A team of researchers from the Massachusetts Institute of Technology, Princeton University, Queen’s University, and Penn State University believes it has found a way around that problem. In a new open access paper published in PNAS Nexus, the group describes a series of experiments conducted in a pressurized wind tunnel, a facility that allows scaled-down turbines to reproduce the flow physics of full-size machines operating in the open atmosphere. By raising the air pressure inside the tunnel, the researchers dramatically increased the density of the air, and with it the inertia of the flow around their model turbine, closing a gap between laboratory experiments and field conditions that has hampered wind energy research for decades.

The logic behind the approach rests on a principle known as dynamic similarity. A small turbine spinning in ordinary air does not behave like a giant machine standing in a windy plain, because the balance of inertial and aerodynamic forces is different at different scales. But when the air in the test chamber is pressurized, it becomes far denser, and the scaled model suddenly experiences forces that mirror those acting on a much larger turbine. In the new study, the team used a turbine measuring just 15 centimeters in diameter, but at pressures of up to 240 atmospheres the air density increased by a factor of 100 to 220 times. According to lead author John Kurelek, an assistant professor at Queen’s University, that means the experiments effectively tested a turbine that is, all else being equal, 15 to 20 meters in diameter, with the capability of reaching the equivalent of 35 meters.

The motivation for this experimental paradigm comes in part from the frustrations of field research. Michael Howland, MIT’s Jeffrey Cheah Career Development Professor and a senior figure in the project, has spent years developing models to simulate wind farm performance and to increase power output. In 2022, he demonstrated that accounting for the wake of individual turbines when controlling an entire wind farm could significantly boost electricity production. But that work demanded a lengthy and costly field campaign in which turbines at a real wind farm were intentionally misaligned with the wind for months, temporarily lowering the farm’s output, in order to understand how misalignment affects performance.

Wind energy, Howland explains, sits at a unique intersection of environmental flow, mechanics, aerodynamics, and meteorology, and that makes controlled experimentation extraordinarily difficult. Researchers want to isolate the effect of a single change, but wind farms operate in chaotic, turbulent environments where the weather is constantly evolving and turbines must react to conditions beyond anyone’s control. This complexity has left engineers uncertain about how precisely changes in the alignment between wind and turbine, or variations in the turbine’s tip speed relative to the wind, alter the power a machine produces. Many predictive models in use today are built on the assumption that turbines always face perfectly perpendicular to the wind, an assumption that is almost never true in the real world, even for modern turbines that continuously adjust their orientation in response to rapid directional shifts in the wind.

That uncertainty is exactly what the pressurized experiments were designed to resolve. Marcus Hultmark, a professor at Princeton University whose laboratory pioneered the study of scaled turbines in pressurized wind tunnels, notes that researchers have long debated which models best describe the output of wind farms, but without reliable experimental data to compare against, the field has struggled to advance. The new paper, he says, attempts to do both: settle questions about turbine performance and provide the missing experimental benchmark. Over several weeks of testing, the team ran the model turbine through a systematic series of operating conditions, varying its alignment with the wind and its control strategy to isolate how each factor influences power production.

The results carry direct implications for the economics of wind energy. The researchers found that power output could be significantly increased by adjusting the turbine’s tip speed based on its misalignment angle with the wind, a control strategy that is rarely employed at wind farms today but that could deliver performance gains at minimal added cost. Kurelek describes this as the clearest output of the experiments: new power maximums become achievable when a turbine is misaligned with the wind, simply through changes to the tip speed. Combined with optimization of the turbine’s alignment relative to the wind and the blade pitch angles, which control the airfoil’s angle of attack, the researchers estimate that such improvements could yield tens of thousands of dollars per turbine every year in additional revenue.

The experiments also served a second, equally important purpose: validating a new predictive model. Howland and his colleagues developed what they call a unified wind turbine model, building on previous work that produced a more general aerodynamic theory for wind turbines. The model simulates turbine performance across operating conditions without relying on the empirical corrections that have historically been baked into wind power models. Before running the experiments, Kurelek sent the dimensions of the wind tunnel and turbine setup to Howland, who used them to calculate the expected aerodynamics, forces, and power production. The close agreement between prediction and measurement marks the first experimental validation of the unified momentum model’s predictions about how turbines should be controlled under misalignment to achieve maximum power production.

One of the most striking features of the validated model is its computational efficiency. According to Howland, the model is fast enough to run on ordinary laptop computers, which means engineers designing and operating wind turbines anywhere in the world can use it to test different turbine designs and wind farm control strategies without access to supercomputers. That accessibility could accelerate the adoption of the control strategies identified in the study, allowing existing wind farms to be retuned for higher output rather than waiting for new hardware to be installed. Because the approach improves and validates the models that feed directly into wind turbine control protocols, its immediate impact applies to the vast installed base of turbines already generating power today.

Beyond the immediate gains, the researchers see the pressurized wind tunnel as a way to fill a persistent void in wind energy research. Howland describes a massive gap between idealized theoretical and simulation models on one side and full-scale testing in extremely complicated field environments on the other, a gap that he says nothing else currently fills except these pressurized experiments. By enabling high-throughput, controlled experiments that achieve the right physics in a time-efficient and low-cost manner, the technique could allow researchers to investigate a wide range of previously unanswered questions about turbine aerodynamics, wake behavior, and farm-level control. The work, supported in part by the Natural Sciences and Engineering Research Council of Canada, the National Science Foundation, and the MIT-GE Vernova Alliance, suggests that the path to more wind power may run not only through bigger turbines and new installations, but through smarter operation of the machines already turning in the wind.

Subject of Research: Pressurized wind tunnel experiments validating wind turbine aerodynamic models and control strategies for increased wind farm power output

Article Title: Pressurized experiments could help wind farms generate more power

Article References: Pressurized experiments could help wind farms generate more power. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: wind energy, wind turbines, pressurized wind tunnel, dynamic similarity, aerodynamics, wake modeling, turbine control, tip speed ratio, blade pitch, PNAS Nexus, MIT, renewable energy