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Can HPC unlock the future of wind power?

Speed read
  • Wind farms are a promising source of renewable energy
  • Scientists use computational fluid dynamics (CFD) to improve airflows
  • Cheyenne supercomputer quickly handles massive amounts of CFD data

Wind turbines are quickly becoming a top choice among scientists interested in renewable energy. Their effectiveness in providing clean energy is already proven. In 2016, the US Energy Information Administration (EIA) found that wind energy accounted for more of the country’s generating capacity than any other renewable resource.

Predicting performance. Researchers used supercomputers to simulate and visualize airflow around a wind turbine in the interest of increasing efficiency of energy production. Courtesy NCAR VisLab.

That said, no technology is perfect. Researchers at the University of Wyoming (UW) and Intelligent Light are working hard to improve the efficiency of wind energy. One aspect they’re currently investigating is the use of computational fluid dynamics (CFD) to simulate, predict, and improve the performance of wind farms.

CFD uses supercomputers to model the behavior of fluids such as air or water over moving surfaces. In this instance, UW professor of mechanical engineering Dimitri Mavriplis and Earl Duque at Intelligent Light turned to CFD to study how wind currents transform after coming into contact with a moving turbine’s blades in the context of a complete wind farm.

<strong>Strategic formation. </strong>Cyclists riding in an echelon formation take advantage of air disruption. Riding in the middle of the formation is easier than at the head.To illustrate the problem, Duque asks us to think about cyclists racing in an echelon, forming a diagonal line against the wind.

The rider in front blocks the wind, smoothing the way for those behind. This smoothness translates to lower wind resistance, which means less energy needed to maintain pace.   

While that’s great for athletes, it’s not so great for wind turbines. Since the entire point of a wind farm is to convert wind into energy, it’s a problem when the turbine in front disrupts the current flowing towards the ones behind it.

“The big issue is that these systems are too large to model in a wind tunnel, and the wind itself is difficult to predict,” Duque said. “So, CFD has been used for the last twenty-seven years to predict wind turbine performance.”

Out of thin air

Using the Cheyenne supercomputer at the National Center for Atmospheric Research (NCAR)-Wyoming Supercomputer Alliance, Duque and UW researchers Mavriplis, Michael Brazell and Andrew Kirby were able to model wind farms in unique ways.

The team used the Cheyenne supercomputer to create 3-D simulations of how terrain can affect wind drafts and to calculate isosurfaces.

An isosurface maps all points of constant value, such as velocity, within a certain area. Visualizing the isosurface of a wind turbine allows researchers to understand how turbines displace air, produce wakes and affect the performance of other turbines in the downstream area.

<strong>When wind hits</strong> a turbine's blades, it disrupts the flow of air to the other turbines behind it. Courtesy Eskinder Debebe/United Nations , <a href='https://creativecommons.org/licenses/by-nc-nd/2.0/'>(CC BY-NC-ND 2.0)</a>Mavriplis, et al. recently used this technology to complete a study of the Liligrund Wind Farm in Sweden. The domain size of this simulation was 10kmx10km with 1.1 billion degrees of freedom (DOFS) off body and 340 million DOFS for the near body.

With so much data to contend with, Cheyenne’s processing power was absolutely necessary. The 5.34 petaflop SGI ICE XA Cluster machine boasts 145,152 Intel Xeon processor cores in 4,032 dual-socket nodes (36 cores/node) and 313 TB of total memory.

But what really makes their research unique is the use of in-situ processing. Unlike traditional visualizations produced from stored data, in-situ processing means that visualizations and analysis can be created as a simulation takes place, without writing to disk.

In-situ processing eliminates file transfer bottlenecks, allows increased fidelity, and faster turnaround. 

"In-situ has helped reduce the amount of 3D data that we need to store,” Brazell says. “Just the restart files take 10 TB on a 12-hour run. Automation has gone way up; we have scripts that go straight from simulation to animation. Also, in-situ has helped with debugging—I don’t need to pull down 3D data, and I can just use slices, save those to a FieldView XDB file, and then view that on my local machine."

Wind energy’s two cents

The ultimate goal of this research is to increase the efficiency of wind farms and decrease the expense. In 2017, the levelized cost of energy from wind turbines cost around 5 cents per kilowatt-hour. That’s cheaper than natural gas at 5.4 cents per kilowatt-hour. But the research team believes that wind energy could become an even better bargain, eventually reaching prices as low as 2 cents per kilowatt-hour.

Of course, challenges remain for projects like this. To make wind energy a consistently cheap and reliable resource, Duque says that we have to “convince the regulators or Congress to say ‘These are the industries that are important to us.’”    

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