Scientists have demonstrated the advantage of accurately linking the profile of wind turbine blades to geography—to specific operating conditions. Wind conditions are different everywhere, and they are very different in urban areas. But previously, taking into account all the factors to optimize the operation of a wind turbine was difficult and expensive. Today AI copes with this “on time”. This is what helped bring the project to life.
Turbine blades in the background. Image source: University of Birmingham
Scientists from the University of Birmingham have begun creating the most optimized blades for urban wind turbines. The development was called the Birmingham Blade. In just a few weeks, AI checked more than 2,000 turbine blade profiles, saving scientists years of work and millions of dollars.
The idea to use artificial intelligence for the project was also based on the desire to get away from the human perception of the problem – from the stereotypes that have developed in the industry. People have always sought compromises between various parameters when designing wind turbine blades. In this regard, AI received complete freedom and was able to look at the problem from all sides.
It should be noted that the AI was also special. It was created by scientists at the University of Birmingham. This is the EvoPhase platform, which simulates natural selection. This approach allows you to simultaneously optimize many different parameters, avoiding traditional trade-offs between certain performance factors. The blades themselves were manufactured by local company KwikFab, a specialist in precision metal structures. It also took little time to produce and deliver.
«We needed a turbine that could capture Birmingham’s relatively low wind speeds while managing turbulence caused by surrounding buildings,” explained Leonard Nicusan, technical director at EvoPhase. “The design also had to be compact and lightweight to be suitable for rooftop installation.”
Tests showed that the AI-designed blade design was seven times more effective in a given location than if a conventional blade had been used. Now Edinburgh is taking on Birmingham’s experience. For operating conditions in a new location, AI develops other blades, and it can create these for any terrain and any “geography”, which, ideally, can make wind energy much more accessible and inexpensive.