Data and digitalisation
Augmented Reality Futures Close
Augmented Reality (AR) technology will be used at Futures Close to convey and inform various audiences including vulnerable consumers about various property archetypes their construction heat loss and the type of retrofit solutions (heating systems controls fabric improvements) available to improve the level of domestic energy efficiency. AR will be used to inform educate and engage audiences on-site at Futures Close as well as off-site at conferences and meetings avoiding the need to facilitate multiple visits on site. Live data feeds will also be visualised illustrating room-by-room temperature humidity as well as other metrics providing an engaging interactive and informative asset for Futures Close.
Novel Unified Viewer for NGT Network Performance Twin
As part of the National Gas Network Performance Twin program this project is designed to demonstrate a scalable digital twin platform focused on improving infrastructure resilience supporting hydrogen integration and addressing climate adaptation across the National Transmission System (NTS). This initiative integrates three strategic components: Collaborative Visual Data Twin (CVDT) – a 3D BIM-based digital twin platform that visualises and monitors asset performance in real time. HyNTS Dataset Automation – a structured automated geodatabase that supports hydrogen readiness assessments and asset integrity modelling. Flood Twin – a predictive flood simulation model that enables scenario-based risk analysis and resilience planning for Above Ground Installations (AGIs).
Gas transmission asset resilience through network transitions Discovery
As the energy system transitions away from unabated natural gas and parts of the gas network are either decommissioned or repurposed to support the UK’s net zero goals there is an increased risk of unintentional third-party damage to the network. Any supply interruptions to the transmission network would directly impact security of supply across the country and have a significant cost to customers including power generators industry and domestic users. This project will investigate the benefits of moving from expensive low frequency manual network inspections to innovative AI assisted surveillance technologies in combination with satellite imagery and drones.
Asset Cortex – Generative AI for asset hierarchy
The Asset Cortex project is a Generative AI initiative by National Gas Transmission (NGT) aimed at transforming its legacy 4-level asset hierarchy into a deeper ISO 14224-compliant structure. This Proof of Concept (PoC) will explore the feasibility of using AI to infer component-level details from system-level data such as pressure and age enabling automated hierarchy generation. The project supports RIIO-GT3 objectives including predictive maintenance digital twin creation and improved asset lifecycle visibility. It will also enhance integration with systems like SAP and Copperleaf and streamline field force operations. Key phases include requirements capture data mapping AI model development benchmarking against manually collected data and final reporting. Grasby Bottom and Hatton Multi Junction sites will serve as testbeds. The project is expected to reduce manual effort improve scalability and lay the foundation for broader digital transformation. It will also inform IT infrastructure needs and data governance strategies. While the current phase focuses on feasibility successful validation could lead to full-scale deployment supporting NGT’s strategic goals around automation cost efficiency and sustainability. Asset Cortex is positioned as a foundational enabler for future infrastructure planning and operational excellence across the gas network.
Gas Transmission Data Sharing Infrastructure
This project will entail a feasibility study to assess the viability of developing a secure scalable and interoperable data sharing infrastructure for National Gas Transmission (NGT) supporting regulatory compliance stakeholder access and alignment with NESO’s DSI initiative. The main objective is to gain a better understanding of how we share data currently and how this will change moving forward both within established participants and enabling new participants and stakeholders to benefit from National Gas’s data. This will support the wider NESO led DSI initiative. Using two NGT data systems as a use case for this study
Pathfinder Enhancements
This project will update the Pathfinder tool to improve functionality and reflect more current underlying data. Use of the tool developed in this project should result in better choices regarding investment in energy saving measures
Digital Decommissioning of Large-Scale Equipment
As the Gas Transmission network responds to a changing energy system from drivers including the transition to net zero and to changes in supply and demand we are required to decommission our large site based assets in certain locations. Decommissioning is a multifaceted endeavour that goes beyond the conclusion of an asset’s lifespan and encompasses a complex deconstruction process. This project will implement an innovative AI tool to help National Gas manage decommissioning to drive benefits such as increasing the accuracy of cost estimation ways to reduce carbon emissions identify re-use potential and lower the overall time taken to decommission.
Lotus Notes Logbook Upgrade
NGN currently operate a Lotus Notes application with a bespoke electronic Logbook system to capture all of the activity with day and planned ahead that occurs within our gas control centre. This system has been in operation since 1997 and has proven to be a highly reliable and flexible tool to manage planned works faults general site activity and wider issues.
The current technology is outdated and contains years’ worth of data causing it to be slow. There are no links between Lotus notes and other vital control room applications (SCADA etc.). Raising faults becomes a tedious task and the Logbook and other in-apps are not user friendly. There are no updates available to improve the existing system.
The current system needs to be replaced but to achieve that we need a full exploration of where technology can deliver to our requirements and to fully explore the impact of net zero and what new functionality may be required to manage the transition to net zero.
This is an early stage feasibility project to understand all of the challenges opportunities and risks that UK GDNs face with their systems in order to help facilitate the transition to net zero energy systems.
Augmented Reality Futures Close
Augmented Reality (AR) technology will be used at Futures Close to convey and inform various audiences including vulnerable consumers about various property archetypes their construction heat loss and the type of retrofit solutions (heating systems controls fabric improvements) available to improve the level of domestic energy efficiency. AR will be used to inform educate and engage audiences on-site at Futures Close as well as off-site at conferences and meetings avoiding the need to facilitate multiple visits on site. Live data feeds will also be visualised illustrating room-by-room temperature humidity as well as other metrics providing an engaging interactive and informative asset for Futures Close.
Energy Plan Translator
Develop a flexible and adaptable toolset for the rapid analysis of Local Area Energy Plans (LAEPs). This will convert qualitative statements to quantified metrics and identify key network specific planning parameters.
GDN Gas Quality Forecasting
This project aims to develop a means of forecasting gas quality at the NTS offtakes which will support current arrangements for target Calorific Value (CV) setting allowing networks to more accurately provide target CVs to biomethane producers and reducing sudden changes in targets sent to biomethane sites which can cause operational problems. Going forward gas quality information on CV and potentially Wobbe will also assist the GDNs in managing hydrogen blend.