Experimental characterization of complex atmospheric flows: A wind turbine wake case study

Area of Science:

• Atmospheric Science
• Renewable Energy Engineering
• Fluid Dynamics

Background:

• Understanding atmospheric flow around surface obstacles is vital for meteorology, forestry, urban planning, and wind energy.
• Current knowledge relies heavily on wind tunnel experiments and computational fluid dynamics (CFD) models.
• Limited field observations exist for the complex interactions within a wind turbine's wake.

Purpose of the Study:

• To present a novel remote sensing methodology for detailed atmospheric flow measurements around a utility-scale wind turbine.
• To provide spatially distributed data on the wind turbine's wake characteristics.
• To investigate momentum fluxes influencing wake-atmosphere interactions for improved wind energy optimization.

Main Methods:

• Utilized three synchronized wind lidars to scan a volume of the atmosphere.
• Conducted a case study focusing on a utility-scale wind turbine.
• Employed remote sensing techniques for atmospheric field measurements.

Main Results:

• Successfully mapped the mean wake flow, including velocity deficit distribution and spatial gradients.
• Observed momentum fluxes governing the interaction between the turbine wake and surrounding airflow.
• Demonstrated the capability of lidar technology for detailed atmospheric flow analysis.

Conclusions:

• The presented remote sensing approach offers unprecedented atmospheric flow observations.
• This methodology represents a paradigm shift for atmospheric field studies.
• Findings are essential for optimizing wind energy production and advancing boundary-layer meteorology.