Stanford Study Shows Realigned Wind Turbines Can Boost Output Of Wind Farms
People who follow auto racing or sailing know about aerodynamics and wind turbulence. Race cars leave eddies of disturbed air in their wake, slowing down the cars behind. Sailboats have similar eddies of turbulent air streaming back from their sails, slowing down the boats following. Researchers at Stanford have taken a look at how the wake from wind turbines can interfere with the efficiency of other turbines in the area and discovered that turbulence can decrease the efficiency of turbines down wind by as much as 40% or more. Their research was published this month in the journal Proceedings of the National Academy of Sciences.
In an experiment at a wind farm in Alberta, Canada, the researchers repositioned the wind turbines so the turbulent air they created had less of an effect on other turbines in the area — a process they call wake steering. The research is preliminary but encouraging, especially at a time when variability of renewable energy resources makes the case for keeping peaker plants operational.
“To meet global targets for renewable energy generation, we need to find ways to generate a lot more energy from existing wind farms,” said Stanford professor John Dabiri, senior author of the paper. “The traditional focus has been on the performance of individual turbines in a wind farm, but we need to instead start thinking about the farm as a whole, and not just as the sum of its parts.”
Renewable Energy Magazine reports that turbine wakes can reduce the efficiency of downwind generators by more than 40%. Previously, researchers have used computer simulations to show that misaligning turbines from the prevailing winds could raise production of downstream turbines.
First, the Stanford group developed a faster way to calculate the optimal misalignment angles for turbines. Then they tested their calculations in collaboration with TransAlta Renewables, the operator of the Alberta wind farm. The overall power output of the farm increased by up to 47% in low wind speeds — depending on the angle of the turbines — and by 7 to 13% in average wind speeds. Wake steering also reduced the ebbs and flows of power that are normally a challenge with wind power.
“Through wake steering, the front turbine produced less power as we expected,” says PhD candidate Michael Howland, lead author on the study. “But we found that because of decreased wake effects, the downstream turbines generated significantly more power.”
The observed power improvement at low wind speeds was particularly important because turbines typically stop spinning below a minimum speed, cutting production entirely and forcing grid managers to rely on backup power. In addition, turbulence from wakes can make wind farm production erratic minute by minute, which makes matching supply and demand more challenging for system operators in the very short term. In the study, wake steering reduced the very short-term variability of power production by up to 72%.
To calculate the best angles of misalignment for this study, the researchers developed a new model based on historical data from the wind farm.“Designing wind farms is typically a very data and computationally intensive task,” professor Sanjiva Lele. “Instead, we established simplified mathematical representations that not only worked but also reduced the computational load by at least two orders of magnitude.”
This faster computation could help wind farm operators use wake steering widely. “Our model is essentially plug-and-play because it can use the site-specific data on wind farm performance,” Howland said. “Different farm locations will be able to use the model and continuously adjust their turbine angles based on wind conditions.”
The next step, said Dabiri, is to run field tests for an entire year. “If we can get to the point where we can deploy this strategy on a large-scale for long periods of time, we can potentially optimize aerodynamics, power production and even land-use for wind farms everywhere.”
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