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Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations

Author

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  • Frank Schneider

    (Supply Chain Management and Management Science, University of Cologne, 50931 Cologne, Germany)

  • Ulrich W. Thonemann

    (Supply Chain Management and Management Science, University of Cologne, 50931 Cologne, Germany)

  • Diego Klabjan

    (Industrial Engineering and Management Science, Northwestern University, Evanston, Illinois 60208)

Abstract

An operator of a network of battery swap stations for electric vehicles must make a long-term investment decision on the number of batteries and charging bays in the system and periodic short-term decisions on when and how many batteries to recharge. Both decisions must be made concurrently, because there exists a trade-off between the long-term investment in batteries and charging bays, and short-term expenses for operating the system. Costs for electric energy as well as demand rates for batteries are stochastic: We consider an infinite time horizon for operation of the system. We derive an optimization problem, which cannot be solved optimally in a reasonable time for real world instances. By optimally solving various small problem instances, we show the mechanics of the model and the influence of its parameters on the optimal cost. We then develop a near-optimal solution heuristic based on Monte Carlo sampling following the ideas of approximate dynamic programming for the infinite horizon dynamic program. We show that operating battery swap stations in a network where lateral transshipments are allowed can substantially decrease expected operating costs.

Suggested Citation

  • Frank Schneider & Ulrich W. Thonemann & Diego Klabjan, 2018. "Optimization of Battery Charging and Purchasing at Electric Vehicle Battery Swap Stations," Transportation Science, INFORMS, vol. 52(5), pages 1211-1234, October.
    • Handle: RePEc:inm:ortrsc:v:52:y:2018:i:5:p:1211-1234
    DOI: 10.1287/trsc.2017.0781
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    5. Lingshu Zhong & Mingyang Pei, 2020. "Optimal Design for a Shared Swap Charging System Considering the Electric Vehicle Battery Charging Rate," Energies, MDPI, vol. 13(5), pages 1-16, March.
    6. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    7. Guo, Fang & Zhang, Jingjing & Huang, Zhihong & Huang, Weilai, 2022. "Simultaneous charging station location-routing problem for electric vehicles: Effect of nonlinear partial charging and battery degradation," Energy, Elsevier, vol. 250(C).
    8. Tang, Juan & Ji, Guan-Qun & Liu, Zhi & Sheu, Jiuh-Biing, 2024. "Electric vehicle battery-charging service and operations managing under different charging station construction modes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    9. Zhang, Junxia & Li, Xingmei & Jia, Dongqing & Zhou, Yuexin, 2023. "A Bi-level programming for union battery swapping stations location-routing problem under joint distribution and cost allocation," Energy, Elsevier, vol. 272(C).
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    11. Kewcharoenwong, Panitan & Li, Qiaofeng & Üster, Halit, 2023. "Lagrangean relaxation algorithms for fixed-charge capacitated relay network design," Omega, Elsevier, vol. 121(C).
    12. Shuna Wang & Zhi-Hua Hu, 2021. "Green Logistics Service Supply Chain Games Considering Risk Preference in Fuzzy Environments," Sustainability, MDPI, vol. 13(14), pages 1-32, July.
    13. Kumar, Rajeev Ranjan & Chakraborty, Abhishek & Mandal, Prasenjit, 2021. "Promoting electric vehicle adoption: Who should invest in charging infrastructure?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    14. Xianhao Shen & Yexin Zhang & Decheng Wang, 2022. "Online Charging Strategy for Electric Vehicle Clusters Based on Multi-Agent Reinforcement Learning and Long–Short Memory Networks," Energies, MDPI, vol. 15(13), pages 1-14, June.
    15. Li, Linman & Li, Yuqing & Liu, Ran & Zhou, Yaoming & Pan, Ershun, 2023. "A Two-stage Stochastic Programming for AGV scheduling with random tasks and battery swapping in automated container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 174(C).
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    17. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.

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