Author:
Narasimhan Ghanesh,Gayme Dennice F.,Meneveau Charles
Abstract
Abstract
Reliable characterization of wind turbine wakes in the presence of Atmospheric Boundary Layer (ABL) flows is crucial to accurately predict wind farm performance. Wind veering in the ABL shears the wake in the lateral direction, and wind veer strength depends on the thermal stability of the ABL. Analytical wake modeling approaches must capture these ABL effects to ensure correct prediction of the wake structure under varied atmospheric conditions. To this end, a new physics-based analytical wake model is developed in this study that is capable of predicting the shape of wakes influenced by wind veer and thermal stratification effects. This model combines a novel ABL wind field model with the Gaussian wake model. The new ABL wind model is capable of predicting both the streamwise and spanwise velocity components in conventionally neutral (CNBL) and stable (SBL) ABL flows. The analytical expressions for both of these horizontal velocity components adhere to Monin-Obukhov Similarity Theory (MOST) in the surface layer, while capturing wind veering in the outer layer of the ABL. Incorporating this ABL model with the Gaussian wake model predicts laterally deflected wake shapes in a fully predictive and self-consistent fashion for a wide range of atmospheric conditions. The results also demonstrate that the enhanced wake model gives improved predictions relative to Large Eddy Simulations of power losses due to wake interactions under strongly stably stratified atmospheric conditions, where wind veer effects are dominant.