IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v341y2023ics0306261923004907.html
   My bibliography  Save this article

Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems

Author

Listed:
  • Aghajan-Eshkevari, Saleh
  • Ameli, Mohammad Taghi
  • Azad, Sasan

Abstract

With the increasing penetration level of electric vehicles (EVs) in the transportation network, it is necessary to control the charging and discharging process of EVs to avoid operational issues in the power grid. Therefore, in this paper, a two-stage framework is presented for EVs optimal routing and their active and reactive power control in the distribution grid. In the first stage, the EVs mobility in the transportation system is taken into consideration. On this basis, EV daily trips in the transportation network are modelled using the trip chain method. Also, the Dijkstra algorithm is utilized for optimal routing with the shortest travel time between the origin and the destination node. Furthermore, the effects of ambient temperature, traffic congestion and road type on the EVs energy consumption are assessed. In the second stage, optimal active and reactive power exchange of EVs with the distribution grid is carried out. Thus, a mixed-integer linear programming (MILP) model is proposed that simultaneously considers EV owners’ and the distribution network operator's benefits as the optimization goals. The EV battery degradation cost due to the discharging of active power is also integrated into the objective function of the optimization problem. The proposed framework is implemented on a standard IEEE 33-bus system coupled with a 30-node transportation network. The simulation results show that the presented method can reduce the loss cost of the distribution grid and benefit EV owners compared to different charging strategies. In addition, with the battery technology development, the proposed framework can significantly improve the distribution system operation, decrease environmental issues, and reduce EV owner’s costs.

