Wind energy is a cornerstone of renewable transition. But while scaling wind turbines up has proven effective for large-scale applications, scaling them down for urban environments remains a significant challenge. Wind speeds in cities, often as low as 3–4 meters per second, are about 2–3 times lower than the efficiency sweet spot for conventional turbines. To unlock wind energy’s potential in urban areas, new designs must cater specifically to these lower speeds and turbulent conditions.
Enter the AI-designed turbine.
The system takes into consideration the wind conditions of the city where it is meant to be deployed — in this case, Birmingham, UK — and optimizes the design to account for these conditions.
AI powered design
“We needed a turbine that could capture Birmingham’s relatively low wind speeds while managing turbulence caused by surrounding buildings” explained Leonard Nicusan, Chief Technology Officer of EvoPhase. “The design also had to be compact and lightweight to suit rooftop installations.”
The new wind turbine, which boasts an unorthodox but efficient design, was developed by a research group led by Dr. Kit Williams-Yul at the University of Birmingham. It also features a collaboration with AI design specialists EvoPhase and precision metal fabricators Kwik Fab Ltd. The design involves curved blades spinning around a central point.
The AI-driven approach proved transformative. It enabled researchers to generate, test, and refine over 2,000 designs in just weeks—an achievement that would have taken way more time and money using traditional methods. The result is a turbine that is up to seven times more efficient than existing designs in Birmingham’s urban environment, according to initial tests.
“Using AI was essential for breaking free from the long-standing biases that have influenced turbine designs for the past century” added Mr Nicusan. “AI allowed us to explore design possibilities beyond the scope of traditional human experimentation. We were able to generate, test, and refine over 2,000 wind turbine designs in just a few weeks, significantly accelerating our development process and achieving what would have taken years and millions of pounds through conventional methods. Our evolutionary simulations have confirmed the Birmingham Blade is up to seven times more efficient than existing designs in Birmingham’s wind speeds and urban environment. The final design is not just a prototype — it is a predictive solution that is ready for real-world use.”
Blueprint for the future
The AI-designed wind turbine will now be left in operation in Birmingham to assess real-life performance. Researchers are confident that they can make a wind turbine for every city with ease. The team is already working on a wind turbine tailor-made for the city of Edinburgh in Scotland, which has very different wind conditions to Birmingham.
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“We can take a complex design, and manufacture and ship a prototype for testing within weeks” said Paul Jarvis from Kwik Fab. Mr Jarvis is confident that there is sufficient talent and space in Birmingham to deliver quick turnaround from design to prototyping for wind turbines that are geographically tailored to specific local conditions around the rest of the world. “We’d like to work with organizations that want to make the most of wind power, a source of sustainable energy that is free, and present in every country.”
By now, we all know the immense potential that wind energy has. Yet finding custom, hyper-localized solutions has proven remarkably challenging. It works great in large, open fields, but with this AI-driven, customized approach, it could also transform localized renewable energy generation. With their rapid design-to-prototype cycle, these innovations promise to accelerate the transition to a greener, smarter future — one city at a time.
