Modeling the Seasonal Variability of Wind Farm Wakes

Abstract:

Wind farm wake effects during low-level jet (LLJ) events may depend on the season in which they occur. We investigate four LLJ cases, one for each season, to determine the impact of seasonal variability on wind farm wakes and variables relevant for wind energy. We use the Weather Research and Forecasting (WRF) model, focused on the location of the Dept. of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site near Lamont, Oklahoma where observational data is available for model skill evaluation (see Figure 1).

We first quantify model skill to investigate the impact of seasonal variability on forecasting important wind energy variables such as boundary-layer height, wind speeds at wind turbine hub-height, turbulence intensity at hub height, and atmospheric stability. This model skill quantification uses lidar-based wind and turbulence profiles as well as surface station measurements. We also quantify model sensitivity to planetary boundary layer (PBL) schemes by comparing the MYNN and QNSE schemes. Finally, WRF simulations with and without the wind farm parameterization (WFP) are compared to quantify wake impacts. This study will provide new insight into the impact of seasonal variability on wind farm wakes while also exploring differences in model skill based on season and PBL scheme choice.