Ten British AI breakthroughs set to cut bills and heat homes more efficiently
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Millions of families could see warmer homes and lower energy bills,
as ministers back ten new AI innovations which will help make the
UK a clean energy superpower through the government's Plan for
Change. The ten finalists for the second round of the Manchester
Prize include revolutionary technologies that could transform how
Britain tackles climate change, while cutting costs for working
families. Among them is a system using AI to design
bespoke panels,...Request free trial
Millions of families could see warmer homes and lower energy bills, as ministers back ten new AI innovations which will help make the UK a clean energy superpower through the government's Plan for Change. The ten finalists for the second round of the Manchester Prize include revolutionary technologies that could transform how Britain tackles climate change, while cutting costs for working families. Among them is a system using AI to design bespoke panels, turning bricks into radiators to warm homes from the outside in, keeping a comfortable inside temperature all year round and simplifying the installation of heat pumps in older homes while reducing costs. Another team uses AI-enabled drones to map heat loss across entire neighbourhoods, helping councils identify exactly which homes need urgent insulation upgrades – which could save households hundreds on their annual energy bill.
The Manchester Prize, funded by the Department of Science,
Innovation and Technology and delivered by Challenge Works (part
of the Nesta group), is rewarding UK-led AI breakthroughs that support
the public good, including growing the economy, improving public
services and helping to create a just transition to Net Zero for
everyone. AI is opening up transformative new ways to tackle climate change and support the UK's ambition to become a clean energy superpower. That includes using the technology to keep our homes warm, while also supporting projects which will use AI to slash carbon emissions in our cement and steel industries - sectors which account for 16% of global emissions. This is how we deliver our Plan for Change - harnessing innovation to solve major challenges, cut energy bills, and improve lives across Britain. Energy Secretary Ed Miliband said: Clean power is the economic opportunity of the 21st century and these projects will help households and businesses take advantage of lower bills, in a smarter and faster way than ever before. From specially designed radiator walls to a smart power grid that flicks on and off as we need, AI has the potential to help every home in Britain to feel the benefits of warmer homes and homegrown clean energy. Julia King, Baroness Brown of Cambridge, chair of the Manchester Prize judging panel said: We are at a critical juncture in the journey to net zero, the next decade is make or break if the world is to keep global temperatures from exceeding 1.5C by 2050. Global emissions need to halve by 2030 compared to 1990 levels if we are to stay on track, while electricity production will need to double by 2050 to meet the demands of an electrified economy – clean energy innovation is essential. The rapid advancement of AI means we have tools like never before to achieve the goal of decarbonising the economy while supporting individuals, communities and businesses to thrive.
Other finalists include AI technologies to help the
logistics industry cut its emissions, and AI being used to ensure the
energy grid remains balanced at all times – as more and more of
our energy supplies comes from wind and solar. These shortlisted finalists will now follow in the footsteps of Polaron – the inaugural winners of the Manchester Prize which speeds up the development of advanced materials used in all walks of life – from wind turbines to electric batteries. The winning innovation will be announced early next year, taking home the grand prize of £1 million to bring their cutting-edge ideas to life. It builds on the AI Opportunities Action Plan, the UK government's blueprint to accelerate the use of AI across the economy. By harnessing cutting-edge solutions like these, AI is driving breakthroughs in industry, transforming public services, and improving the lives of citizens across the country. Notes to EditorsAbout the first Manchester Prize
The Manchester Prize is a
multi-million-pound challenge prize from the UK's Department for
Science, Innovation and Technology to reward UK-led breakthroughs
in artificial intelligence for public good. It is rewarding
innovations that will help to transform the lives of the people
across the UK and continue to secure the UK's place as a global
leader in cutting edge innovation. About Challenge Works Challenge Works is a global leader in designing and delivering high-impact challenge prizes that incentivise cutting-edge innovation for social good. It is part of UK innovation foundation agency Nesta. For more than a decade, it has run more than 97 prizes, distributed more than £210 million in funding and engaged with 16,000 innovators. Manchester Prize (year 2) finalistsAgent Net Zero Agent Net Zero by University of Sheffield and AMRC. Agent Net Zero is an innovative AI system that helps industrial companies become more sustainable by analysing their environmental impact in real-time. The system continuously monitors energy usage and emissions by connecting to various data sources across operations. Using advanced AI techniques, Agent Net Zero identifies environmental hotspots and automatically suggests practical improvements. This gives businesses clear, actionable insights to reduce their carbon footprint while maintaining productivity and competitiveness, essentially providing a “sustainability assistant” that works 24/7 to help companies achieve their net-zero goals. BiofuelAi BiofuelAi by University of Surrey. BiofuelAi brings cutting-edge AI and