Experimental study of thermal effects on wind turbine flows at high Reynolds numbers

• Applicant: Dr. Yuna Hattori
• Subject Area: Fluid Mechanics
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 555568385

The complex, temperature dependent behaviour of turbulent airflow around wind turbines makes it difficult to predict realistic wind energy generation conditions. To meet our growing global energy demand it is important to acquire new information about these flows that can help us maximize the efficiency of wind energy production. The proposed research will conduct the first ever laboratory study of flows around wind turbines in different thermal gradients at very high Reynolds numbers. Wind turbines are always placed in the atmospheric boundary layer (ABL), where flows are heavily affected by thermal effects due to solar radiation. Although these real flows are rarely free of thermal effects, most experimental studies of wind turbines neglect them. There are technical difficulties to creating flows with thermal gradients around wind turbine models; however, the Variable Density Turbulence Tunnel (VDTT) in the Göttingen Turbulence Facility at the Max Plank Institute for Dynamics and Self-Organization in Germany has the equipment needed to overcome these challenges. Here, I propose three different research objectives using the VDTT to quantify thermal effects on boundary flows around wind turbines. The first objective will experimentally classify thermal effects in various states of the ABL. The second objective focuses on determining the effect of these states on the wake energy recovery of a single wind turbine. The final objective studies the collective effect of a prototype wind farm in an experimentally generated ABL, specifically how thermal gradients change the energy coupling that is known to alter the airflow around an entire warm farm. By combining these experimental studies with theoretical analyses, the final results will give generalised information for use in the performance prediction of wind farms.

• DFG Programme: WBP Position