| Project Detail |
Turbulence drives transport processes in the atmosphere and determines Earth’s weather and climate. Wind farm performance depends on atmospheric turbulence as it entrains energy into wind turbine arrays. As wind turbines and farms expand in size, they increasingly interact with an unexplored atmospheric region and large-scale weather phenomena in ways that are not fully understood. Typical wind farm simulations assume idealized cases and do not capture the influence of (i) dynamic changes in atmospheric conditions, (ii) the interaction between the atmosphere and ocean, and (iii) the influence of clouds. In reality, these effects are dynamic and influence atmospheric turbulent flow across a wind farm. Understanding these interactions is crucial to optimize wind farm design, control, and power production forecasts. Far beyond the local scale, wind farm physics impact large-scale atmospheric processes. Outstanding questions include how wind farms influence large-scale weather phenomena, atmospheric stability, moisture dispersion, and clouds. The influence of wind farms on heat and momentum exchange between the atmosphere and ocean is also not fully understood.
To bridge these knowledge gaps, I envision using 3D simulations to locally model the wind farm flow physics (microscale) in a weather model (mesoscale). This is a conceptually different approach from typical weather models that use a limited refinement of microscale processes throughout the domain. Using high-resolution simulations, I will go beyond idealized cases and explore dynamic interaction between atmosphere, ocean, clouds, and wind farms. The goal is to study wind farm interaction with realistic weather conditions and provide more accurate wind production forecasts. I will develop novel computational techniques to increase the domain size of high-resolution simulations. Addressing these fundamental modeling challenges is crucial to unlock the complex interaction between wind farms and the atmosphere. |
