IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v188y2024ics1366554524002023.html
   My bibliography  Save this article

A novel ranking method based on semi-SPO for battery swapping allocation optimization in a hybrid electric transit system

Author

Listed:
  • Huang, Di
  • Zhang, Jinyu
  • Liu, Zhiyuan
  • He, Yiliu
  • Liu, Pan

Abstract

The allocation of batteries in hybrid charging stations has consistently played a significant role in the decision-making process for plug-in charging and battery swapping. Predicting the state of charge (SOC) for each electric bus (EB) in advance is crucial to assist in making future battery allocation decisions. This paper proposes a semi-Smart “Predict, then Optimize” (semi-SPO) framework for the battery allocation scheduling problem. The battery allocation optimization problem is reduced to a ranking problem with respect to SOC and integrated into the prediction model. The rank of SOC is determined from both pairwise and listwise perspectives. Considering the inherent characteristics of rankwise regression, such as missing parameters and infinite number of optimal solutions, a geometric analysis is conducted. A model enhancement approach is then proposed to ensure the accuracy of both prediction and optimization models. This enhancement facilitates optimal decision-making while preserving the interpretability of predicted values. A case study is conducted using the real-world data of Nanjing, China. The result shows that the proposed semi-SPO framework offers superior decision-making outcomes in the battery allocation pro.

Suggested Citation

  • Huang, Di & Zhang, Jinyu & Liu, Zhiyuan & He, Yiliu & Liu, Pan, 2024. "A novel ranking method based on semi-SPO for battery swapping allocation optimization in a hybrid electric transit system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:transe:v:188:y:2024:i:c:s1366554524002023
    DOI: 10.1016/j.tre.2024.103611
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554524002023
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2024.103611?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. Gah-Yi Ban & Cynthia Rudin, 2019. "The Big Data Newsvendor: Practical Insights from Machine Learning," Operations Research, INFORMS, vol. 67(1), pages 90-108, January.
    2. Cheng, Qixiu & Lin, Yuqian & Zhou, Xuesong (Simon) & Liu, Zhiyuan, 2024. "Analytical formulation for explaining the variations in traffic states: A fundamental diagram modeling perspective with stochastic parameters," European Journal of Operational Research, Elsevier, vol. 312(1), pages 182-197.
    3. Zhao, Li & Ke, Hanchen & Huo, Weiwei, 2023. "A frequency item mining based energy consumption prediction method for electric bus," Energy, Elsevier, vol. 263(PD).
    4. Cheng, Qixiu & Liu, Zhiyuan & Lu, Jiawei & List, George & Liu, Pan & Zhou, Xuesong Simon, 2024. "Using frequency domain analysis to elucidate travel time reliability along congested freeway corridors," Transportation Research Part B: Methodological, Elsevier, vol. 184(C).
    5. Li, Pengshun & Zhang, Yuhang & Zhang, Yi & Zhang, Yi & Zhang, Kai, 2021. "Prediction of electric bus energy consumption with stochastic speed profile generation modelling and data driven method based on real-world big data," Applied Energy, Elsevier, vol. 298(C).
    6. Cui, Shaohua & Gao, Kun & Yu, Bin & Ma, Zhenliang & Najafi, Arsalan, 2023. "Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    7. Huang, Di & Liu, Zhiyuan & Liu, Pan & Chen, Jun, 2016. "Optimal transit fare and service frequency of a nonlinear origin-destination based fare structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 1-19.
    8. Jing-Quan Li, 2014. "Transit Bus Scheduling with Limited Energy," Transportation Science, INFORMS, vol. 48(4), pages 521-539, November.
    9. Battaïa, Olga & Dolgui, Alexandre & Guschinsky, Nikolai & Kovalyov, Mikhail Y., 2023. "Designing fast-charge urban electric bus services: An Integer Linear Programming model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    10. Dimitris Bertsimas & Nathan Kallus, 2020. "From Predictive to Prescriptive Analytics," Management Science, INFORMS, vol. 66(3), pages 1025-1044, March.
    11. Honggang Zhang & Zhiyuan Liu & Yicheng Zhang & Weijie Chen & Chenyang Zhang, 2024. "A Distributed Computing Method Integrating Improved Gradient Projection for Solving Stochastic Traffic Equilibrium Problem," Networks and Spatial Economics, Springer, vol. 24(2), pages 361-381, June.
    12. Tian, Xuecheng & Yan, Ran & Liu, Yannick & Wang, Shuaian, 2023. "A smart predict-then-optimize method for targeted and cost-effective maritime transportation," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 32-52.
    13. Wang, Yusheng & Huang, Yongxi & Xu, Jiuping & Barclay, Nicole, 2017. "Optimal recharging scheduling for urban electric buses: A case study in Davis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 115-132.
    14. 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.
    15. Shi, Junzhe & Zeng, Teng & Moura, Scott, 2023. "Electric fleet charging management considering battery degradation and nonlinear charging profile," Energy, Elsevier, vol. 283(C).
    16. Alvo, Matías & Angulo, Gustavo & Klapp, Mathias A., 2021. "An exact solution approach for an electric bus dispatch problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    17. Zhang, Le & Wang, Shuaian & Qu, Xiaobo, 2021. "Optimal electric bus fleet scheduling considering battery degradation and non-linear charging profile," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    18. Yan, Ran & Wang, Shuaian & Fagerholt, Kjetil, 2020. "A semi-“smart predict then optimize” (semi-SPO) method for efficient ship inspection," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 100-125.
    19. Yang, Jie & Liu, Wei & Ma, Kai & Yue, Zhiyuan & Zhu, Anhu & Guo, Shiliang, 2023. "An optimal battery allocation model for battery swapping station of electric vehicles," Energy, Elsevier, vol. 272(C).
    20. Chen, Xinjiang & Yang, Yu & Wang, Jianxiao & Song, Jie & He, Guannan, 2023. "Battery valuation and management for battery swapping station," Energy, Elsevier, vol. 279(C).
    21. Nathan Kallus & Xiaojie Mao, 2023. "Stochastic Optimization Forests," Management Science, INFORMS, vol. 69(4), pages 1975-1994, April.
    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. Zhang, Jinyu & Huang, Di & Liu, Zhiyuan & Zheng, Yifei & Han, Yu & Liu, Pan & Huang, Wei, 2024. "A data-driven optimization-based approach for freeway traffic state estimation based on heterogeneous sensor data fusion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 189(C).

