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

doi: 10.3390/en13226038
handle: 11588/823938
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.
- University Federico II of Naples Italy
- University of Sannio Italy
- University of Sannio Italy
Technology, railway sector, metro lines, driving speed profiles, T, energy-saving, simulation, energy-saving, railway sector, metro lines, driving speed profiles, simulation
Technology, railway sector, metro lines, driving speed profiles, T, energy-saving, simulation, energy-saving, railway sector, metro lines, driving speed profiles, simulation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).10 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
