Projects: Projects for Investigator |
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Reference Number | ENA_10063754 | |
Title | Intelligent Gas Grid - Beta | |
Status | Started | |
Energy Categories | Renewable Energy Sources(Bio-Energy, Other bio-energy) 10%; Other Cross-Cutting Technologies or Research(Energy system analysis) 10%; Fossil Fuels: Oil Gas and Coal(Oil and Gas, Refining, transport and storage of oil and gas) 80%; |
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Research Types | Applied Research and Development 100% | |
Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 60%; ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 40%; |
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UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
Principal Investigator |
Project Contact No email address given SGN |
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Award Type | Network Innovation Allowance | |
Funding Source | Ofgem | |
Start Date | 01 August 2023 | |
End Date | 01 August 2026 | |
Duration | 36 months | |
Total Grant Value | £6,304,121 | |
Industrial Sectors | Energy | |
Region | South East | |
Programme | ||
Investigators | Principal Investigator | Project Contact , SGN (100.000%) |
Industrial Collaborator | Project Contact , Wales and West Utilities (0.000%) Project Contact , Cadent Gas (0.000%) |
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Web Site | https://smarter.energynetworks.org/projects/10063754 |
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Objectives | ||
Abstract | "The projects scope is tightly aligned with SIFs data and digitalisation challenge criteria:Automated pressure management software, and use of near real time data and machine-learning techniques, will contribute to better coordination, planning and network optimisation.Increased injection of biomethane (and, in the future, hydrogen) into networks will enable progress towards net zero and enable strategic outcomes from other challenges e.g., decarbonisation of heat.The project directly addresses two points in the challenge scope:Point 7: this project will use novel sensor technology to improve visibility of network infrastructure condition, and make data-driven decisions about that infrastructurePoint 9: this project will use data, combined with machine-learning (ML) and artificial intelligence (AI) techniques, to improve the forecasting abilities of both demand on networks, and required maintenance and interventions.The principal innovation underscoring the project is use of data-driven techniques, based on ML & AI technology, acting in combination with remote pressure control and network extremity monitoring equipment deployed to networks in a distributed digitalised architecture. The innovation evolved from Utonomys current solution, which uses manually-generated schedules, to offer a novel method for UK gas distribution network management and digitalisation.From Alpha to Beta, the project evolved by taking a tiered approach to eight opportunity areas reflecting Discovery phase feasibility study outputs. Opportunities were progressed through targeted user research and collection of operational data, and, for highest ranked opportunities, Alpha phase activities extended to bench-testing proof-of-concept models designed to de-risk development and implementation of solutions at Beta phase. In addition, Alpha activities included a further evaluation of opportunities benefits and definition of field trial stages.The projects perception of the problem evolved from Alpha to Beta via a series of user interviews with representatives of key SGN stakeholders: Network Planning, Maintenance, Operational Technology, Policy, and Innovation. Key learnings were;Opportunities to reduce methane leakage and create holistic management dashboards were the most mature.Prediction of escapes was important to stakeholders but a definitive link between pressure and escapes could not be established from the data available in Alpha.Factors that lead to low pressure incidents showed the most potential from the second tier of opportunities.That increasing biomethane injection had a clear need within SGN.In Beta, core users of innovations will come from: Maintenance teams, who are looking for faster resolution of network problems and fewer truck rolls to manually adjust governors; Network Planning teams who are looking for lower methane emissions; and Biomethane teams who are looking for greater injection rates.Utonomy will be the main project partner at Beta, continuing itssuccessful history of collaboration with SGN. The Utonomy engineering team has capabilities in electronics design for hazardous areas, data science and machine learning, industrial IoT and digital communications technologies, cyber security, and cloud-hosted software applications. Utonomy has collaborated successfully with SGN and Wales & West Utilities on the development and trial of its remote pressure control and management solution. Utonomy has developed and carried out initial field trialsof Intelligent Control software via an Innovate UK funded project completed in March 2022 and is in the process of trialling a medium pressure variant of its pressure control equipment with Northern Gas Networks and Wales & West Utilities.Utonomy will use Faculty Science Limited as lead subcontractor. Faculty has the unique capability to deliver state-of-the-art AI solutions from teams formed from over 200 professionals comprising both technical and commercial experts. In delivering AI solutions, in-house developed AI Engines allow specialised techniques to be applied to customer problems and to optimise performance.As a world-class engineering consultancy with a range of multi-discipline technical specialists, DNV will leverage further expertise from their pool of Gas Industry experts to provide third-party verification and specialist support services. Acting as independent assurers, using their industry-leading recommended practices, they will ensure that any new solutions developed will provide real benefits in their application.Other network partners will bring oversight and stakeholder governance to the project by contributing to regular steering discussions and stage gates, reviewing deliverables, and providing feedback on proposed solutions. Solutions could be trialled on other network partners sites, and additional test data could also be provided. Having all four UK gas distribution networks in the project will also ensure that solutions are rolled-out as quickly as possible to benefit UK gas consumers.Solutions will be primarily used by two sets of users: Network and Maintenance teams who have responsibility for managing pressure and carrying out maintenance, will use the solutions to adjust governor pressures remotely and automatically to minimise leakage and optimise biomethane feed-in; they will also use solutions to diagnose, and ultimately resolve, network faults; and network planning teams will use the solutions to track KPIs such as leakage reduction or biomethane injection, and take strategic network decisions based on the analysis provided by the solutions." | |
Data | No related datasets |
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Projects | No related projects |
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Publications | No related publications |
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Added to Database | 12/10/23 |