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Multi-modelling for decarbonisation in urban rail systems

Lookup NU author(s): Dr David Golightly, Dr Carl Gamble, Dr Roberto Palacin, Dr Ken Pierce

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

This paper demonstrates a methodology for flexible, dynamic systems modelling relevant to urban rail decarbonisation. Decarbonisation of urban rail is 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 & Wear Metro. These scenarios compared combinations of decarbonisation intervention (baseline rolling stock vs lightweight/regenerative braking rolling stock; baseline driving style vs 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.


Publication metadata

Author(s): Golightly D, Gamble C, Palacin R, Pierce K

Publication type: Article

Publication status: Published

Journal: Urban Rail Transit

Year: 2019

Volume: 5

Pages: 254-266

Online publication date: 15/11/2019

Acceptance date: 11/10/2019

Date deposited: 08/11/2019

ISSN (print): 2199-6687

ISSN (electronic): 2199-6679

Publisher: SpringerOpen

URL: https://doi.org/10.1007/s40864-019-00114-2

DOI: 10.1007/s40864-019-00114-2


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