Suggested Citation

  • Aghajan-Eshkevari, Saleh & Ameli, Mohammad Taghi & Azad, Sasan, 2023. "Optimal routing and power management of electric vehicles in coupled power distribution and transportation systems," Applied Energy, Elsevier, vol. 341(C).
    • Handle: RePEc:eee:appene:v:341:y:2023:i:c:s0306261923004907
    DOI: 10.1016/j.apenergy.2023.121126
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923004907
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.121126?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, Haiyang & Fu, Kun & Wang, Yu & Sun, Qie & Li, Hailong & Hu, Yukun & Sun, Bo & Wennersten, Ronald, 2019. "Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model," Energy, Elsevier, vol. 188(C).
    2. Mehta, R. & Verma, P. & Srinivasan, D. & Yang, Jing, 2019. "Double-layered intelligent energy management for optimal integration of plug-in electric vehicles into distribution systems," Applied Energy, Elsevier, vol. 233, pages 146-155.
    3. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    4. Lili Gong & Wu Cao & Kangli Liu & Jianfeng Zhao & Xiang Li, 2018. "Spatial and Temporal Optimization Strategy for Plug-In Electric Vehicle Charging to Mitigate Impacts on Distribution Network," Energies, MDPI, vol. 11(6), pages 1-16, May.
    5. Lidan Chen & Yao Zhang & Antonio Figueiredo, 2019. "Spatio-Temporal Model for Evaluating Demand Response Potential of Electric Vehicles in Power-Traffic Network," Energies, MDPI, vol. 12(10), pages 1-20, May.
    6. Lotfi, Mohamed & Almeida, Tiago & Javadi, Mohammad S. & Osório, Gerardo J. & Monteiro, Cláudio & Catalão, João P.S., 2022. "Coordinating energy management systems in smart cities with electric vehicles," Applied Energy, Elsevier, vol. 307(C).
    7. Lyu, Lin & Yang, Xinran & Xiang, Yue & Liu, Junyong & Jawad, Shafqat & Deng, Runqi, 2020. "Exploring high-penetration electric vehicles impact on urban power grid based on voltage stability analysis," Energy, Elsevier, vol. 198(C).
    8. Enjian Yao & Zhiqiang Yang & Yuanyuan Song & Ting Zuo, 2013. "Comparison of Electric Vehicle’s Energy Consumption Factors for Different Road Types," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-7, December.
    9. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    10. Wenxia Liu & Huiting Xu & Shuya Niu & Jiang Xie, 2016. "Optimal Distributed Generator Allocation Method Considering Voltage Control Cost," Sustainability, MDPI, vol. 8(2), pages 1-20, February.
    11. Nimalsiri, Nanduni I. & Ratnam, Elizabeth L. & Mediwaththe, Chathurika P. & Smith, David B. & Halgamuge, Saman K., 2021. "Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit," Applied Energy, Elsevier, vol. 291(C).
    12. Xiang, Yue & Jiang, Zhuozhen & Gu, Chenghong & Teng, Fei & Wei, Xiangyu & Wang, Yang, 2019. "Electric vehicle charging in smart grid: A spatial-temporal simulation method," Energy, Elsevier, vol. 189(C).
    13. Triviño-Cabrera, Alicia & Aguado, José A. & Torre, Sebastián de la, 2019. "Joint routing and scheduling for electric vehicles in smart grids with V2G," Energy, Elsevier, vol. 175(C), pages 113-122.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei Dai & Zhihong Zeng & Cheng Wang & Zhijie Zhang & Yang Gao & Jun Xu, 2024. "Non-Iterative Coordinated Optimisation of Power–Traffic Networks Based on Equivalent Projection," Energies, MDPI, vol. 17(8), pages 1-21, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    2. Meng, Weiqi & Song, Dongran & Huang, Liansheng & Chen, Xiaojiao & Yang, Jian & Dong, Mi & Talaat, M., 2024. "A Bi-level optimization strategy for electric vehicle retailers based on robust pricing and hybrid demand response," Energy, Elsevier, vol. 289(C).
    3. Zhao, Zhonghao & Lee, Carman K.M. & Huo, Jiage, 2023. "EV charging station deployment on coupled transportation and power distribution networks via reinforcement learning," Energy, Elsevier, vol. 267(C).
    4. Junaid Bin Fakhrul Islam & Mir Toufikur Rahman & Shameem Ahmad & Tofael Ahmed & G. M. Shafiullah & Hazlie Mokhlis & Mohamadariff Othman & Tengku Faiz Tengku Mohmed Noor Izam & Hasmaini Mohamad & Moham, 2023. "Multi-Objective-Based Charging and Discharging Coordination of Plug-in Electric Vehicle Integrating Capacitor and OLTC," Energies, MDPI, vol. 16(5), pages 1-20, February.
    5. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    6. Zhang, Chao & Yin, Wanjun & Wen, Tao, 2024. "An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid," Energy, Elsevier, vol. 287(C).
    7. Liu, Yuechen Sophia & Tayarani, Mohammad & Gao, H. Oliver, 2022. "An activity-based travel and charging behavior model for simulating battery electric vehicle charging demand," Energy, Elsevier, vol. 258(C).
    8. Ren, Yilong & Lan, Zhengxing & Yu, Haiyang & Jiao, Gangxin, 2022. "Analysis and prediction of charging behaviors for private battery electric vehicles with regular commuting: A case study in Beijing," Energy, Elsevier, vol. 253(C).
    9. Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
    10. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    11. Guo, Shiliang & Li, Pengpeng & Ma, Kai & Yang, Bo & Yang, Jie, 2022. "Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles," Applied Energy, Elsevier, vol. 325(C).
    12. Jiaan Zhang & Chenyu Liu & Leijiao Ge, 2022. "Short-Term Load Forecasting Model of Electric Vehicle Charging Load Based on MCCNN-TCN," Energies, MDPI, vol. 15(7), pages 1-25, April.
    13. Wang, Y. & Mauree, D. & Sun, Q. & Lin, H. & Scartezzini, J.L. & Wennersten, R., 2020. "A review of approaches to low-carbon transition of high-rise residential buildings in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    14. Tan, Bifei & Lin, Zhenjia & Zheng, Xiaodong & Xiao, Fu & Wu, Qiuwei & Yan, Jinyue, 2023. "Distributionally robust energy management for multi-microgrids with grid-interactive EVs considering the multi-period coupling effect of user behaviors," Applied Energy, Elsevier, vol. 350(C).
    15. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
    16. Bi, Huibo & Shang, Wen-Long & Chen, Yanyan & Wang, Kezhi & Yu, Qing & Sui, Yi, 2021. "GIS aided sustainable urban road management with a unifying queueing and neural network model," Applied Energy, Elsevier, vol. 291(C).
    17. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M., 2021. "An energy paradigm transition framework from negative towards positive district energy sharing networks—Battery cycling aging, advanced battery management strategies, flexible vehicles-to-buildings in," Applied Energy, Elsevier, vol. 288(C).
    18. Balu, Korra & Mukherjee, V., 2024. "Optimal deployment of electric vehicle charging stations, renewable distributed generation with battery energy storage and distribution static compensator in radial distribution network considering un," Applied Energy, Elsevier, vol. 359(C).
    19. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
    20. Wen, Shuang & Lin, Ni & Huang, Shengxu & Wang, Zhenpo & Zhang, Zhaosheng, 2023. "Lithium battery health state assessment based on vehicle-to-grid (V2G) real-world data and natural gradient boosting model," Energy, Elsevier, vol. 284(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:341:y:2023:i:c:s0306261923004907. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.