电 高速公路
Keywords:
traffic engineering mobile energy storage vehicle flexible load renewable energy generation expressway
分类号:
U469.72
DOI:
10.19721/j.cnki.1671-8879.2025.04.015
文献标志码:
A
摘要:
为解决高速公路沿线柔性负荷与可再生能源发电之间的电能供需不平衡问题,提出一种移动储能车调度策略。该策略利用高速公路管理中心可再生能源发出的电能,为移动储能车装载的储能电池组进行充电,随后调度这些移动储能车前往高速公路服务区,为柔性负荷提供绿色能源。考虑高速公路系统的交通及能源特性,建立移动储能车的时空-储能约束方程。为求解移动储能车的最优行驶路线以及合理的充放电策略,模型被构建为混合整数二次约束规划问题,旨在最大化移动储能车的供电净收益,同时兼顾高速公路行驶成本以及储能电池组的充放电损耗花费。在包含4个服务区、1个管理中心以及5辆移动储能车的高速公路系统中,对所提出的调度策略进行了仿真验证。研究结果表明:所提出的调度策略有效实现了高速公路管理中心可再生能源发电的收集及再分配; 相较于2个对比案例,该策略在可再生能源消纳方面表现最为优越,消纳总量达到了3 167 kW·h,在满足服务区柔性负荷供电需求方面亦展现出了最佳性能,供电需求满足率达到45%。研究结果为高速公路运营管理部门提供了科学依据和理论指导,有助于其解决用电需求与绿色供能之间的区域不平衡问题,进而推动高速公路交通与能源系统的融合发展。
Abstract:
To address the supply and demand imbalance between flexible loads along expressways and renewable energy generation, a scheduling strategy for mobile energy storage vehicles(MESVs)was proposed. This strategy utilized the electricity generated from renewable energy at the expressway management center(EMC)to charge the storage battery packs of MESVs. These MESVs were then dispatched to expressway service areas(EMAs)to supply green energy to flexible loads. Considering the traffic and energy characteristics of the expressway system, the spatiotemporal-storage constraint equations for MESVs were established. The model was formulated as a mixed-integer quadratic constraint programming problem to solve for the optimal route and charging/discharging strategies, aiming to maximize the net energy supply benefit while balancing costs from expressway driving and storage battery pack losses. The proposed scheduling strategy was validated in an expressway system that includes four ESAs, one EMC, and five MESVs. The results show that the strategy effectively achieves the collection and redistribution of renewable energy at the EMC. Compared with the two comparative cases, the proposed strategy demonstrates superior performance in renewable energy utilization, achieving a total consumption of 3 167 kW·h. It also shows the best performance in meeting the power supply demands of flexible loads in ESAs, with a demand satisfaction rate of 45%. The findings provide a scientific basis and theoretical guidance for expressway operation and management departments to address the regional imbalance between energy demand and green energy supply, contributing to the integrated development of expressway transportation and energy systems.5 tabs, 13 figs, 25 refs.

参考文献/References:

