Efficient Formulations and Decomposition Approaches for Power Peak Reduction in Railway Traffic via Timetabling

Andreas Bärmann (), Alexander Martin () and Oskar Schneider ()
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Andreas Bärmann: Department Mathematik, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Alexander Martin: Department Mathematik, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany
Oskar Schneider: Gruppe Optimization, Fraunhofer Arbeitsgruppe für Supply Chain Services SCS, Fraunhofer-Institut für Integrierte Schaltungen IIS, 90411 Nürnberg, Germany

Transportation Science, 2021, vol. 55, issue 3, 747-767

Abstract: Over the last few years, optimization models for the energy-efficient operation of railway traffic have received more and more attention, particularly in connection with timetable design. In this work, we study the effect of load management via timetabling. The idea is to consider trains as time-flexible consumers in the railway power supply network and to use slight shifts in the departure times from the stations to avoid too many simultaneous departures. This limits peak consumption and can help to improve the stability of the power supply. To this end, we derive efficient formulations for the problem of an optimal timetable adjustment based on a given timetable draft, two of which even allow for totally unimodular polyhedral descriptions. The proper choice of the objective function allows the incorporation of the priorities of either the train operating companies or the infrastructure manager. These include the avoidance of large peaks in average or instantaneous consumption and the improved use of recuperated braking energy. To solve the arising optimization models efficiently, we develop specially tailored exact Benders decomposition schemes that allow for the computation of high-quality solutions within a very short time. In an extensive case study for German railway passenger traffic, we show that our methods are capable of solving the problem on a nationwide scale. We see that the optimal adjustment of timetables entails a tremendous potential for reducing energy consumption.

Keywords: railway timetabling; energy efficiency; total unimodularity; decomposition; mixed-integer programming (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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