LONDON, Sept. 11 (Xinhua) -- With renewables generating more than half of its electricity, Britain is looking to artificial intelligence (AI) to make its expanding clean energy system more efficient and affordable.
Renewables produced a record 153 terawatt-hours of electricity in 2025, accounting for 52.1 percent of Britain's electricity generation, according to statistics from Britain's Department for Energy Security and Net Zero. Output increased by 5.9 percent from 2024, with offshore wind, solar and bioenergy reaching record levels.
Progress across the wider energy system remains uneven. Government statistics put renewables' share of gross final energy consumption, which extends beyond electricity, at 16.8 percent in 2025.
However, energy affordability remains a pressing concern. Simon Cran-McGreehin, head of analysis at the Energy and Climate Intelligence Unit (ECIU), argued in a statement that moving away from oil and gas would reduce exposure to volatile fossil fuel markets. He advocated continued adoption of electric vehicles and heat pumps powered by British wind and solar generation.
Meanwhile, growing reliance on weather-dependent electricity generation and flexible electricity demand is making grid management more complex, according to an independent review, The Grid We Need Now, released in September.
To boost the development of a clean homegrown power system, the Department for Energy Security and Net Zero has recently opened a call for evidence on how AI can transform the energy system to inform policy development.
"AI could enable renewable power sources, electric vehicles, heat pumps, batteries and smart appliances to work together more effectively. It could help us identify faults before they happen, forecast demand more accurately, make better investment decisions and accelerate the development of new energy technologies," said Martin McCluskey, Britain's Minister for Local Energy and Jobs.
In a document titled Vision for an AI-enabled Clean Energy System, the government says AI could help manage batteries, electric vehicles, heat pumps and smart appliances to shift electricity use to times when power is cheaper and cleaner. Better forecasting and planning could reduce waste and avoid building excess capacity as a precaution.
Some applications are already producing results. The independent review reports that British startup Open Climate Fix combined weather forecasts, satellite imagery and live solar-generation readings to halve solar forecasting errors for the National Energy System Operator (NESO), saving 30 million pounds (40.6 million U.S. dollars) annually in reserve costs.
Other work focuses on coordinating decisions across the grid. In an August 2025 explanation of its Volta program, NESO said its Grand Optimiser project aimed to improve how the grid directs power plants and batteries to supply electricity. The project envisages multiple digital models working together across different operational timescales. NESO said this could streamline control-room processes and potentially reduce electricity system operating costs.
Looking further ahead, the independent review, led by the British government's AI Champion for Clean Energy Lucy Yu, recommends using ongoing assessments of the likelihood and impact of potential disruptions to guide grid operations by 2035 and grid planning by 2036. This could reduce the cost of preparing for fixed worst-case scenarios while maintaining or improving reliability.
However, the review says existing approaches to running the grid and difficulties putting new technologies into widespread use are holding back progress. It recommends setting up a national center to help test AI tools and introduce them across the electricity network.
"While much of it can and must begin immediately, we should prepare for a decade of delivery," Yu wrote in the review's foreword.
The British government also identifies fragmented data, incompatible standards, weak investment incentives and shortages of digital skills as barriers. Existing systems can be difficult to integrate, while unclear regulatory expectations may discourage adoption.
"Just as was true for other technologies in the past, the opportunity from AI comes not just from what it can do in the system as it is, but from its potential to change the system itself," said Yu. ■