machine learning to the biofuel industry, optimising complex, variable processes in real time. Traditional biogas production often relies on operator intuition due to unpredictable biological systems because biofuels are made from multiple material inputs. BiofuelAi solves this with advanced predictive models that create a digital twin of each site, enabling whole-system optimisation – from daily feedstock recipes to long-term acquisition strategies. Developed by AI and sustainability experts, the platform boosts efficiency, profitability, and environmental impact, offering a scalable solution for cleaner, data-driven energy production worldwide. Carbon Re Carbon Re by Carbon Re. Cement forms the foundation of our modern world but it has a sustainability problem - it is responsible for around 8% of global CO₂ emissions. Carbon Re is tackling this challenge by building AI process control software to cut emissions in cement production. Acting like self-driving for industrial plants, Carbon Re optimises industrial processes in real-time, helping manufacturers cut both costs and carbon while transitioning to low-carbon operations. A joint spin out of University College London and the University of Cambridge, Carbon Re was founded to deliver immediate climate impact for heavy industry. Cavolo Cavolo by Kale AI. Cavolo uses advanced AI to make city deliveries more efficient and eco-friendly. The system helps businesses switch from traditional delivery vans to Light Electric Vehicles (LEVs), which are more efficient in busy cities. By using AI, Cavolo optimises delivery routes in real-time, reducing traffic, energy use, and emissions. The technology helps make urban logistics faster and greener, allowing businesses to deliver goods quickly while saving time and reducing their environmental impact. Deep.Optimiser-PhyX Deep.Optimiser-PhyX by Deep.Meta. Deep.Meta is tackling carbon emissions in the steel industry with an AI-powered Digital Twin - a smart digital replica of the production process that combines physics and machine learning to optimise furnace operations. By using real-time sensor data and material science, Deep.Meta more accurately predicts steel slab temperatures and improves scheduling, boosting energy efficiency and significantly cutting emissions. Unlike black-box AI, which can discourage adoption, Deep.Meta's explainable, physics-based models offer clear reasoning, building trust with users. Founded by experts in metallurgy and machine learning, Deep.Meta is already partnering with global steelmakers and aims to scale through broader industry collaboration. DRIVE DRIVE (Deep Re-enforcement learning for Intelligent Vehicle and Energy optimisation) by Flexible Power Systems. Flexible Power Systems (FPS) helps big fleets like vans, trucks, and buses switch to electric by managing vehicles, chargers, and schedules with smart software. FPS uses advanced AIcalled Deep Reinforcement Learning to solve complex, fast-changing problems – like where and when to charge – more quickly and efficiently. After training in a virtual world, the AI can make smart decisions in real time. First used in EV fleets, this technology could also help with bigger energy challenges in the future. EnergyWall EnergyWall by Underheat, in partnership with University of Salford. EnergyWall upgrades a building's walls, gently warming or cooling homes from the outside, turning bricks into radiators that maintain a comfortable internal temperature all year round. Using AI to analyse a building and off-site manufacturing, it designs and installs pipe systems into insulation panels for the walls of a building, making retrofitting buildings with heat pumps faster, cheaper, and less disruptive. This approach is ideal for social housing, helping reduce carbon emissions, cut energy bills, and tackle condensation that causes mould. It's a smarter, scalable way to decarbonise heating and fight fuel poverty across the UK. Green Loops Green Loops by University of Wolverhampton, in partnership with ABCircular GmbH Berlin. Green Loops tackles the challenge of recycling end-of-life photovoltaic (PV) cells by creating high-efficiency solar panels from recycled materials. It uses machine learning to analyse the optical properties of materials and structures of solar cells. Using highly conductive artificially engineered MXene-based metamaterials, Green Loops optimises the design of solar cells to enhance energy performance while reducing manufacturing costs. With the growing e-waste problem from old solar panels, the technology helps reduce waste, supports a circular economy, and makes solar energy more sustainable and accessible. Grid Stability Grid Stability by University of Manchester. For electricity grids to function, there must be balance between the electricity going into the grid and the electricity leaving it. Grid Stability Monitor uses AI and machine learning to quickly analyse power grid stability as more low-carbon technologies like wind, solar, EVs and heat pumps connect. It replaces slow, complex simulations with rapid, AI-driven assessments, enabling real-time monitoring, faster decision-making, and more confident planning. This helps grid operators maintain reliability while scaling up clean energy solutions and cutting emissions. Rapid Thermal Performance Assessment algorithms (RaThPAs) Rapid Thermal Performance Assessment algorithms (RaThPAs) by Kestrix. Kestrix uses AI and thermal drones to map heat loss across entire neighbourhoods, acting as fast, 3D energy surveys from the sky. This helps stakeholders like utilities, councils and housing providers plan energy upgrades with fewer costly, time-consuming site visits. Like a “Google Maps of heat loss,” the system shows where buildings are leaking heat and recommends fixes. With a team of experts in computer vision and physics, Kestrix aims to speed up home retrofits, in turn cutting emissions, saving households money, and making homes warmer and healthier at scale. |