IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v172y2023ics136655452300073x.html
   My bibliography  Save this article

A comparative analysis of charging strategies for battery electric buses in wholesale electricity and ancillary services markets

Author

Listed:
  • Brinkel, Nico
  • Zijlstra, Marle
  • van Bezu, Ronald
  • van Twuijver, Tim
  • Lampropoulos, Ioannis
  • van Sark, Wilfried

Abstract

The application of smart charging to battery electric buses can provide opportunities for bus operators to reduce the operational costs of their bus fleet. This research aims to create insight into the impact of different charging strategies for battery electric bus fleets on charging costs and the grid load. It proposes a novel framework to model the charging process of battery electric buses for different charging strategies: charging-on-arrival, peak-shaving, day-ahead market optimization with and without vehicle-to-grid (V2G) functions, including the provision of Frequency Containment Reserves (FCR) and automatic Frequency Restoration Reserves (aFRR) for system balancing in ancillary services markets. Model simulations are conducted to compare the charging costs and grid impact of different charging strategies, using three depots of bus operator Qbuzz in the Netherlands as a case study. Results indicate that the application of smart charging algorithms can considerably reduce charging costs for bus operators. Application of the peak-shaving strategy was found to reduce charging costs by 23–32% compared to the reference case of charging-on-arrival. Charging costs can be further reduced by 6–11% when considering day-ahead market optimization. Participation in ancillary services markets for system balancing is economically attractive for bus operators, particularly in the aFRR market, characterized by a cost reduction potential of 90–¿100% compared to the charging-on-arrival strategy. The grid impact analysis indicates that charging-on-arrival can result in high charging demand peaks, which can be drastically reduced by the application of peak-shaving or day-ahead market optimization charging strategies. However, the provision of aFRR and FCR using the battery electric bus charging process can have a severe impact on the local grid in terms of high peak demand.

