IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v294y2021ics0306261921004840.html
   My bibliography  Save this article

Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains

Author

Listed:
  • Kapetanović, Marko
  • Núñez, Alfredo
  • van Oort, Niels
  • Goverde, Rob M.P.

Abstract

Hybridization of diesel multiple unit railway vehicles is an effective approach to reduce fuel consumption and related emissions in regional non-electrified networks. This paper is part of a bigger project realized in collaboration with Arriva, the largest regional railway undertaking in the Netherlands, to identify optimal solutions in improving trains’ energy and environmental performance. A significant problem in vehicle hybridization is determining the optimal size for the energy storage system, while incorporating an energy management strategy as well as technical and operational requirements. With the primary requirement imposed by the railway undertaking to achieve emission-free and noise-free operation within railway stations, we formalize this as a bi-level multi-objective optimization problem, including vehicle performance, the trade-off between fuel savings and hybridization cost, influence of the energy management strategy, and other constraints. By deriving a Li-ion battery parameters at the cell level, a nested coordination framework is employed, where a brute force search finds the optimal battery size using dynamic programming for full controller optimization for each feasible solution. In this way, the global minimum for fuel consumption for each battery configuration is achieved. The results from a Dutch case study demonstrated fuel savings and CO2 emission reduction of more than 34% compared to a standard vehicle. Additionally, benefits in terms of local pollutants (NOx and PM) emissions are observed. Using an alternative sub-optimal rule-based control demonstrated a significant impact of the energy management on the results, reflected in higher fuel consumption and increased battery size together with corresponding costs.

