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Reconciliation of Train-Run data and Train consumption data for a better traction energy consumption estimation, a new Tool

Authors :
SOURDILLE, Etienne
ROBBIANO, Sylvain
EL-HAIMOUR, Nourdine
TAUNAY, Lionel
Source :
Transportation Research Procedia; January 2023, Vol. 72 Issue: 1 p2716-2723, 8p
Publication Year :
2023

Abstract

The present work addresses the estimation of the traction energy using train-run data. The proper quantification of electrical traction energy by Railway Undertaking is necessary for energy settlement and billing by the different energy stakeholders such as energy suppliers as well as the infrastructure managers. The system thus needs a fair estimation of the train consumption most notably in case of missing data. Train-run data are used to compute an estimation at the train level and then aggregated at the Railway Undertaking level. We used an aggregate tree-based model for the estimation models using a set of different physical variables extrapolated from a train dynamic physical model. In turn, it has imposed another tool for the reconciliation between train-run data and consumption data at the vehicle level because often train-run data and consumption data are siloed.

Details

Language :
English
ISSN :
23521465
Volume :
72
Issue :
1
Database :
Supplemental Index
Journal :
Transportation Research Procedia
Publication Type :
Periodical
Accession number :
ejs64951343
Full Text :
https://doi.org/10.1016/j.trpro.2023.11.812