IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp1577.html
   My bibliography  Save this paper

Electrification of a City Bus Network: An Optimization Model for Cost-Effective Placing of Charging Infrastructure and Battery Sizing of Fast Charging Electric Bus Systems

Author

Listed:
  • Alexander Kunith
  • Roman Mendelevitch
  • Dietmar Goehlich

Abstract

The deployment of battery-powered electric bus systems within the public transportation sector plays an important role to increase energy efficiency and to abate emissions. Rising attention is given to bus systems using fast charging technology. This concept requires a comprehensive infrastructure to equip bus routes with charging stations. The combination of charging infrastructure and bus batteries needs a reliable energy supply to maintain a stable bus operation even under demanding conditions. An efficient layout of the charging infrastructure and an appropriate dimensioning of battery capacity are crucial to minimize the total cost of ownership and to enable an energetically feasible bus operation. In this work, the central issue of jointly optimizing the charging infrastructure and battery capacity is described by a capacitated set covering problem. A mixed-integer linear optimization model is developed to determine the minimum number and location of required charging stations for a bus network as well as the adequate battery capacity for each bus line of the network. The bus energy consumption for each route segments is determined based on individual route, bus type, traffic and other information. Different scenarios are examined in order to assess the influence of charging power, climate and changing operating conditions. The findings reveal significant differences in terms of needed infrastructure depending on the scenarios considered. Moreover, the results highlight a trade-off between battery size and charging infrastructure under different operational and infrastructure conditions. The paper addresses upcoming challenges for transport authorities during the electrification process of the bus fleets and sharpens the focus on infrastructural issues related to the fast charging concept.

Suggested Citation

  • Alexander Kunith & Roman Mendelevitch & Dietmar Goehlich, 2016. "Electrification of a City Bus Network: An Optimization Model for Cost-Effective Placing of Charging Infrastructure and Battery Sizing of Fast Charging Electric Bus Systems," Discussion Papers of DIW Berlin 1577, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1577
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.534056.de/dp1577.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haghani, Ali & Banihashemi, Mohamadreza, 2002. "Heuristic approaches for solving large-scale bus transit vehicle scheduling problem with route time constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 36(4), pages 309-333, May.
    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. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2018. "Assessing life cycle impacts and the risk and uncertainty of alternative bus technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 569-579.

    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. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    2. Raka Jovanovic & Islam Safak Bayram & Sertac Bayhan & Stefan Voß, 2021. "A GRASP Approach for Solving Large-Scale Electric Bus Scheduling Problems," Energies, MDPI, vol. 14(20), pages 1-23, October.
    3. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    4. Higgins, Andrew, 2006. "Scheduling of road vehicles in sugarcane transport: A case study at an Australian sugar mill," European Journal of Operational Research, Elsevier, vol. 170(3), pages 987-1000, May.
    5. Quadrifoglio, Luca & Dessouky, Maged M. & Ordóñez, Fernando, 2008. "A simulation study of demand responsive transit system design," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 718-737, May.
    6. Wang, Zhongxiang & Haghani, Ali, 2020. "Column generation-based stochastic school bell time and bus scheduling optimization," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1087-1102.
    7. Roca-Riu, Mireia & Estrada, Miquel & Trapote, César, 2012. "The design of interurban bus networks in city centers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1153-1165.
    8. Diefenbach, Heiko & Emde, Simon & Glock, Christoph H., 2023. "Multi-depot electric vehicle scheduling in in-plant production logistics considering non-linear charging models," European Journal of Operational Research, Elsevier, vol. 306(2), pages 828-848.
    9. Uçar, Ezgi & İlker Birbil, Ş. & Muter, İbrahim, 2017. "Managing disruptions in the multi-depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 249-269.
    10. Haghani, Ali & Banihashemi, Mohamadreza & Chiang, Kun-Hung, 2003. "A comparative analysis of bus transit vehicle scheduling models," Transportation Research Part B: Methodological, Elsevier, vol. 37(4), pages 301-322, May.
    11. Dessouky, Maged M. & Ordóñez, Fernando & Quadrifoglio, Luca, 2005. "Productivity and Cost-Effectiveness of Demand Responsive Transit Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9qj1d5s0, Institute of Transportation Studies, UC Berkeley.
    12. Shafahi, Yousef & Khani, Alireza, 2010. "A practical model for transfer optimization in a transit network: Model formulations and solutions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(6), pages 377-389, July.
    13. Bin Yu & Liu Zhang & Feng Guan & Zixuan Peng & Baozhen Yao, 2017. "Equity based congestion pricing: considering the constraint of alternative path," Operational Research, Springer, vol. 17(1), pages 313-337, April.
    14. Jonathan D. Adler & Pitu B. Mirchandani, 2017. "The Vehicle Scheduling Problem for Fleets with Alternative-Fuel Vehicles," Transportation Science, INFORMS, vol. 51(2), pages 441-456, May.
    15. Ibarra-Rojas, O.J. & Delgado, F. & Giesen, R. & Muñoz, J.C., 2015. "Planning, operation, and control of bus transport systems: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 38-75.
    16. Shen, Yindong & Xu, Jia & Li, Jingpeng, 2016. "A probabilistic model for vehicle scheduling based on stochastic trip times," Transportation Research Part B: Methodological, Elsevier, vol. 85(C), pages 19-31.
    17. Abdolmaleki, Mojtaba & Masoud, Neda & Yin, Yafeng, 2020. "Transit timetable synchronization for transfer time minimization," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 143-159.
    18. Nguyen, Phuong H.D. & Tran, Daniel, 2024. "Constraint-Based snowplow optimization model for winter maintenance operations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    19. Olsen, Nils, 2020. "A literature overview on scheduling electric vehicles in public transport and location planning of the charging infrastructure," Discussion Papers 2020/16, Free University Berlin, School of Business & Economics.
    20. Jing-Quan Li, 2014. "Transit Bus Scheduling with Limited Energy," Transportation Science, INFORMS, vol. 48(4), pages 521-539, November.

    More about this item

    Keywords

    Electric bus; charging infrastructure; fast charging; cost optimization; capacitated set-covering problem;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L92 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Railroads and Other Surface Transportation
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:diw:diwwpp:dp1577. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    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.