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A Simulation Approach for Optimising Energy-Efficient Driving Speed Profiles in Metro Lines

Author

Listed:
  • Mariano Gallo

    (Department of Engineering, University of Sannio, Piazza Roma 21, 82100 Benevento, Italy)

  • Marilisa Botte

    (Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Via Claudio 21, 80125 Naples, Italy)

  • Antonio Ruggiero

    (Rete Ferroviaria Italiana S.P.A. (RFI), Via Marsala 75, 00185 Rome, Italy)

  • Luca D’Acierno

    (Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Via Claudio 21, 80125 Naples, Italy)

Abstract

We propose a model for optimising driving speed profiles on metro lines to reduce traction energy consumption. The model optimises the cruising speed to be maintained on each section between two stations; the functions that link the cruising speed to the travel time on the section and the corresponding energy consumption are built using microscopic railway simulation software. In addition to formulating an optimisation model and its resolution through a gradient algorithm, the problem is also solved by using a simulation model and the corresponding optimisation module, with which stochastic factors may be included in the problem. The results are promising and show that traction energy savings of over 25% compared to non-optimised operations may be achieved.

Suggested Citation

  • Mariano Gallo & Marilisa Botte & Antonio Ruggiero & Luca D’Acierno, 2020. "A Simulation Approach for Optimising Energy-Efficient Driving Speed Profiles in Metro Lines," Energies, MDPI, vol. 13(22), pages 1-17, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6038-:d:447428
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    References listed on IDEAS

    as
    1. Wang, Pengling & Goverde, Rob M.P., 2019. "Multi-train trajectory optimization for energy-efficient timetabling," European Journal of Operational Research, Elsevier, vol. 272(2), pages 621-635.
    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. Alejandro Cunillera & Adrián Fernández-Rodríguez & Asunción P. Cucala & Antonio Fernández-Cardador & Maria Carmen Falvo, 2020. "Assessment of the Worthwhileness of Efficient Driving in Railway Systems with High-Receptivity Power Supplies," Energies, MDPI, vol. 13(7), pages 1-24, April.
    4. Phil Howlett, 2000. "The Optimal Control of a Train," Annals of Operations Research, Springer, vol. 98(1), pages 65-87, December.
    5. Liu, Rongfang (Rachel) & Golovitcher, Iakov M., 2003. "Energy-efficient operation of rail vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 917-932, December.
    6. Luca D’Acierno & Marilisa Botte, 2018. "A Passenger-Oriented Optimization Model for Implementing Energy-Saving Strategies in Railway Contexts," Energies, MDPI, vol. 11(11), pages 1-25, October.
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    Cited by:

    1. Gianfranco Di Lorenzo & Erika Stracqualursi & Rodolfo Araneo, 2022. "The Journey Towards the Energy Transition: Perspectives from the International Conference on Environment and Electrical Engineering (EEEIC)," Energies, MDPI, vol. 15(18), pages 1-5, September.
    2. Donato Morea & Stefano Elia & Chiara Boccaletti & Pasquale Buonadonna, 2021. "Improvement of Energy Savings in Electric Railways Using Coasting Technique," Energies, MDPI, vol. 14(23), pages 1-15, December.

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