Analytical yaw models: a two-dimensional comparison

Abstract. Analytical wake models are essential for wind farm design and control. However, they often lack validation beyond scale data. This study compares six, two-dimensional yawed wake models which include single-Gaussian, super-Gaussian, lifting line, and vortex sheet methods. An additional double-Gaussian model is also proposed. All models are calibrated and tested against three datasets: near-wake and far-wake PIV measurements, as well as full-scale turbine data. The proposed double-Gaussian model achieves the lowest mean absolute error (2.6 %) across all datasets. However, all models struggle to predict the full-scale dataset under yawed conditions, emphasising the necessity for validating models against a wide range of turbine operating conditions.