Suggested Citation

  • Kapetanović, Marko & Núñez, Alfredo & van Oort, Niels & Goverde, Rob M.P., 2021. "Reducing fuel consumption and related emissions through optimal sizing of energy storage systems for diesel-electric trains," Applied Energy, Elsevier, vol. 294(C).
    • Handle: RePEc:eee:appene:v:294:y:2021:i:c:s0306261921004840
    DOI: 10.1016/j.apenergy.2021.117018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921004840
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117018?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. Luan, Xiaojie & Wang, Yihui & De Schutter, Bart & Meng, Lingyun & Lodewijks, Gabriel & Corman, Francesco, 2018. "Integration of real-time traffic management and train control for rail networks - Part 2: Extensions towards energy-efficient train operations," Transportation Research Part B: Methodological, Elsevier, vol. 115(C), pages 72-94.
    2. Meinert, M. & Prenleloup, P. & Schmid, S. & Palacin, R., 2015. "Energy storage technologies and hybrid architectures for specific diesel-driven rail duty cycles: Design and system integration aspects," Applied Energy, Elsevier, vol. 157(C), pages 619-629.
    3. Loïc Joud & Rui Da Silva & Daniela Chrenko & Alan Kéromnès & Luis Le Moyne, 2020. "Smart Energy Management for Series Hybrid Electric Vehicles Based on Driver Habits Recognition and Prediction," Energies, MDPI, vol. 13(11), pages 1-17, June.
    4. Scheepmaker, Gerben M. & Goverde, Rob M.P. & Kroon, Leo G., 2017. "Review of energy-efficient train control and timetabling," European Journal of Operational Research, Elsevier, vol. 257(2), pages 355-376.
    5. Wang, Jinghui & Rakha, Hesham A., 2017. "Electric train energy consumption modeling," Applied Energy, Elsevier, vol. 193(C), pages 346-355.
    6. Cipek, Mihael & Pavković, Danijel & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2019. "Assessment of battery-hybrid diesel-electric locomotive fuel savings and emission reduction potentials based on a realistic mountainous rail route," Energy, Elsevier, vol. 173(C), pages 1154-1171.
    7. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    8. Meinert, M. & Melzer, M. & Kamburow, C. & Palacin, R. & Leska, M. & Aschemann, H., 2015. "Benefits of hybridisation of diesel driven rail vehicles: Energy management strategies and life-cycle costs appraisal," Applied Energy, Elsevier, vol. 157(C), pages 897-904.
    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. Zdenko Kljaić & Danijel Pavković & Mihael Cipek & Maja Trstenjak & Tomislav Josip Mlinarić & Mladen Nikšić, 2023. "An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport," Future Internet, MDPI, vol. 15(11), pages 1-44, October.
    2. Zhang, Hao & Lei, Nuo & Wang, Zhi, 2024. "Ammonia-hydrogen propulsion system for carbon-free heavy-duty vehicles," Applied Energy, Elsevier, vol. 369(C).
    3. Marko Kapetanović & Mohammad Vajihi & Rob M. P. Goverde, 2021. "Analysis of Hybrid and Plug-In Hybrid Alternative Propulsion Systems for Regional Diesel-Electric Multiple Unit Trains," Energies, MDPI, vol. 14(18), pages 1-29, September.
    4. Zhang, Chi & Zeng, Guohong & Wu, Jian & Wei, Shaoyuan & Zhang, Weige & Sun, Bingxiang, 2023. "Integrated optimization of driving strategy and energy management for hybrid diesel multiple units," Energy, Elsevier, vol. 281(C).
    5. Wang, Weida & Chen, Yincong & Yang, Chao & Li, Ying & Xu, Bin & Xiang, Changle, 2022. "An enhanced hypotrochoid spiral optimization algorithm based intertwined optimal sizing and control strategy of a hybrid electric air-ground vehicle," Energy, Elsevier, vol. 257(C).
    6. Antonio Gabaldón & Ana García-Garre & María Carmen Ruiz-Abellón & Antonio Guillamón & Roque Molina & Juan Medina, 2023. "Management of Railway Power System Peaks with Demand-Side Resources: An Application to Periodic Timetables," Sustainability, MDPI, vol. 15(3), pages 1-27, February.
    7. Joo Won Lee & Emily Craparo & Giovanna Oriti & Arthur Krener, 2022. "Optimizing Fuel Efficiency on an Islanded Microgrid under Varying Loads," Energies, MDPI, vol. 15(21), pages 1-21, October.
    8. Hu, Ting & Wang, Ting & Yan, Qingyun & Chen, Tiexi & Jin, Shuanggen & Hu, Jun, 2022. "Modeling the spatiotemporal dynamics of global electric power consumption (1992–2019) by utilizing consistent nighttime light data from DMSP-OLS and NPP-VIIRS," Applied Energy, Elsevier, vol. 322(C).
    9. Emrani, Anisa & Berrada, Asmae & Bakhouya, Mohamed, 2022. "Optimal sizing and deployment of gravity energy storage system in hybrid PV-Wind power plant," Renewable Energy, Elsevier, vol. 183(C), pages 12-27.
    10. Chen, Shuang & Hu, Minghui & Lei, Yanlei & Kong, Linghao, 2023. "Novel hybrid power system and energy management strategy for locomotives," Applied Energy, Elsevier, vol. 348(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. Marko Kapetanović & Mohammad Vajihi & Rob M. P. Goverde, 2021. "Analysis of Hybrid and Plug-In Hybrid Alternative Propulsion Systems for Regional Diesel-Electric Multiple Unit Trains," Energies, MDPI, vol. 14(18), pages 1-29, September.
