Back in May 2024, the DAFNI programme announced its funding opportunity which focused on infrastructure resilience and data sharing opportunities and barriers. We have recently held a project closure wrap up session with DAFNI’s three transport and three energy projects, who presented their progress and outputs available on DAFNI.
Dr Quichen Lu presenting at the DAFNI Networkshop
ClimaTRACKS: forecasting resilience of railway networks under propagating uncertainty
The project focused on forecasting resilience of railway networks under propagating uncertainty in weather events and asset failures, to help combat the rise of weather-related disruptions on railway services.
They achieved data integration across datasets with diverse codification, including weather conditions, vegetation line side and historical rail delay data. The team used logistic regression to make predictions and developed algorithms to build and perform simulations. They were able to predict incidents and map predicted conditions of the rails to develop route building.
Stakeholders consulted include Network Rail and UKRI, and the team is attending the Dresden Rail Conference to present the results.
Outputs uploaded onto DAFNI:
- Aggregated datasets of weather-related disruptions
- A weather-related risk map of the railway network in the Anglia region
- Risk mapping software (in Python)
Next steps will include adding the option to include user preferences to help them build a route tailored to their needs.
Contact: Giuliano Punzo
MARS: Modelling Aviation Resilience Scenarios
The project tackled the challenge of how to divert aircraft should the UK lose one of the major airports. When an airport shuts down due to weather, technical failure, or security concerns, multiple aircraft require immediate diversion to suitable alternative airports.
With increasing flight movements and high runway utilisation, the capacity at alternates is often limited, escalating the complexity of the response. This project was launched to create a computational model that simulates how an airport closure affects the broader aviation network, facilitating a coordinated, data-driven response.
As well as keeping in touch with industry throughout the project, the team liaised with Eurocontrol, the pan-European air navigation organisation, to see what’s being developed from their side and how MARS could support and complement this.
Stakeholders consulted primarily included the Operation Directors Liaison Group (a cross-industry group where all major UK aviation stakeholders are represented, the Department of Transport, he Civil Aviation Authority, National Air Traffic Services (NATS), as well as the Airports UK Trade Association.
Outputs uploaded onto DAFNI:
- A mock dataset allowing users to test out differing scenarios for closure of any of the 34 major airports in the dataset
- The simulation tool, its algorithm, and documentation
- The heat map of diversions in a visualisation through Jupyter notebook
BRINES: Building Risk-Informed Redundancy in Net-zero Energy Systems
Dr Hannah Bloomfield presenting at the DAFNI Networkshop
Energy systems are becoming more weather dependent, in line with increasing reliance on wind and solar power. This, combined with increased use of electricity and more extreme weather events due to climate change, means it’s critical to understand how much redundancy there is in energy systems – how much slack is available should there be an issue with one of the generators.
The BRINES interdisciplinary team involves meteorologists, energy and transport systems modellers. They are working with stakeholders including the Climate Change Commission (CCC), National Grid and OFGEM.
Outputs uploaded onto DAFNI:
- Security of supply datasets
- Infrastructure damage datasets
- Redundancy model workflow
- All datasets with historical weather data (ERA5) and future climate predictions
Dissemination efforts include finalising three papers as well as seven conference presentations and two poster presentations.
Next steps include revisiting the framework and making sure modelling inputs into the redundancy model are consistent, analysing more types of infrastructure extremes. On a larger scale, they plan to extend to European scale and to conduct combined security of supply and operational extremes stress testing.
FORNet: DAFNI Forecasting services for energy networks
The project captured the behavioural aspects of energy consumption. The idea is quite simple but it is hard to implement real-time forecasting of electricity demand, due to changing behaviour of consumers, affected by external triggers, such as weather or extreme events, as well as tariff changes or cheaper electricity at certain times.
Dissemination includes forthcoming work on journal papers, LinkedIn activity and DAFNI events.
Outputs uploaded onto DAFNI:
- Real and simulated datasets: one which is a real dataset with 36 houses from Energy Catapult and temperature data, combined with behavioural data for 9 events through 2020-21
- Python code embedded in a DAFNI workflow
Next steps include aiming for a full national scale project in partnership with the grid, ONS, energy providers and government.
IMPACT: Improving flood-disrupted road networks resilience with dynamic people-centric digital twins
In the UK, escalating floods increasingly affect people and property, intensifying pressure on national road networks.
The project took London as a case study and focused on 3 challenges across the UK road networks: dynamic risk, cross-domain integration including integrated flood-road-user characteristics, and multimodal.
Key stakeholders include the Digital Road of the Future Program, University of Cambridge, Cranfield University, UCL, Loughborough and Vercity Ltd.
Dissemination efforts include one journal paper already published and a further two journal papers submitted, as well as conference papers and posters in the UK and overseas.
Outputs uploaded onto DAFNI:
- The dynamic people-centric digital twin, including a web platform demonstrator on DAFNI, a trial platform with the London case study, and the novel user-road-flood data sharing strategies for multi-scale and multi-modal traffic data (bicycle, bus and cars).
Next steps – they plan to establish multimodal data as a basis for multimodal digital twins to predict and analyse risk.
Contact: Dr. Qiuchen Lu, qiuchen.lu@ucl.ac.uk
D-RES: Provision of distributed grid resilience using EVs during extreme weather events
Our existing electrical infrastructure is at risk from the growing Electric Vehicle (EV) numbers as well as from the increasing frequency of extreme weather events. Nevertheless, EVs could also be used as mobile back-up batteries in an extreme weather event, to keep the heating and lights on, providing distributed grid resilience.
The D-RES project moved weather-informed adaptive strategies for energy management forward, focusing on electric vehicles and storms.
The Orkney Islands was chosen as the study area, as it presents a microcosm of how the UK may look in the future, with an increasing number of storms and high penetration of renewable energy. However, high winds and storms don’t always allow for high electricity generation outputs and can lead to an increase in electricity demand for heating and lighting, and turn-down of wind energy generators.
Work with stakeholders included network operators, local councils, people who are engaging with communities, two full day workshops, presenting work at external events including Risk and Resilience Day in March 2025.
Dissemination work includes outreach on LinkedIn, creating a webspace for D-RES on University of Edinburgh’s site and academic publications which will be disseminated internationally
Outputs uploaded onto DAFNI:
- A D-RES decision framework to help responses pre-, during and post-event.
- A network flow model to demonstrate environmental and economic benefits.
Next steps – D-RES 2.0 is looking for collaborators in order to expand the framework across three dimensions: place-based case studies (e.g. urban and/or outside of the UK), other extreme weather events beyond storms (e.g. flooding), looking at other flexibility provision beyond EVs.