Researchers from Johns Hopkins University, led by Shuolin Xiao and Xiaowei Zhu, along with Ghanesh Narasimhan, Dennice F. Gayme, and Charles Meneveau, have conducted a comprehensive study on wind farm dynamics over a diurnal cycle. Their work, published in the Journal of Physics: Conference Series, provides valuable insights into how atmospheric changes throughout the day can impact wind turbine performance and wake effects within wind farms.
The team utilized Large Eddy Simulations (LES) to create a detailed dataset of an 8-turbine wind farm, consisting of four rows of two turbines each. To accurately model the atmospheric boundary layer, they employed a local 1D soil heat conduction model with time-periodic solar surface heating, coupled to the LES. After several days of low-resolution simulations to achieve a stable, time-periodic behavior, they conducted high-resolution LES over a 24-hour period.
Their analysis revealed that wind turbine wakes significantly influence the temperature field and spatial surface heat flux patterns. Notably, the simulations showed an increased surface temperature behind the wind farm at night, under the specific conditions of dry, unvegetated soil and a clear sky. Interestingly, the researchers observed that during the morning hours, the first row of wind turbines generated less power compared to the last row.
The study also identified that during the morning transition, the presence of a low-level jet and the wind farm blockage effect combined to cause cooling and a reduction in wind speed at hub height upstream of the wind farm. Additionally, larger turbulence levels were found downstream within the wind farm, which explained the higher power production of downstream turbines.
These findings have practical implications for the energy sector, particularly in optimizing wind farm layouts and improving turbine performance. By understanding the dynamics of wind farm wakes and their interaction with the atmospheric boundary layer, developers can better design wind farms to maximize energy output and efficiency. The innovative web-services facilitated data access tools developed for this study also provide a valuable resource for further research and analysis in the field.
This article is based on research available at arXiv.