Wind energy is notoriously mercurial, with patterns shifting drastically over the course of years, days, even minutes.

These changes make scheduling power much more difficult for utilities that rely on wind turbines to serve an increasing percentage of their power demands. Because wind power in some places is now as cheap as or cheaper than coal-fired power, future profits and challenges for the industry will be written on the wind and how well they can use it.

So scientists are stepping in with new measurements and models that may help them manage their power more effectively.

"Wind energy often has ramp events where energy increases or decreases by a large amount or in a short time. If there is an overload, there is excess energy on the grid," explained Chandrika Kamath, a researcher at the Lawrence Livermore National Laboratory.

The extra electricity, which can increase by as much as a gigawatt -- or the output of a large nuclear power plant -- in under an hour, must be quickly sold to other utilities or in many cases it is wasted. "If the ramp is a downward ramp, that is, the energy goes down, then you have to find that extra energy to keep the load balanced," she added. In the electricity industry, an "unbalanced load" is not just untidy, it can mean blackouts and brownouts: bad news for local economies.

Managing electric loads is already a challenge for utilities, which have to respond to electricity demand as lights, televisions and computers are turned on and off throughout the day. As more wind energy is added to the grid, power companies have to match increasingly variable electricity supplies to intermittent demand. Because of this, wind energy providers are looking for more effective and reliable ways to deliver power, from planning where to build to scheduling energy output.

With better wind forecasts, utilities can buy or sell extra power earlier at favorable rates. This also means that other generators, such as those powered by fossil fuels, can scale their power output in advance rather than rapidly ramping up or slowing down to compensate for wind, increasing their efficiency and improving the grid's reliability.

Increasing value of prediction
One way to overcome energy output challenges is to anticipate peaks and valleys in wind electricity production. That is what Kamath is doing with WindSENSE, a project aimed at helping wind turbine operators forecast energy surges.

"Typically, in a control room, they schedule the wind energy based on forecasts," she said. "We wanted to see if we can try to improve the forecasts. ... Right now, predicting ramp events is extremely hard."

Kamath looked at historical wind data from the Tehachapi Pass in Southern California and the Columbia Basin region on the Oregon-Washington border. Combing through the numbers, she pieced together the variables associated with ramp events, like the time of day, the season and ambient weather.

"What I'm interested in is seeing if we can use that weather data. Ideally, the better the data quality we have, the better the predictions would be," Kamath said.

She then created a computer model of wind patterns and compared the simulations to the data to find out what information she still needed. "The second half [of the WindSENSE project] was to essentially develop techniques to identify where we need additional sensors to improve the forecasts," said Kamath.

With these results, the simulations can be improved further and give utilities the tools to better manage energy while reducing costs and improving reliability for consumers.

How terrain shapes the wind
But for wind turbines, it's not just the air but the ground that affects their output, a fact that turbine designers have largely neglected, according to Hui Hu, an aerospace engineering professor at Iowa State University. Engineers often design turbines and arrange them as though the terrain was flat.

For offshore turbines, such as those found off coasts in Europe, this approximation is valid. However, Hu explained, even seemingly flat land, like in Iowa, can make an appreciable impact on wind energy production.

Hu and his team are using wind tunnels, miniature generators and scale models of wind turbines to see how rolling hills, ravines and ridges can affect energy output. "Recently, we found that if you have a hill [near a wind farm], the distance between the wind turbines can be reduced significantly. Energy can be recovered faster," said Hu. "We can quantify how that decay will interact with the next row of wind turbines."

The researchers observed flow fields and vortices created by spinning blades and published some of their findings online in the Journal of Visualization last November. In addition, Hu is investigating how turbine operators can compensate for weather effects like icing on turbine blades.

With this information, energy developers can plan wind farms better, but also extract more energy from their existing turbines while minimizing wear and tear on their hardware.

What's going on at the hub?
However, over a turbine's operating life, the climate becomes a larger factor. "If we take the intermediate term, a five-year basis, there have been some studies that show there have been some periods where wind speeds are significantly above or below the long-term average," explained Eugene Takle, a professor of agricultural meteorology at Iowa State.

"That's the scale that's relevant for people that are investing in wind power," he said. Long-term predictions can also help utilities plan new generators to meet future demand.

According to Takle, predicting wind speeds that are relevant for wind turbines is still an emerging process. "One of the challenges we have is that most of the models we use don't have a long history of application and validation for forecasting wind at the hub height of these turbines. We've used these forecasts for years to forecast winds near the surface of the Earth," he said.

The reason that's important, particularly in places in the central United States, he explains, is that winds at the height of the hub of a wind turbine, roughly 260 feet, are different from the winds at the surface.

Like Kamath, Takle did acknowledge that the simulations need to be validated with field studies, measuring how accurate their predictions are in the real world. He said that using tools like weather balloons, airplane-mounted instruments and laser radar, scientists can test their simulations.

Eventually, the scientists hope to reduce the uncertainty in wind forecasting, lowering its overall costs and increasing its reliability.

Reprinted from Climatewire with permission from Environment & Energy Publishing, LLC., 202-628-6500