- Title: AI-designed 'local' wind turbine optimises energy production
- Date: 10th December 2024
- Summary: LONDON, ENGLAND, UK (DECEMBER 04, 2024) (Reuters) (SOUNDBITE) (English) DOCTOR KIT WINDOWS-YULE, UNIVERSITY OF BIRMINGHAM, SAYING: "The design of our turbine that's optimised for the specific wind speeds of Edinburgh is as different to the Birmingham Blade as a drill bit is from a feather. The designs are radically different and the reason for that is the Birmingham Blade
- Embargoed: 24th December 2024 09:59
- Keywords: AI-designed wind turbine Birmingham Blade College of Engineering and Physical Sciences Dr Christopher (Kit) Windows-Yule Edinburgh Edge EvoPhase University of Birmingham geographically optimised wind turbine
- Location: BIRMINGHAM & LONDON, ENGLAND, UK / NAUEN, GERMANY / COMPUTER GENERATED IMAGES
- City: BIRMINGHAM & LONDON, ENGLAND, UK / NAUEN, GERMANY / COMPUTER GENERATED IMAGES
- Country: UK
- Topics: Climate Adaptation and Solution,Climate Change,Environment,Europe,General News
- Reuters ID: LVA00E587709122024RP1
- Aspect Ratio: 16:9
- Story Text: A unique wind turbine, entirely designed by AI for a specific location, is up to seven times more efficient than a traditional turbine in the wind speeds and urban environment it's intended for, according to its developers at the University of Birmingham.
"The Birmingham Blade is the world's first A.I. designed, geographically optimised, wind turbine," Dr Kit Windows-Yule, Director of Innovation at the University's College of Engineering and Physical Science, told Reuters.
"It's tailored to be optimally efficient for the specific city it's going to be operating in," he said.
The turbine is the work of a University incubator venture called EvoPhase, specialising in AI prototyping that saves years on normal development timelines. Simulations showed the turbine to be up to seven times more efficient than existing designs in low wind speeds.
"Every minute detail of the geometry of this wind turbine, every twist, every edge, every bend, every angle has been tuned and tweaked by our EvoPhase AI to be as efficient as possible for the specific wind speeds and specific topography of Birmingham," he said.
The AI was only told that the blades should point upwards. From that point onwards, conventional research and development was abandoned with the software taking just over a week to hone its design from thousands of variations.
"We generated, tested and refined more than 2000 different designs in eight days. And can you imagine the size of the workforce you would need to do that in real life?" Windows-Yule said.
The final design features S-shaped, curved blades which spin around a central point, creating a vortex in the middle and allowing the turbine to operate in winds 3.6 metres per second, substantially lower than the 10 m/s rating for most turbines with a wind mill configuration.
The team is now working on another design for the very different conditions in Edinburgh.
They also want to apply AI driven design to systems and machines beyond wind energy, including the optimisation of equipment for mixing, blending, and storing granular materials in the food, pharmaceutical, and chemical manufacturing sectors.
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