IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v340y2025ics0360544225048443.html

A Nash–Stackelberg–Nash game for collaborative operation of a coupled microgrid-transportation network

Author

Listed:
  • Li, Bin
  • Li, Jia
  • Liu, Zhitao
  • Su, Hongye

Abstract

With the increasing adoption of electric vehicles (EVs) and the advancement of dynamic wireless charging, the transportation network (TN) and multi-microgrid (MMG) are gradually transitioning from independent operations to a tightly coupled mode. This paper proposes a Nash–Stackelberg–Nash (N–S–N) game to optimize the collaborative operation of a coupled microgrid-transportation network (CMTN). The follower problem refers to the traffic assignment of the TN, which is established as a dynamic user equilibrium (DUE) model with elastic demand. Traffic demand changes in response to the operational and congestion states of the TN. This DUE model is transformed into variational inequalities for solving, and the obtained charging demand is then transmitted to the MMG. The leader problem concerns the cooperative scheduling of the MMG, where direct electricity trading among microgrids is allowed, which can be formulated as a cooperative game. The cooperative game can be decomposed into two sequential subproblems for solving, and the determined charging prices are then released to the TN. The leader and follower problems form an N–S–N game through this feedback dependency between charging prices and charging loads. This paper transforms the N–S–N game into a fixed-point problem and develops a best response algorithm to solve it. Moreover, an improved fixed-point algorithm and alternating direction method of multipliers with adaptive penalty factor are proposed to obtain the DUE of the TN and the cooperative scheduling of the MMG, respectively. The numerical results demonstrate that the proposed N–S–N game can not only effectively realize the collaborative operation of the CMTN but also improve energy efficiency, reduce costs, and lower carbon emissions.

Suggested Citation

  • Li, Bin & Li, Jia & Liu, Zhitao & Su, Hongye, 2025. "A Nash–Stackelberg–Nash game for collaborative operation of a coupled microgrid-transportation network," Energy, Elsevier, vol. 340(C).
  • Handle: RePEc:eee:energy:v:340:y:2025:i:c:s0360544225048443
    DOI: 10.1016/j.energy.2025.139202
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225048443
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.139202?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Najafi, Arsalan & Tsaousoglou, Georgios & Gao, Kun & Parishwad, Omkar, 2024. "Coordination of coupled electrified road systems and active power distribution networks with flexibility integration," Applied Energy, Elsevier, vol. 369(C).
    2. Chen, Sheng & Sun, Guoqiang & Wei, Zhinong & Wang, Dan, 2020. "Dynamic pricing in electricity and natural gas distribution networks: An EPEC model," Energy, Elsevier, vol. 207(C).
    3. Zhou, Ze & Liu, Zhitao & Su, Hongye & Zhang, Liyan, 2023. "Planning of static and dynamic charging facilities for electric vehicles in electrified transportation networks," Energy, Elsevier, vol. 263(PE).
    4. Li, Zepeng & Wu, Qiuwei & Li, Hui & Nie, Chengkai & Tan, Jin, 2024. "Distributed low-carbon economic dispatch of integrated power and transportation system," Applied Energy, Elsevier, vol. 353(PA).
    5. Friesz, Terry L. & Han, Ke & Bagherzadeh, Amir, 2021. "Convergence of fixed-point algorithms for elastic demand dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 336-352.
    6. Li, Bin & Li, Jia & Liu, Zhitao & Su, Hongye, 2025. "Network equilibrium of a transportation-power distribution coupled system: A Stackelberg–Nash game model," Renewable Energy, Elsevier, vol. 241(C).
    7. Paul I. Richards, 1956. "Shock Waves on the Highway," Operations Research, INFORMS, vol. 4(1), pages 42-51, February.
    8. Chen, Yuanyi & Hu, Simon & Zheng, Yanchong & Xie, Shiwei & Hu, Qinru & Yang, Qiang, 2024. "Coordinated expansion planning of coupled power and transportation networks considering dynamic network equilibrium," Applied Energy, Elsevier, vol. 360(C).
    9. Zhou, Yizhou & Li, Yu & Huang, Wentao & Chen, Sheng & Zang, Haixiang & Tai, Nengling, 2025. "Collaborative scheduling of seaport integrated energy, logistics, and vessels: A bi-level nash-stackelberg-nash game approach," Applied Energy, Elsevier, vol. 400(C).
    Full references (including those not matched with items on IDEAS)

