Multi-modelling for Decarbonisation in Urban Rail Systems

This paper demonstrates a methodology for flexible, dynamic systems modelling relevant to urban rail decarbonisation. Decarbonisation of urban rail is a vital component of policy and strategy to minimize anthropogenic emissions. Decarbonisation is a systems problem, however, that needs to reflect th...

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Bibliographic Details
Published in:Urban rail transit 2019-12, Vol.5 (4), p.254-266
Main Authors: Golightly, David, Gamble, Carl, Palacin, Roberto, Pierce, Ken
Format: Article
Language:English
Subjects:
Anthropogenic factors
Automotive Engineering
Capital costs
Carbon
Computational Intelligence
Decarbonisation
Decarbonization
Dynamic modelling
Energy efficiency
Engineering
Foundations
Geoengineering
Human performance
Hydraulics
Intellectual property
Light rail transportation
Model testing
Multi-modelling
Original Research Papers
Power consumption
Power optimisation
Railway
Regenerative braking
Rolling stock
Systems modelling
Urban rail
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Summary:This paper demonstrates a methodology for flexible, dynamic systems modelling relevant to urban rail decarbonisation. Decarbonisation of urban rail is a vital component of policy and strategy to minimize anthropogenic emissions. Decarbonisation is a systems problem, however, that needs to reflect the interaction between components and processes. Dynamic computer modelling of systems for decarbonisation involves interfacing multiple models together and running them in parallel in order to observe and predict systems-level effects. This is challenging due to the diverse nature of models, achieving parallel model integration and concerns around intellectual property (IP). One solution is the multi-modelling paradigm, which supports integrated, diverse, secure interfacing of models. This paper demonstrates the application of the multi-modelling approach, using the INTO-CPS tool chain. A multi-model was developed comprising key components required for urban rail decarbonisation problems. This multi-model was tested for power consumption in four different scenarios with an example drawn from the Tyne and Wear Metro in Newcastle-upon-Tyne in the United Kingdom. These scenarios compared combinations of decarbonisation intervention (baseline rolling stock versus lightweight, regenerative braking rolling stock and baseline driving style versus energy-efficient defensive driving style), generating different power consumption profiles for each. As such, this serves as a proof of the application of the multi-modelling approach and demonstrates a number of benefits for flexible and rapid systems modelling. This paper fills a knowledge gap by demonstrating a potentially valuable tool for future systems-level decarbonisation challenges in urban rail.
ISSN:2199-6687
2199-6679
DOI:10.1007/s40864-019-00114-2