As electricity networks face growing pressure for connections, the need for smarter, faster, and more flexible network solutions becomes essential. Dynamic Rating (DR) allows electricity network assets, particularly overhead lines, to operate closer to their real-time thermal capacity by accounting for environmental conditions. Dynamic, Data Driven Asset Rating (3DAR) will identify those circuits where DR could be deployed to release additional headroom, overlay future constraints with mapped additional capacity from DR to facilitate assessment at scale. 3DAR will allow DR to be scaled at distribution level, productising the solution to embed it within processes and accelerate network connections.

With increasing demand for both electrification and renewables connections, many areas of the distribution network are approaching their capacity and will need intervention. Traditionally, DNOs can reinforce the network or procure flexibility services to meet these peaks. These are costly solutions that can have long lead times. By leveraging dynamic asset ratings at scale for the first time at distribution level, this project enables the deployment of a data-driven solution that optimises capacity through real-time, localised weather data and asset modelling. 3DAR will enhance network investment planning, reducing costs and ensuring long-term resilience for faster, more efficient connections.

Energy efficiency retrofits rolled out by Local Authorities (LAs) and Social Housing Providers (SHPs), such as home insulation and storage heating, represent an opportunity to procure flexibility from disadvantaged households that are typically not able to participate in flexibility markets. Flex Direct aims to develop a new way to procure this type of flexibility by Distribution System Operators (DSOs). The project is developing novel commercial models and coordinated market approaches to enable LAs and SHPs to operate in direct contract with DSOs. This will incentivise use of energy efficiency in flexibility markets and facilitate participation of 'hard-to-reach' customers at scale.

Quantum computers will transform numerous industrial sectors, from the major aerodynamic simulations used to optimise jet engine design, through artificial intelligence, machine learning and the data economy, to drug discovery. Quantum computers are set to be as game-changing as the development of conventional computers in the last century, as they will be able to solve high-impact problems which would take the fastest supercomputer billions of years. A primary goal of UK's National Quantum Technology Programme is translating the UK's academic excellence in developing practical quantum computers into economic prosperity, by building a quantum computing industry sector including relevant supply chains. The biggest remaining challenges in realising universal quantum computation are in scaling up to fault-tolerant machines with millions of qubits. The quantum hardware developed in QCorrect will be capable of overcoming the limitations faced by competitors around the world propelling the UK to become a leader in commercial quantum computing. While competing platforms based on superconducting qubits are limited in the number of qubits they can realise because of the requirement to cool microchips to -273C, our platform is based on trapped-ions and does not require such cooling. Our platform is also suitable for implementation of efficient and scalable error-correction algorithms which improve the performance of the computer whilst reducing the hardware requirements. The combination of these factors offers the opportunity to develop systems featuring much larger qubit numbers. Full silicon microchip integration will allow the creation of self-sufficient electronic quantum computing modules to be deployed and made cloud-accessible for end-user investigation during the project. Hardware/software co-development is led by system integrator Universal Quantum and quantum software developer Riverlane, together with leading subsystem manufacturers for vacuum systems (Edwards) and microwave technologies (TMD Technologies, Diamond Microwave) incubating a quantum computing supply chain in the UK. The University of Sussex will perform use-case demonstrations and deliver performance enhancements aided by theoretical innovations from Imperial College London. In order to ensure a pathway to commercialisation, applied Computational Fluid Dynamics (CFD) experts at Rolls-Royce and STFC will work with Riverlane and UQ to develop a quantum approach to solving partial differential equations that underpin commercially-relevant simulations in the UK aerospace sector. Exploitation/dissemination partners Sia Partners will develop a roadmap to commercialisation of application-specific tools in CFD and Qureca will develop broader use-cases that depend on solving partial differential equations. The consortium will execute the first use-case demonstrations and streamline hardware/software development towards practical applications.