    2. Yuan, Weichang & Frey, H. Christopher, 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving," Applied Energy, Elsevier, vol. 268(C).
    3. Mo, Pengli & D’Ariano, Andrea & Yang, Lixing & Veelenturf, Lucas P. & Gao, Ziyou, 2021. "An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 283-321.
    4. Ovalle, Andres & Pouget, Julien & Bacha, Seddik & Gerbaud, Laurent & Vinot, Emmanuel & Sonier, Benoît, 2018. "Energy storage sizing methodology for mass-transit direct-current wayside support: Application to French railway company case study," Applied Energy, Elsevier, vol. 230(C), pages 1673-1684.
    5. Cipek, Mihael & Pavković, Danijel & Krznar, Matija & Kljaić, Zdenko & Mlinarić, Tomislav Josip, 2021. "Comparative analysis of conventional diesel-electric and hypothetical battery-electric heavy haul locomotive operation in terms of fuel savings and emissions reduction potentials," Energy, Elsevier, vol. 232(C).
    6. Zhang, Yongxiang & D'Ariano, Andrea & He, Bisheng & Peng, Qiyuan, 2019. "Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 127(C), pages 237-278.
    7. Li, Wenxin & Peng, Qiyuan & Wen, Chao & Wang, Pengling & Lessan, Javad & Xu, Xinyue, 2020. "Joint optimization of delay-recovery and energy-saving in a metro system: A case study from China," Energy, Elsevier, vol. 202(C).
    8. Oke, Jimi B. & Akkinepally, Arun Prakash & Chen, Siyu & Xie, Yifei & Aboutaleb, Youssef M. & Azevedo, Carlos Lima & Zegras, P. Christopher & Ferreira, Joseph & Ben-Akiva, Moshe, 2020. "Evaluating the systemic effects of automated mobility-on-demand services via large-scale agent-based simulation of auto-dependent prototype cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 98-126.
    9. Zdenko Kljaić & Danijel Pavković & Mihael Cipek & Maja Trstenjak & Tomislav Josip Mlinarić & Mladen Nikšić, 2023. "An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport," Future Internet, MDPI, vol. 15(11), pages 1-44, October.
    10. Yang, Songpo & Liao, Feixiong & Wu, Jianjun & Timmermans, Harry J.P. & Sun, Huijun & Gao, Ziyou, 2020. "A bi-objective timetable optimization model incorporating energy allocation and passenger assignment in an energy-regenerative metro system," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 85-113.
    11. Atiquzzaman Khan Ankur & Stefan Kraus & Thomas Grube & Rui Castro & Detlef Stolten, 2022. "A Versatile Model for Estimating the Fuel Consumption of a Wide Range of Transport Modes," Energies, MDPI, vol. 15(6), pages 1-24, March.
    12. Yang, Songpo & Chen, Yanyan & Dong, Zhurong & Wu, Jianjun, 2023. "A collaborative operation mode of energy storage system and train operation system in power supply network," Energy, Elsevier, vol. 276(C).
    13. Aredah, Ahmed & Du, Jianhe & Hegazi, Mohamed & List, George & Rakha, Hesham A., 2024. "Comparative analysis of alternative powertrain technologies in freight trains: A numerical examination towards sustainable rail transport," Applied Energy, Elsevier, vol. 356(C).
    14. Xie, Yunkun & Li, Yangyang & Zhao, Zhichao & Dong, Hao & Wang, Shuqian & Liu, Jingping & Guan, Jinhuan & Duan, Xiongbo, 2020. "Microsimulation of electric vehicle energy consumption and driving range," Applied Energy, Elsevier, vol. 267(C).
    15. Yashraj Tripathy & Andrew McGordon & Anup Barai, 2020. "Improving Accessible Capacity Tracking at Low Ambient Temperatures for Range Estimation of Battery Electric Vehicles," Energies, MDPI, vol. 13(8), pages 1-18, April.
    16. K. S. Reddy & S. Aravindhan & Tapas K. Mallick, 2017. "Techno-Economic Investigation of Solar Powered Electric Auto-Rickshaw for a Sustainable Transport System," Energies, MDPI, vol. 10(6), pages 1-15, May.
    17. Stefano De Pinto & Pablo Camocardi & Christoforos Chatzikomis & Aldo Sorniotti & Francesco Bottiglione & Giacomo Mantriota & Pietro Perlo, 2020. "On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems," Energies, MDPI, vol. 13(13), pages 1-24, June.
    18. Nan, Sirui & Tu, Ran & Li, Tiezhu & Sun, Jian & Chen, Haibo, 2022. "From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus," Energy, Elsevier, vol. 261(PA).
    19. Tuyen Nguyen & Yannick Rauch & Reiner Kriesten & Daniela Chrenko, 2023. "Approach for a Global Route-Based Energy Management System for Electric Vehicles with a Hybrid Energy Storage System," Energies, MDPI, vol. 16(2), pages 1-20, January.
    20. Huang, Hai-chao & He, Hong-di & Peng, Zhong-ren, 2024. "Urban-scale estimation model of carbon emissions for ride-hailing electric vehicles during operational phase," Energy, Elsevier, vol. 293(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:appene:v:294:y:2021:i:c:s0306261921004840. 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/405891/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.