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A single-leader and multiple-follower stackelberg model for the look-ahead dispatch of plug-in electric buses in multiple microgrids

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  • Tang, Chong
  • Liu, Mingbo
  • Xie, Min
  • Dong, Ping
  • Zhu, Jianquan
  • Lin, Shunjiang

Abstract

Plug-in electric buses have great potential to enhance the profits of operators in multiple-microgrid systems via the use of vehicle-to-grid technology. In contrast to stationary energy storage units, a plug-in electric bus can move among different microgrids to provide not only passenger transportation service but also energy transportation service. In this paper, a single-leader and multiple-follower model based on the Stackelberg game method is proposed for the look-ahead dispatch of bus routes and power allocation in microgrids. First, a time-space trip model for a fleet of plug-in electric buses was established, and the total costs of the plug-in electric bus operator were optimized as a leader-level problem. Then a rolling energy management strategy was formulated as a follower-level problem to optimize the total costs of each microgrid operator and to deal with the prediction error of the distributed energy resources and loads. Next, the proposed bi-level optimization problem was transformed into a single-level mixed-integer linear programming problem. Finally, case studies were carried out on three real microgrids in China and on BYD-K9 plug-in electric buses. The simulation results indicated that the costs for a plug-in electric bus operator would decrease by 33.35% in the proposed bi-level model compared with the fixed charging model, and the costs for an isolated MG would decrease by 24.16% compared with the model regardless of the plug-in electric buses.

Suggested Citation

  • Tang, Chong & Liu, Mingbo & Xie, Min & Dong, Ping & Zhu, Jianquan & Lin, Shunjiang, 2021. "A single-leader and multiple-follower stackelberg model for the look-ahead dispatch of plug-in electric buses in multiple microgrids," Energy, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:energy:v:214:y:2021:i:c:s0360544220320363
    DOI: 10.1016/j.energy.2020.118929
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    References listed on IDEAS

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    1. Wang, Feng & Zhang, Jian & Xu, Xing & Cai, Yingfeng & Zhou, Zhiguang & Sun, Xiaoqiang, 2019. "A comprehensive dynamic efficiency-enhanced energy management strategy for plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 247(C), pages 657-669.
    2. Xie, Min & Ji, Xiang & Hu, Xintong & Cheng, Peijun & Du, Yuxin & Liu, Mingbo, 2018. "Autonomous optimized economic dispatch of active distribution system with multi-microgrids," Energy, Elsevier, vol. 153(C), pages 479-489.
    3. Wu, Z. & Guo, F. & Polak, J. & Strbac, G., 2019. "Evaluating grid-interactive electric bus operation and demand response with load management tariff," Applied Energy, Elsevier, vol. 255(C).
    4. Berkeley, Nigel & Bailey, David & Jones, Andrew & Jarvis, David, 2017. "Assessing the transition towards Battery Electric Vehicles: A Multi-Level Perspective on drivers of, and barriers to, take up," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 320-332.
    5. Tang, Chong & Liu, Mingbo & Dai, Yue & Wang, Zhijun & Xie, Min, 2019. "Decentralized saddle-point dynamics solution for optimal power flow of distribution systems with multi-microgrids," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    6. Jian, Linni & Zheng, Yanchong & Shao, Ziyun, 2017. "High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles," Applied Energy, Elsevier, vol. 186(P1), pages 46-55.
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    Cited by:

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    2. Zeng, Bo & Luo, Yangfan, 2022. "Potential of harnessing operational flexibility from public transport hubs to improve reliability and economic performance of urban multi-energy systems: A holistic assessment framework," Applied Energy, Elsevier, vol. 322(C).
    3. Yan Xing & Quanbo Fu & Yachao Li & Hanshuo Chu & Enyi Niu, 2023. "Optimal Model of Electric Bus Scheduling Based on Energy Consumption and Battery Loss," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    4. Zhu, Ziqing & Wing Chan, Ka & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2021. "Real-Time interaction of active distribution network and virtual microgrids: Market paradigm and data-driven stakeholder behavior analysis," Applied Energy, Elsevier, vol. 297(C).
    5. Fattaheian-Dehkordi, Sajjad & Abbaspour, Ali & Fotuhi-Firuzabad, Mahmud & Lehtonen, Matti, 2022. "A new management framework for mitigating intense ramping in distribution systems," Energy, Elsevier, vol. 254(PA).
    6. Zhang, Jingrui & Li, Zhuoyun & Wang, Beibei, 2021. "Within-day rolling optimal scheduling problem for active distribution networks by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing," Energy, Elsevier, vol. 223(C).
    7. Zhang, Rui & Yu, Jilai, 2024. "Evaluating multi-dimensional response capability of electric bus considering carbon emissions and traffic index," Energy, Elsevier, vol. 286(C).

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