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Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study

Author

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  • Soha Saad

    (Laboratoire de Génie Electrique et Electronique de Paris, Centrale Supélec, CNRS, Université Paris-Saclay, 91192 Gif-sur-Yvette, France
    CNRS, LS2N, 44200 Nantes, France
    SNCF Réseau, Direction de L’Ingénierie, 6 Avenue Francois Mitterand, 95574 La Plaine St-Denis, France)

  • Florence Ossart

    (Laboratoire de Génie Electrique et Electronique de Paris, Centrale Supélec, CNRS, Université Paris-Saclay, 91192 Gif-sur-Yvette, France)

  • Jean Bigeon

    (CNRS, LS2N, 44200 Nantes, France)

  • Etienne Sourdille

    (SNCF Réseau, Direction de L’Ingénierie, 6 Avenue Francois Mitterand, 95574 La Plaine St-Denis, France)

  • Harold Gance

    (SNCF Réseau, Direction de L’Ingénierie, 6 Avenue Francois Mitterand, 95574 La Plaine St-Denis, France)

Abstract

The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper proposes the use of sensitivity analysis in order to evaluate the influence of different traffic adjustment actions (e.g., spacing between trains and speed reduction) on the train supply voltage, which must never drop below the critical value prescribed by technical standards. Three global sensitivity analysis methods dedicated to black box, multivariate, nonlinear models are considered: generalized Sobol indices, energy distance-based indices, and regional sensitivity analysis. The three methods are applied to a simple traffic rescheduling test case and give similar results, but at different costs. Regional sensitivity analysis appears to be the most suitable method for the present application: it is easy to implement, rather fast, and accounts for constraints on the system output (a key feature for electrical incident management). The application of this method to a test case representative of a real rescheduling problem shows that it provides the information needed by the traffic manager to reschedule traffic in an efficient way. The same type of approach can be used for any power system optimization problem with the same characteristics.

Suggested Citation

  • Soha Saad & Florence Ossart & Jean Bigeon & Etienne Sourdille & Harold Gance, 2021. "Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study," Energies, MDPI, vol. 14(19), pages 1-29, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6420-:d:651653
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    References listed on IDEAS

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    1. Chuan Qin & Yuqing Jin & Meng Tian & Ping Ju & Shun Zhou, 2023. "Comparative Study of Global Sensitivity Analysis and Local Sensitivity Analysis in Power System Parameter Identification," Energies, MDPI, vol. 16(16), pages 1-21, August.

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