Modelling Cross-Sector Data Flows: A Simula on Framework for Energy-Rail Data Sharing Infrastructure
Supervisor: Dr Runze Cheng
Partner: SP Energy Networks (SPEN)
School: Engineering
Description:
Achieving full decarbonisation of the UK rail and electricity sectors increasingly depends on the ability of both systems to exchange timely, high-quality data. The University of Glasgow’s £0.6m ConnectRail Hub project, in collaboration with SP Energy Networks (SPEN) and Network Rail, is addressing this challenge by designing a secure, interoperable Data Sharing Infrastructure (DSI) to support cross-sector operational coordination, digital twinning, and integrated decision-making. However, the development and validation of such an infrastructure requires a simulation environment that can model the behaviour of data flows, system interactions, and cyber-physical constraints before real-world deployment. At present, no such simulation framework exists for the energy-rail DSI domain.
This internship project aims to address this gap by developing the foundations of a simulation model for the ConnectRail Hub DSI, using tools like Python or MATLAB. The resulting modelling environment will allow researchers and industry partners to test data-exchange mechanisms, assess performance under varying operating conditions, and explore how the DSI can support predictive analytics, digital twinning, and cross-sector operational scenarios. The project will align directly with, and be supervised in collaboration with, the ConnectRail Hub research team and SPEN, ensuring relevance to ongoing industry-led innovation. Over a ten-week period, the intern will pursue three core objectives:
Objective 1 – Develop a conceptual modelling framework for the DSI: Define the key entities, data flows, and system boundaries required to represent the ConnectRail Hub DSI in a simulation environment. This includes identifying data producers, consumers, timing constraints, and cyber-physical interactions informed by the ongoing ConnectRail Hub work packages
Objective 2 – Build an initial simulation prototype in Python or MATLAB: Implement the foundational simulation components, such as data-flow pathways, latency and throughput modelling, communication constraints, and basic behavioural logic for grid–rail interactions. The prototype should be modular, enabling future expansion toward digital twinning and more advanced analytics.
Objective 3 – Demonstrate and evaluate simulation scenarios: Use the prototype to run simple but illustrative scenarios demonstrating how data flows support operational decision-making within the DSI. Develop basic performance metrics and provide recommendations on how the model could be extended by the ConnectRail Hub team for future research and system-testing needs.
This project provides the intern with experience in simulation modelling, cyber-physical infrastructure, energy–rail systems integration, and stakeholder engagement, while contributing the foundations to available research tool to an active national-scale innovation effort.