Quantifying Wake Impacts on Downwind Wind Farms Using the WRF Wind Farm Parameterization

Wind energy is growing rapidly to meet increasing energy demands while reducing carbon dioxide emissions. Wind farms are now being built in close proximity to previously-built farms. This close proximity leads to interactions between the farms, as turbines create downwind wakes characterized by increased turbulence and reduced wind speeds.

The physical mechanism for these observed economic impacts is demonstrated with mesoscale numerical weather prediction simulations. Using the Weather Research and Forecasting (WRF) model and the WRF Wind Farm Parameterization (WFP), we simulate three cases to quantify wake effects: one containing the “upwind”, “downwind”, and “control” wind farms; one containing the “downwind” and “control” wind farms only; and one without wind farms at all. Each scenario is simulated daily throughout the months of January and September in 2013, in which the prevailing winds create strong and weak wake impacts, respectively. The three cases allow us to isolate the impacts that the upwind wind farm’s wake poses for the power production of the downwind wind farm. The hourly temporal resolution of the mesoscale simulations reveal how simulated wind farm wakes vary as a function of wind speed, wind direction, and atmospheric stability, with the largest effects during stable conditions and when the wind farms are aligned with the wind direction (Figure 1). Simulated wakes created by the addition of the upwind wind farm result in an 8% drop in capacity at the downwind wind farm over the month of January. Comparison of the simulation data to West Texas Mesonet sodar data validates that WRF is adequately capturing the key features of wind speed increases and decreases.