Published on August 19th, 2013 | by Tina Casey6
Shhhh! New Low Noise Wind Turbine Blades Designed By GE
August 19th, 2013 by Tina Casey
Forget about building a better mousetrap, if you could build a noise-free wind turbine the world will beat a path to your door. That’s not only on account of the annoyance factor, it’s because wind turbine noise can be a significant impediment to greater efficiency. GE has been tackling the problem head on in collaboration with Sandia National Laboratories, and the company has just announced a new design model for wind turbine blades that could result in a two percent increase in output.
That might sound like small potatoes, but consider that according to GE, about 240 gigawatts worth of new wind turbines are set to be installed over the next five years, so any small increase in efficiency is going to translate into a big difference worldwide.
Wind Turbine Noise
In terms of the annoyance factor, wind turbine noise can be highly subjective. In 1985, for example, the National Renewable Energy Laboratory undertook a study of noise complaints regarding the experimental DOE/NASA MOD-1 wind turbine in North Carolina.
Of more than 1,000 families living within three kilometers of the turbine, only about 12 reported noise complaints, but the investigation did reveal a probable design flaw leading to generation of a “thumping” phenomenon that could carry over distance.
While there is nothing subjective about measuring wind turbine power output, it is linked to wind turbine noise. Specifically, the aerodynamic noise created by the blades is the most significant source of noise from advanced wind turbines. With the right design approach, a quiet blade will be a more efficient blade, too.
Building A Quieter Wind Turbine Blade
GE Global Research is the arm of the company involved in the project, which at its current state of progress involves using sophisticated engineering models to predict blade noise. The aim is to get the greatest velocity at the tip of the blade without a consequent increase in noise.
As for where those engineering models are to be found, GE went to the Red Mesa supercomputer at Sandia, where they ran a simulation called the Large Eddy Simulation. Developed by Standford University, the simulation is designed to predict fluid dynamics and their effects, including noise from wind blades.
The simulation ran for three months, measuring the turbulent air flow past a section of wind blade. The result is a flow-field prediction model that can be used to assess new blade designs.
By itself, the model isn’t going to design a new blade from scratch, but GE predicts that it will be a useful tool for improving advanced turbine designs even further while increasing power output. GE figures on a two percent increase in annual energy yield per turbine, based on a reduction of 1 decibel in rotor noise.
We Built This Less Noisy, More Efficient Wind Turbine!
The Red Mesa supercomputer is a collaboration between Sandia and NREL, both of which come under the Department of Energy, and GE has been right up front about cheerleading for this valuable public resource.
Mark Jonkhof, who is Wind Energy Platform Leader at GE Global Research, explains:
“Having access to Sandia’s supercomputer was invaluable in our ability to conduct these experiments and make discoveries that will bolster wind power’s potential. Access and availability to HPC resources offers a critical advantage to companies trying to compete in a global environment.”
There’s plenty more where that came from, too. Red Mesa was designed specifically to rev up the R&D process for advanced alternative energy designs.
One of the supercomputer’s first projects was solving a cornstalk-to-energy problem in about six weeks, which would normally take about six months.
As for further improvements in wind turbine design, next up is an answer to the winged animal hazard conundrum. Though bird and bat deaths related to wind energy development may be low compared to other man-made environmental hazards, as the wind market expands this problem will need greater attention.
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