Turbulence is a big nuisance for wind turbines, but this might change. PhD student Ashim Giyanani is trying to predict turbulence right in front of the blades.
They may make fast swooshing sounds, but in their response to changing wind forces, wind turbines are slow buggers. Only after having been knocked back by wind gusts will they change the angle of attack of the blades to diminish the rotor speed and wind exposure.
Giyanani, a wind turbine researcher and expert in turbulence of the Aerospace Engineering faculty, believes he found a way to help turbines anticipate wind gusts. His findings could one day increase the lifespan of turbines and allow for lighter and cheaper windmills.
“Windmills don’t see wind gusts coming,” said Giyanani, who presented his research last month at a conference in Delft organized by the Delft Energy Initiative. “The controllers that manage the generator speed cannot act on a sudden rise in wind speed. Because there is always a short lag in the response, windmills have to be designed in such a way that they can endure short periods of stronger wind forces.”
Scientists in Denmark and Germany are trying to image turbulence in front of windmills using lasers mounted on the nacelle. They use LiDAR, which is an acronym for Light Detection And Ranging.
“But they face a problem,” said Giyanani. “And it is that these lasers have a blind spot. They can image the air only between 40 metres and 185 metres upwind. This has to do with the interferometry of the outgoing light and the reflected light, which is used to calculate the distance. If the distance is very small, the light spectra are overlapping, and you can’t do any calculations.”
For his PhD research Giyanani is modelling the behaviour of turbulence during these last 40 metres, taking the measured turbulence upwind as input. It is a hell of a job. “Nobody understands turbulence. To simplify things, usually the so-called Taylor’s frozen turbulence hypothesis is invoked. It assumes that the turbulent structures move as frozen entities transported by the mean wind. But this is much too simplified.”
Giyanani uses autoregressive models instead. These can provide insights into processes that are too complicated to be explained by the present level of physics. Or at least, that is the idea.
So far, the results seem promising. Giyanani made time series with his model in which he extrapolated the turbulence spatially towards the wind turbine at distances from 185 metres upwind all the way up to the blind spot. The results fitted the model with 90 percent accuracy.
The researcher hopes that the findings can ultimately help construct more efficient, lighter and cheaper windmills. “Light weight constructions are especially important if we want to make bigger turbines and turbines at sea.”
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