Rainfall Dynamics in Wind Energy Scenarios

The presence of rain in wind farms involves several modeling challenges, as the momentum exchanges between turbulent wakes and the particle phase present subtle phenomena. For instance, rain droplets are typically large enough to exhibit inertia relative to the air carrier phase. Under these conditions, it has been found that the gravitational settling of particles in turbulent flows may be either enhanced or hindered compared to stagnant conditions. While this has significant implications for rainfall transport, ash pollutants, and pollen dispersion, very few studies have been conducted in field conditions. Moreover, the scaling laws and non-dimensional parameters governing this phenomenon have not yet been properly identified, and determining which configurations result in the enhancement or hindrance of settling velocity remains an open question.

We propose a hybrid experimental/numerical approach. Field data from a meteorological mast located at a wind farm in Pays d’Othe, 110 km South-East of Paris, France, were used to characterize the background turbulent flow through a set of sonic anemometers. Additionally, disdrometers were employed to characterize the settling velocity of raindrops, discriminating by particle size. Numerical simulations complement this data analysis. Specifically, 3D space and time vector fields that realistically reproduce the observed spatial and temporal variability of wind fields are generated using multifractal tools. Then, 3D trajectories of non-spherical particles are simulated and their settling velocity derived.

Our findings indicate that the presence of turbulence significantly hinders the settling velocity of raindrops in turbulent environments. Our study covers several distinct rainfall events, allowing us to analyze the influence of turbulent flow properties on this phenomenon.