    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. Li, Bin & Li, Jia & Liu, Zhitao & Su, Hongye, 2025. "Capacity optimization of a transportation-power coupled network based on elastic traffic demand user equilibrium using a multi-step evolutionary algorithm," Energy, Elsevier, vol. 334(C).
    2. Li, Bin & Li, Jia & Liu, Zhitao & Su, Hongye, 2025. "Network equilibrium of a transportation-power distribution coupled system: A Stackelberg–Nash game model," Renewable Energy, Elsevier, vol. 241(C).
    3. Shi, Haojie & Xiong, Houbo & Gan, Wei & Lin, Yumian & Guo, Chuangxin, 2025. "Fully distributed planning method for coordinated distribution and urban transportation networks considering three-phase unbalance mitigation," Applied Energy, Elsevier, vol. 377(PA).
    4. Lian, Xianglong & Song, Chenkai & Li, Zepeng & Qiu, Lei & Liu, Lijun, 2026. "Resilience-oriented emergency resource dispatch for power–transportation coupled networks under rainstorm-induced flood hazards," Applied Energy, Elsevier, vol. 403(PA).
    5. Soulaymane Kachani & Georgia Perakis, 2009. "A Dynamic Travel Time Model for Spillback," Networks and Spatial Economics, Springer, vol. 9(4), pages 595-618, December.
    6. Bai, Lu & Wong, S.C. & Xu, Pengpeng & Chow, Andy H.F. & Lam, William H.K., 2021. "Calibration of stochastic link-based fundamental diagram with explicit consideration of speed heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 524-539.
    7. McCrea, Jennifer & Moutari, Salissou, 2010. "A hybrid macroscopic-based model for traffic flow in road networks," European Journal of Operational Research, Elsevier, vol. 207(2), pages 676-684, December.
    8. Xingmin Wang & Zachary Jerome & Zihao Wang & Chenhao Zhang & Shengyin Shen & Vivek Vijaya Kumar & Fan Bai & Paul Krajewski & Danielle Deneau & Ahmad Jawad & Rachel Jones & Gary Piotrowicz & Henry X. L, 2024. "Traffic light optimization with low penetration rate vehicle trajectory data," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    9. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    10. Huanping Li & Jian Wang & Guopeng Bai & Xiaowei Hu, 2021. "Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads," Energies, MDPI, vol. 14(12), pages 1-21, June.
    11. Jin, W. L. & Zhang, H. M., 2003. "The formation and structure of vehicle clusters in the Payne-Whitham traffic flow model," Transportation Research Part B: Methodological, Elsevier, vol. 37(3), pages 207-223, March.
    12. Herrera, Juan C. & Bayen, Alexandre M., 2010. "Incorporation of Lagrangian measurements in freeway traffic state estimation," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 460-481, May.
    13. Saif Eddin Jabari & Laura Wynter, 2016. "Sensor placement with time-to-detection guarantees," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(4), pages 415-433, December.
    14. Jin, Can & Peng, Guanghan & Huang, Yixin, 2025. "Phase transitions in operation of heterogeneous vehicles mixed with human-driven and connected autonomous vehicles under speed restriction circumstances," Chaos, Solitons & Fractals, Elsevier, vol. 195(C).
    15. Tian, Ye & Xu, Yinliang & Sun, Hongbin & Tai, Nengling, 2025. "Frequency-constrained microgrid-distribution network coordinated load restoration: A distributed carbon-aware optimization approach," Applied Energy, Elsevier, vol. 395(C).
    16. García-Chan, N. & Alvarez-Vázquez, L.J. & Martínez, A. & Vázquez-Méndez, M.E., 2021. "Designing an ecologically optimized road corridor surrounding restricted urban areas: A mathematical methodology," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 745-759.
    17. Mohan, Ranju & Ramadurai, Gitakrishnan, 2021. "Multi-class traffic flow model based on three dimensional flow–concentration surface," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    18. Coifman, Benjamin & Ponnu, Balaji, 2020. "Adjacent lane dependencies modulating wave velocity on congested freeways-An empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 84-99.
    19. Georgia Perakis & Guillaume Roels, 2006. "An Analytical Model for Traffic Delays and the Dynamic User Equilibrium Problem," Operations Research, INFORMS, vol. 54(6), pages 1151-1171, December.
    20. Hou, Lin & Pei, Yulong & He, Qingling, 2023. "A car following model in the context of heterogeneous traffic flow involving multilane following behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:340:y:2025:i:c:s0360544225048443. 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.journals.elsevier.com/energy .

    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.