[1] SONG J, HE G, WANG J, et al. Shaping future low-carbon energy and transportation systems: Digital technologies and applications[J]. Energy, 2022, 1(3): 285-305.
[2]LUO C, HUANG Y F, GUPTA V. Stochastic dynamic pricing for EV charging stations with renewable integration and energy storage[J]. IEEE Transactions on Smart Grid, 2018, 9(2): 1494-1505.
[3]ABDELTAWAB H, MOHAMED Y A R I. Mobile energy storage sizing and allocation for multi-services in power distribution systems[J]. IEEE Access, 2019, 7: 176613-176623.
[4]WANG Y, QIU D, STRBAC G. Multi-agent deep reinforcement learning for resilience-driven routing and scheduling of mobile energy storage systems[J]. Applied Energy, 2022, 310: 118575.
[5]YU J, LU J. Slope stability analysis of expressway subgrade with photovoltaic facilities[C]//IEEE. Proceedings of the 8th International Conference on Hydraulic and Civil Engineering: Deep Space Intelligent Development and Utilization Forum(ICHCE). New York: IEEE, 2023: 588-593.
[6]QIN X, SHEN Y, SHAO S. The application study in solar energy technology for highway service area: A case study of West Lushan highway low-carbon service area in China[J]. International Journal of Photoenergy, 2015, 2015: 1-8.
[7]王 飚,赵微微,林少军,等.基于改进的多目标量子遗传算法的高速服务区综合能源管理[J].电网技术,2022,46(5):1742-1751.
WANG Biao, ZHAO Wei-wei, LIN Shao-jun, et al. Integrated energy management of highway service area based on improved multi-objective quantum genetic algorithm[J]. Power System Technology, 2022, 46(5): 1742-1751.
[8]王宁玲,杨超云,王家奇,等.基于能源枢纽建模的高速公路综合能源系统多目标运行优化研究[J/OL].华北电力大学学报(自然科学版),2023:1-12[2023-11-09].https://link.cnki.net/urlid/13.1212.TM.20231108.1111.004.
WANG Ning-ling, YANG Chao-yun, WANG Jia-qi, et al. Research on multi-objective operation optimization of highway integrated energy system basedon energy hub[J/OL]. Journal of North China Electric Power University(Natural Science Edition), 2023:1-12[2023-11-09].https://link.cnki.net/urlid/13.1212.TM.20231108.1111.004.
[9]HOU L Y, YAN J, WANG C, et al. A simultaneous multi-round auction design for scheduling multiple charges of battery electric vehicles on highways[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 8024-8036.
[10]LV S, WEI Z N, SUN G Q, et al. Power and traffic nexus: From perspective of power transmission network and electrified highway network[J]. IEEE Transactions on Transportation Electrification, 2021, 7(2): 566-577.
[11]DING Z, ZHANG Y, TAN W, et al. Pricing based charging navigation scheme for highway transportation to enhance renewable generation integration[J]. IEEE Transactions on Industry Applications, 2023, 59: 108-117.
[12]ZHANG T Y, YAO E J, YANG Y, et al. Deployment optimization of battery swapping stations accounting for taxis' dynamic energy demand[J]. Transportation Research Part D: Transport and Environment, 2023, 116: 103617.
[13]ZHANG T Y, YANG Y, ZHU Y T, et al. Deploying public charging stations for battery electric vehicles on the expressway network based on dynamic charging demand[J]. IEEE Transactions on Transportation Electrification, 2022, 8(2): 2531-2548.
[14]YAN J, LAI F X, LIU Y Q, et al. Multi-stage transport and logistic optimization for the mobilized and distributed battery[J]. Energy Conversion and Management, 2019, 196: 261-276.
[15]KIM J, DVORKIN Y. Enhancing distribution system resilience with mobile energy storage and microgrids[J]. IEEE Transactions on Smart Grid, 2019, 10(5): 4996-5006.
[16]ZHANG L, YU S, ZHANG B, et al. Outage management of hybrid AC/DC distribution systems: Co-optimize service restoration with repair crew and mobile energy storage system dispatch[J]. Applied Energy, 2023, 335: 120422.
[17]ABDELTAWAB H H, MOHAMED Y. Mobile energy storage scheduling and operation in active distribution systems[J]. IEEE Transactions on Industrial Electronics, 2017, 64(9): 6828-6840.
[18]KWON S Y, PARK J Y, KIM Y J. Optimal V2G and route scheduling of mobile energy storage devices using a linear transit model to reduce electricity and transportation energy losses[J]. IEEE Transactions on Industry Applications, 2020, 56(1): 34-47.
[19]SABOORI H, JADID S. Mobile and self-powered battery energy storage system in distribution networks: Modeling, operation optimization, and comparison with stationary counterpart[J]. Journal of Energy Storage, 2021, 42: 103068.
[20]XU Y, WANG Y, HE J H, et al. Resilience-oriented distribution system restoration considering mobile emergency resource dispatch in transportation system[J]. IEEE Access, 2019, 7: 73899-73912.
[21]YAO S H, WANG P, LIU X C, et al. Rolling optimization of mobile energy storage fleets for resilient service restoration[J]. IEEE Transactions on Smart Grid, 2020, 11(2): 1030-1043.
[22]QU Z L, CHEN J J, PENG K, et al. Enhancing stochastic multi-microgrid operational flexibility with mobile energy storage system and power transaction[J]. Sustainable Cities and Society, 2021, 71: 102962.
[23]MISHRA D K, GHADI M J, LI L, et al. Active distribution system resilience quantification and enhancement through multi-microgrid and mobile energy storage[J]. Applied Energy, 2022, 311: 118665.
[24]NIU M B, WANG H C, LI J, et al. Coordinated energy dispatch of highway microgrids with mobile storage system based on DMPC optimization[J]. Electric Power Systems Research, 2023, 217: 109119.
[25]DING Y, QU G, CHEN X, et al. Deep reinforcement learning-based spatiotemporal decision of utility-scale highway portable energy storage systems[J]. IEEE Transactions on Industry Applications, 2023, 60(1): 1-10.

