IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2746-d1056019.html
   My bibliography  Save this article

Management of Railway Power System Peaks with Demand-Side Resources: An Application to Periodic Timetables

Author

Listed:
  • Antonio Gabaldón

    (Power Systems Group, Universidad Politécnica de Cartagena, 30203 Cartagena, Spain)

  • Ana García-Garre

    (Power Systems Group, Universidad Politécnica de Cartagena, 30203 Cartagena, Spain)

  • María Carmen Ruiz-Abellón

    (Department of Applied Mathematics and Statistics, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain)

  • Antonio Guillamón

    (Department of Applied Mathematics and Statistics, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain)

  • Roque Molina

    (Department of Applied Mathematics and Statistics, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain)

  • Juan Medina

    (Department of Applied Mathematics and Statistics, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain)

Abstract

The objective of this paper involves the analysis of opportunities for the management of Railway Systems’ demand using Physical-Based models and aggregation tools well-known in “conventional” Power Systems to develop and enlarge the portfolio of Distributed Energy Resources. This proposed framework would also enable the use of railway flexible resources to their use in Power Systems. The work considers trends for the development of railway transportation units through the adoption of technologies that increase the flexibility of railway units. For instance, we mean a set of resources such as onboard generation in dual units, energy storage and generation in last-mile units, and auxiliary loads. Their inherent flexibility can contribute to increasing the management possibilities of the overall net demand. The proposed scenario under study faces some of the energy concerns of periodic timetables: fast and high-power peaks in demand unknown in conventional Power Systems. The simulation results present the achieved flexibility and its potential: a decrease in peak demand by around 20% and an increase in energy recovery by 10%, lagging new investments in infrastructure. These results improve the social and economic benefits of railway transportation on the overall energy and environmental objectives while reducing energy concerns due to the increasing use of railways and boosting the sustainability of the transportation system in the coming decades.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2746-:d:1056019
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2746/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2746/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Franciszek Restel & Szymon Mateusz Haładyn, 2022. "The Railway Timetable Evaluation Method in Terms of Operational Robustness against Overloads of the Power Supply System," Energies, MDPI, vol. 15(17), pages 1-17, September.
    2. 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).
    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. 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).
    2. 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.
    3. Artur Kierzkowski & Agnieszka A. Tubis, 2023. "Transportation Systems Modeling, Simulation and Analysis with Reference to Energy Supplying," Energies, MDPI, vol. 16(8), pages 1-6, April.
    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. 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.
    6. 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.
    7. 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).
    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. 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.

    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:gam:jsusta:v:15:y:2023:i:3:p:2746-:d:1056019. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.