Suggested Citation

  • Brinkel, Nico & Zijlstra, Marle & van Bezu, Ronald & van Twuijver, Tim & Lampropoulos, Ioannis & van Sark, Wilfried, 2023. "A comparative analysis of charging strategies for battery electric buses in wholesale electricity and ancillary services markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
  • Handle: RePEc:eee:transe:v:172:y:2023:i:c:s136655452300073x
    DOI: 10.1016/j.tre.2023.103085
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136655452300073X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2023.103085?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. Manzolli, Jônatas Augusto & Trovão, João Pedro F. & Henggeler Antunes, Carlos, 2022. "Electric bus coordinated charging strategy considering V2G and battery degradation," Energy, Elsevier, vol. 254(PA).
    2. Vepsäläinen, Jari & Otto, Kevin & Lajunen, Antti & Tammi, Kari, 2019. "Computationally efficient model for energy demand prediction of electric city bus in varying operating conditions," Energy, Elsevier, vol. 169(C), pages 433-443.
    3. 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).
    4. Edwin R. Grijalva & José María López Martínez, 2019. "Analysis of the Reduction of CO 2 Emissions in Urban Environments by Replacing Conventional City Buses by Electric Bus Fleets: Spain Case Study," Energies, MDPI, vol. 12(3), pages 1-31, February.
    5. Lajunen, Antti & Lipman, Timothy, 2016. "Lifecycle cost assessment and carbon dioxide emissions of diesel, natural gas, hybrid electric, fuel cell hybrid and electric transit buses," Energy, Elsevier, vol. 106(C), pages 329-342.
    6. Gallet, Marc & Massier, Tobias & Hamacher, Thomas, 2018. "Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks," Applied Energy, Elsevier, vol. 230(C), pages 344-356.
    7. Lago, Jesus & De Ridder, Fjo & Vrancx, Peter & De Schutter, Bart, 2018. "Forecasting day-ahead electricity prices in Europe: The importance of considering market integration," Applied Energy, Elsevier, vol. 211(C), pages 890-903.
    8. Qin, Nan & Gusrialdi, Azwirman & Paul Brooker, R. & T-Raissi, Ali, 2016. "Numerical analysis of electric bus fast charging strategies for demand charge reduction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 386-396.
    9. Rong-Ceng Leou & Jeng-Jiun Hung, 2017. "Optimal Charging Schedule Planning and Economic Analysis for Electric Bus Charging Stations," Energies, MDPI, vol. 10(4), pages 1-17, April.
    10. Yajing Gao & Shixiao Guo & Jiafeng Ren & Zheng Zhao & Ali Ehsan & Yanan Zheng, 2018. "An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors," Energies, MDPI, vol. 11(8), pages 1-17, August.
    11. Zheng, Yanchong & Yu, Hang & Shao, Ziyun & Jian, Linni, 2020. "Day-ahead bidding strategy for electric vehicle aggregator enabling multiple agent modes in uncertain electricity markets," Applied Energy, Elsevier, vol. 280(C).
    12. 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.
    13. Rogge, Matthias & van der Hurk, Evelien & Larsen, Allan & Sauer, Dirk Uwe, 2018. "Electric bus fleet size and mix problem with optimization of charging infrastructure," Applied Energy, Elsevier, vol. 211(C), pages 282-295.
    14. Brinkel, N.B.G. & Schram, W.L. & AlSkaif, T.A. & Lampropoulos, I. & van Sark, W.G.J.H.M., 2020. "Should we reinforce the grid? Cost and emission optimization of electric vehicle charging under different transformer limits," Applied Energy, Elsevier, vol. 276(C).
    15. Zhou, Boya & Wu, Ye & Zhou, Bin & Wang, Renjie & Ke, Wenwei & Zhang, Shaojun & Hao, Jiming, 2016. "Real-world performance of battery electric buses and their life-cycle benefits with respect to energy consumption and carbon dioxide emissions," Energy, Elsevier, vol. 96(C), pages 603-613.
    16. Lampropoulos, Ioannis & van den Broek, Machteld & van der Hoofd, Erik & Hommes, Klaas & van Sark, Wilfried, 2018. "A system perspective to the deployment of flexibility through aggregator companies in the Netherlands," Energy Policy, Elsevier, vol. 118(C), pages 534-551.
    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. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    2. Kayhan Alamatsaz & Sadam Hussain & Chunyan Lai & Ursula Eicker, 2022. "Electric Bus Scheduling and Timetabling, Fast Charging Infrastructure Planning, and Their Impact on the Grid: A Review," Energies, MDPI, vol. 15(21), pages 1-39, October.
    3. Ali Saadon Al-Ogaili & Ali Q. Al-Shetwi & Hussein M. K. Al-Masri & Thanikanti Sudhakar Babu & Yap Hoon & Khaled Alzaareer & N. V. Phanendra Babu, 2021. "Review of the Estimation Methods of Energy Consumption for Battery Electric Buses," Energies, MDPI, vol. 14(22), pages 1-28, November.
    4. Ma, Xiaolei & Miao, Ran & Wu, Xinkai & Liu, Xianglong, 2021. "Examining influential factors on the energy consumption of electric and diesel buses: A data-driven analysis of large-scale public transit network in Beijing," Energy, Elsevier, vol. 216(C).
    5. Zeng, Ziling & Wang, Shuaian & Qu, Xiaobo, 2022. "On the role of battery degradation in en-route charge scheduling for an electric bus system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    6. 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.
    7. Jean-Michel Clairand & Paulo Guerra-Terán & Xavier Serrano-Guerrero & Mario González-Rodríguez & Guillermo Escrivá-Escrivá, 2019. "Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies," Energies, MDPI, vol. 12(16), pages 1-22, August.
    8. He, Yi & Liu, Zhaocai & Song, Ziqi, 2020. "Optimal charging scheduling and management for a fast-charging battery electric bus system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    9. 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).
    10. Teresa Pamuła & Wiesław Pamuła, 2020. "Estimation of the Energy Consumption of Battery Electric Buses for Public Transport Networks Using Real-World Data and Deep Learning," Energies, MDPI, vol. 13(9), pages 1-17, May.
    11. 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).
    12. Zhao, Li & Ke, Hanchen & Huo, Weiwei, 2023. "A frequency item mining based energy consumption prediction method for electric bus," Energy, Elsevier, vol. 263(PD).
    13. 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).
    14. Manzolli, Jônatas Augusto & Trovão, João Pedro & Antunes, Carlos Henggeler, 2022. "A review of electric bus vehicles research topics – Methods and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    15. Li, Pengshun & Zhang, Yi & Zhang, Yi & Zhang, Kai & Jiang, Mengyan, 2021. "The effects of dynamic traffic conditions, route characteristics and environmental conditions on trip-based electricity consumption prediction of electric bus," Energy, Elsevier, vol. 218(C).
    16. Xinkuo Xu & Xiaofeng Lv & Liyan Han, 2019. "Carbon Asset of Electrification: Valuing the Transition from Fossil Fuel-Powered Buses to Battery Electric Buses in Beijing," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
    17. Gallet, Marc & Massier, Tobias & Hamacher, Thomas, 2018. "Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks," Applied Energy, Elsevier, vol. 230(C), pages 344-356.
    18. 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.
    19. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2020. "A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies," Applied Energy, Elsevier, vol. 261(C).
    20. Xinkuo Xu & Liyan Han, 2020. "Operational Lifecycle Carbon Value of Bus Electrification in Macau," Sustainability, MDPI, vol. 12(9), pages 1-18, May.

    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:172:y:2023:i:c:s136655452300073x. 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.