相似文献/References:

[1]王建伟,李娉,高洁,等.中国交通运输碳减排区域划分[J].长安大学学报(自然科学版),2012,32(01):0.
[2]李曙光,周庆华.具有破坏排队的离散时间动态网络装载算法[J].长安大学学报(自然科学版),2012,32(01):0.
[3]凌海兰,郗恩崇.基于随机波动条件的公交客运量预测模型[J].长安大学学报(自然科学版),2012,32(01):0.
[4]田娥,肖庆,陆小佳,等.安全驾驶的横向安全预警报警阈值的确定[J].长安大学学报(自然科学版),2012,32(01):0.
[5]侯贻栋,赵炜华,魏 朗,等.驾驶人空间距离判识规律心理学分析[J].长安大学学报(自然科学版),2012,32(03):86.
 HOU Yi-dong,ZHAO Wei-hua,WEI Lang,et al.Analysis on psychology in cognitive distance about drivers[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):86.
[6]赵跃峰,张生瑞,魏 华.隧道群路段运行速度特性分析[J].长安大学学报(自然科学版),2012,32(06):67.
 ZHAO Yue-feng,ZHANG Sheng-rui,WEI hua.Operating speed characteristics of tunnel group section[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):67.
[7]林 杉,许宏科,刘占文.一种高速公路隧道交通流元胞自动机模型[J].长安大学学报(自然科学版),2012,32(06):73.
 LIN Shan,XU Hong-ke,LIU Zhan-wen.One cellular automaton traffic flow model for expressway tunnel[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):73.
[8]刘俊德,徐 兵,梁永东,等.交通事故下高速公路行车安全评估[J].长安大学学报(自然科学版),2012,32(06):78.
 LIU Jun-de,XU bing,LIANG Yong-dong,et al.Traffic safety assessment of expressway in the accident[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):78.
[9]芮海田,吴群琪,赵跃峰,等.公路建设对区域经济发展的影响分析——以陕西省为例[J].长安大学学报(自然科学版),2012,32(06):83.
 RUI Hai-tian,WU Qun-qi,ZHAO Yue-feng,et al.Influence of highway construction on regional economy development——taking Shaanxi as an example[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):83.
[10]彭 辉,续宗芳,韩永启,等.城市群城际运输结构配置客流分担率模型[J].长安大学学报(自然科学版),2012,32(02):91.
 PENG Hui,XU Zong-fang,HAN Yong-qi,et al.Sharing ratios model of passenger flows in intercity transportation structure configuration among urban agglomeration[J].Journal of Chang’an University (Natural Science Edition),2012,32(4):91.

备注/Memo

备注/Memo:
收稿日期:2024-12-31
基金项目:国家重点研发计划项目(2021YFB2601401)
作者简介:王大伟(1989-),男,河南洛阳人,讲师,工学博士,E-mail:dwei1523900@163.com。
通信作者:代 亮(1981-),男,陕西安康人,教授,工学博士,E-mail:ldai@chd.edu.cn。
更新日期/Last Update: 2025-07-25