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Journal of Tsinghua University(Science and Technology)    2022, Vol. 62 Issue (7) : 1163-1177,1219     DOI: 10.16511/j.cnki.qhdxxb.2022.26.017
Research Article |
Optimizing the deployment of charging systems on an expressway network considering the construction time sequence and the dynamic charging demand
YANG Yang1, ZHANG Tianyu1, ZHU Yuting2, YAO Enjian1
1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China;
2. School of E-business and Logistics, Beijing Technology and Business University, Beijing 100048, China
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Abstract  A bi-level optimization model was developed for planning charging facility deployment on an intercity highway network. The model balances the variable charging demand and the construction time sequence. The lower model is based on a dynamic traffic assignment model. The spatial-temporal distribution of the charging demand at equilibrium was obtained from simulations of multi-user driving and charging behavior. The upper model optimizes the charging station's locations and capacities using construction time sequence and level of service (LOS) constraints to minimize the operator investment. The model is then used to analyze the intercity highway network between Jinan and Qingdao in the Shandong Peninsula urban agglomeration. The model provides reliable estimates of the real-time charging system LOS and a satisfactory layout based on the user chargig preferences, network traffic conditions, and facility conditions. The layout was then analysed using forward and reverse construction time sequences. The results show that for the same LOS constraint, long-term deployment should consider future energy demands and the planners should use the reverse construction time sequence method.
Keywords traffic engineering      charging infrastructure      bi-level optimal deployment      electric vehicles      dynamic traffic assignment      construction time sequence     
Issue Date: 16 June 2022
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YANG Yang
ZHANG Tianyu
ZHU Yuting
YAO Enjian
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YANG Yang,ZHANG Tianyu,ZHU Yuting, et al. Optimizing the deployment of charging systems on an expressway network considering the construction time sequence and the dynamic charging demand[J]. Journal of Tsinghua University(Science and Technology), 2022, 62(7): 1163-1177,1219.
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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2022.26.017     OR     http://jst.tsinghuajournals.com/EN/Y2022/V62/I7/1163
  
  
  
  
  
  
  
  
  
  
  
  
  
