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Optimising Frequency-Based Railway Services with a Limited Fleet Endowment: An Energy-Efficient Perspective

Author

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  • Luca D’Acierno

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

  • Marilisa Botte

    (Department of Civil, Architectural and Environmental Engineering, Federico II University of Naples, Via Claudio 21, 80125 Naples, Italy
    Department of Agricultural Sciences, Federico II University of Naples, Via Università 100, 80055 Portici (NA), Italy)

Abstract

Energy-saving and energy-recovery strategies represent key factors to achieve operational cost reductions within rail systems’ management tasks. However, in altering service features, they also affect passenger satisfaction. This paper investigates the effect of implementing such measures in the case of rolling stock unavailability. Numerous operational scenarios were explored by analysing different planned headway and rolling stock configurations. The scenarios were simulated with and without the adoption of Energy-Saving Strategies (ESS), both in ordinary and in disruption conditions. Our results show that, in ordinary conditions, the optimal scenarios are those that minimise the planned headway. By contrast, in disrupted conditions, due to greater passenger inconvenience, the use of a time-optimal condition is preferable if a real-time adjustment of ESS is not feasible. However, if the ESS can be updated in real-time, use of ESS is preferable only if the adopted headway is the smallest of those associated with the rolling stock scheme considered.

Suggested Citation

  • Luca D’Acierno & Marilisa Botte, 2020. "Optimising Frequency-Based Railway Services with a Limited Fleet Endowment: An Energy-Efficient Perspective," Energies, MDPI, vol. 13(10), pages 1-26, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2403-:d:356788
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    References listed on IDEAS

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    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. Zhan, Shuguang & Kroon, Leo G. & Veelenturf, Lucas P. & Wagenaar, Joris C., 2015. "Real-time high-speed train rescheduling in case of a complete blockage," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 182-201.
    3. Gallo, Mariano, 2018. "Improving equity of urban transit systems with the adoption of origin-destination based taxi fares," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 38-55.
    4. 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. Sahil Bhagat & Jacopo Bongiorno & Andrea Mariscotti, 2023. "Influence of Infrastructure and Operating Conditions on Energy Performance of DC Transit Systems," Energies, MDPI, vol. 16(10), pages 1-26, May.
    2. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.

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