    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. Peng, Yiyang & Li, Guoyuan & Xu, Min & Chen, Anthony, 2024. "Mixed-fleet operation of battery electric bus and hydrogen bus: Considering limited depot size with flexible refueling processes," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 188(C).
    2. Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    3. Shuaian Wang & Xuecheng Tian, 2023. "A Deficiency of the Predict-Then-Optimize Framework: Decreased Decision Quality with Increased Data Size," Mathematics, MDPI, vol. 11(15), pages 1-9, July.
    4. Zhou, Yu & Wang, Hua & Wang, Yun & Yu, Bin & Tang, Tianpei, 2024. "Charging facility planning and scheduling problems for battery electric bus systems: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    5. Gkiotsalitis, K. & Iliopoulou, C. & Kepaptsoglou, K., 2023. "An exact approach for the multi-depot electric bus scheduling problem with time windows," European Journal of Operational Research, Elsevier, vol. 306(1), pages 189-206.
    6. Cui, Shaohua & Gao, Kun & Yu, Bin & Ma, Zhenliang & Najafi, Arsalan, 2023. "Joint optimal vehicle and recharging scheduling for mixed bus fleets under limited chargers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    7. Feifeng Zheng & Zhixin Wang & Zhaojie Wang & Ming Liu, 2023. "Daytime and Overnight Joint Charging Scheduling for Battery Electric Buses Considering Time-Varying Charging Power," Sustainability, MDPI, vol. 15(13), pages 1-19, July.
    8. Jing Wang & Heqi Wang & Chunguang Wang, 2023. "Optimal Charging Pile Configuration and Charging Scheduling for Electric Bus Routes Considering the Impact of Ambient Temperature on Charging Power," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    9. Lim, Lek Keng & Muis, Zarina Ab & Ho, Wai Shin & Hashim, Haslenda & Bong, Cassendra Phun Chien, 2023. "Review of the energy forecasting and scheduling model for electric buses," Energy, Elsevier, vol. 263(PD).
    10. Tian, Xuecheng & Wang, Shuaian & Laporte, Gilbert & Yang, Ying, 2024. "Determinism versus uncertainty: Examining the worst-case expected performance of data-driven policies," European Journal of Operational Research, Elsevier, vol. 318(1), pages 242-252.
    11. Battaïa, Olga & Dolgui, Alexandre & Guschinsky, Nikolai & Kovalyov, Mikhail Y., 2023. "Designing fast-charge urban electric bus services: An Integer Linear Programming model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    12. Liu, Xiaohan & Yeh, Sonia & Plötz, Patrick & Ma, Wenxi & Li, Feng & Ma, Xiaolei, 2024. "Electric bus charging scheduling problem considering charging infrastructure integrated with solar photovoltaic and energy storage systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    13. Guschinsky, Nikolai & Kovalyov, Mikhail Y. & Pesch, Erwin & Rozin, Boris, 2023. "Cost minimizing decisions on equipment and charging schedule for electric buses in a single depot," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    14. Zhou, Yu & Meng, Qiang & Ong, Ghim Ping, 2022. "Electric Bus Charging Scheduling for a Single Public Transport Route Considering Nonlinear Charging Profile and Battery Degradation Effect," Transportation Research Part B: Methodological, Elsevier, vol. 159(C), pages 49-75.
    15. Serrano, Breno & Minner, Stefan & Schiffer, Maximilian & Vidal, Thibaut, 2024. "Bilevel optimization for feature selection in the data-driven newsvendor problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 703-714.
    16. Wu, Weitiao & Lin, Yue & Liu, Ronghui & Jin, Wenzhou, 2022. "The multi-depot electric vehicle scheduling problem with power grid characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 322-347.
    17. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & Jose Blanchet & Erick Delage & Yinyu Ye, 2021. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Papers 2103.16451, arXiv.org, revised Apr 2024.
    18. Meng Qi & Ying Cao & Zuo-Jun (Max) Shen, 2022. "Distributionally Robust Conditional Quantile Prediction with Fixed Design," Management Science, INFORMS, vol. 68(3), pages 1639-1658, March.
    19. Jos'e-Manuel Pe~na & Fernando Su'arez & Omar Larr'e & Domingo Ram'irez & Arturo Cifuentes, 2023. "A Modified CTGAN-Plus-Features Based Method for Optimal Asset Allocation," Papers 2302.02269, arXiv.org, revised May 2024.
    20. Yang, Cheng-Hu & Wang, Hai-Tang & Ma, Xin & Talluri, Srinivas, 2023. "A data-driven newsvendor problem: A high-dimensional and mixed-frequency method," International Journal of Production Economics, Elsevier, vol. 266(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:transe:v:188:y:2024:i:c:s1366554524002023. 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/600244/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.