  
[1] China Daily. China's vehicles in numbers[EB/OL]. (2021-04-11)[2022-05-10]. https://global.chinadaily.com.cn/a/202204/11/WS6253ce11a310fd2b29e56419.html.
[2] Min News. Embarrassment:Charge for one hour, queue for four hours[EB/OL]. (2022-04-13)[2022-05-10]. https://min.news/en/digital/279f868e061b1445de96b00113d54ce1.html.
[3] China Daily. EV drivers queue to recharge during holiday[EB/OL]. (2021-10-11)[2022-05-10]. https://global.chinadaily.com.cn/a/202110/11/WS61639f31a310cdd39bc6e0b7.html.
[4] 郭创新, 刘洞宇, 朱承治, 等. 电动汽车居民区充电负荷建模分析[J]. 电力自动化设备, 2020, 40(1):1-9. GUO C X, LIU D Y, ZHU C Z, et al. Modeling and analysis of electric vehicle charging load in residential area[J]. Electric Power Automation Equipment, 2020, 40(1):1-9. (in Chinese)
[5] HU D D, ZHANG J S, ZHANG Q. Optimization design of electric vehicle charging stations based on the forecasting data with service balance consideration[J]. Applied Soft Computing, 2019, 75:215-226.
[6] ZENG M, PAN Y F, ZHANG D Y, et al. Data-driven location selection for battery swapping stations[J]. IEEE Access, 2019, 7:133760-133771.
[7] LI S Y, HUANG Y X, MASON S J. A multi-period optimization model for the deployment of public electric vehicle charging stations on network[J]. Transportation Research Part C:Emerging Technologies, 2016, 65:128-143.
[8] 曹小曙, 胡培婷, 刘丹. 电动汽车充电站选址研究进展[J]. 地理科学进展, 2019, 38(1):139-152. CAO X S, HU P T, LIU D. Progress of research on electric vehicle charging stations[J]. Progress in Geography, 2019, 38(1):139-152. (in Chinese)
[9] LIU Z C, SONG Z Q. Network user equilibrium of battery electric vehicles considering flow-dependent electricity consumption[J]. Transportation Research Part C:Emerging Technologies, 2018, 95:516-544.
[10] HE J, YANG H, TANG T Q, et al. An optimal charging station location model with the consideration of electric vehicle's driving range[J]. Transportation Research Part C:Emerging Technologies, 2018, 86:641-654.
[11] 郇宁, 姚恩建, 杨扬, 等. 电动汽车混入条件下随机动态用户均衡分配模型[J]. 交通运输工程学报, 2019, 19(5):150-161. HUAN N, YAO E J, YANG Y, et al. Stochastic dynamic user equilibrium assignment model considering penetration of electric vehicles[J]. Journal of Traffic and Transportation Engineering, 2019, 19(5):150-161. (in Chinese)
[12] 张美霞, 蔡雅慧, 杨秀, 等. 考虑用户充电差异性的家用电动汽车充电需求分布分析方法[J]. 电力自动化设备, 2020, 40(2):154-161. ZHANG M X, CAI Y H, YANG X, et al. Charging demand distribution analysis method of household electric vehicles considering users' charging difference[J]. Electric Power Automation Equipment, 2020, 40(2):154-161. (in Chinese)
[13] 贾龙, 胡泽春, 宋永华. 考虑不同类型充电需求的城市内电动汽车充电设施综合规划[J]. 电网技术, 2016, 40(9):2579-2587. JIA L, HU Z C, SONG Y H. An integrated planning of electric vehicle charging facilities for urban area considering different types of charging demands[J]. Power System Technology, 2016, 40(9):2579-2587. (in Chinese)
[14] XIE F, LIU C Z, LI S Y, et al. Long-term strategic planning of inter-city fast charging infrastructure for battery electric vehicles[J]. Transportation Research Part E:Logistics and Transportation Review, 2018, 109:261-276.
[15] 李浩, 陈浩, 陆续, 等. 考虑排放约束的电动汽车混行交通路网均衡模型[J]. 交通运输工程与信息学报, 2021, 19(4):24-35, 117. LI H, CHEN H, LU X, et al. Mixed traffic network equilibrium with battery electric vehicles considering emission constraints[J]. Journal of Transportation Engineering and Information, 2021, 19(4):24-35, 117. (in Chinese)
[16] 袁胜强, 曾小清, 张伟略, 等. 城市快速路建设时机的决策模型与准则[J]. 同济大学学报(自然科学版), 2019, 47(9):1294-1301. YUAN S Q, ZENG X Q, ZHANG W L, et al. Decision model and criteria of urban expressway construction timing[J]. Journal of Tongji University (Natural Science), 2019, 47(9):1294-1301. (in Chinese)
[17] 程林, 张靖, 黄仁乐, 等. 基于多能互补的综合能源系统多场景规划案例分析[J]. 电力自动化设备, 2017, 37(6):282-287. CHENG L, ZHANG J, HUANG R L, et al. Case analysis of multi-scenario planning based on multi-energy complementation for integrated energy system[J]. Electric Power Automation Equipment, 2017, 37(6):282-287. (in Chinese)
[18] 陈昌铭, 张群, 黄亦昕, 等. 考虑最优建设时序和云储能的园区综合能源系统优化配置方法[J]. 电力系统自动化, 2022, 46(2):24-32. CHEN C M, ZHANG Q, HUANG Y X, et al. Optimal configuration method of park-level integrated energy system considering optimal construction time sequence and cloud energystorage[J]. Automation of Electric Power Systems, 2022, 46(2):24-32. (in Chinese)
[19] 杨扬, 姚恩建, 王梅英, 等. 电动汽车混入条件下的随机用户均衡分配模型[J]. 中国公路学报, 2015, 28(9):91-97. YANG Y, YAO E J, WANG M Y, et al. Stochastic user equilibrium assignment model for electric vehicle under hybrid traffic condition[J]. China Journal of Highway and Transport, 2015, 28(9):91-97. (in Chinese)
[20] 叶露, 郭倩芸, 倪舒晨, 等. 混合交通网络充电站选址模型[J]. 交通运输工程与信息学报, 2019, 17(4):97-104. YE L, GUO Q Y, NI S C, et al. Charging station location model for mixed traffic network[J]. Journal of Transportation Engineering and Information, 2019, 17(4):97-104. (in Chinese)
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