📝 SummarXiv

Abstract

The atmospheric boundary layer undergoes significant changes throughout a diurnal cycle, affecting wind turbine performance and wakes in wind farms. Wind farm Large Eddy Simulations (LES) under such conditions provide rich datasets to study the underlying dynamics and identify important trends. Here, we describe a comprehensive open dataset generated using LES of an 8-turbine wind farm consisting of four rows of two turbines. To avoid specifying either prescribed surface temperature or heat flux, a local 1D soil heat conduction model is used with time-periodic solar surface heating, coupled to LES. After several days of low-resolution LES, an approximately time periodic behavior is achieved, after which high-resolution LES is continued during a 24-hour period. Analysis of the LES data reveals that wind turbine wakes have a significant impact on the temperature field and spatial surface heat flux patterns and exhibiting increased surface temperature behind the wind farm at night under the specific conditions of the simulation (dry unvegetated soil, clear sky). We observe that for a few morning hours the first row of wind turbines generates less power compared to the last row. Detailed analyses of the data using innovative web-services facilitated data access tools reveal that during the morning transition, the presence of a low-level jet and the wind farm blockage effect combine to cause cooling and a reduction in wind speed at hub height upstream of the wind farm. In addition, larger turbulence levels exist downstream in the wind farm, explaining the larger power production of downstream turbines.