Optimization of wind turbine yaw angles in a wind farm using a three-dimensional yawed wake model. (15th October 2020) - Dou, Bingzheng; Qu, Timing; Lei, Liping; Zeng, Pan
Abstract: An appropriate yaw angle misalignment of the wind turbines in a wind farm has been found to improve the average energy production of the turbine array. Predicting the spatial evolution of the yawed turbine wakes is a key factor in optimizing the yaw angles. In this study, a new three-dimensional yawed wake model is proposed to estimate the non-centrosymmetric cross-sectional shape of the yawed wake velocity distribution, and the model is experimentally validated. Then, a yaw angle optimization strategy that optimizes the wind farm yaw angle distribution and maximizes the power output using the proposed wake model is described. The covariance matrix adaptation evolution strategy is employed as an intelligent algorithm to implement the optimization. The results indicate that yaw angle optimization improves the power of an offshore wind farm by up to 7%, and the optimization yields better results for a small streamwise spacing between turbines than for a large streamwise spacing. Wind farm yaw angle optimization shows great promise for the development of smart wind farms because it has the potential to enable real-time optimization of the yaw angles in response to changes in the incoming wind direction. Highlights: A new 3-D wake model is proposed to predict the yawed turbine wake velocity. The wake model can predict the curled cross-section shape of the wake velocity. The yaw angle misalignment is adopted to improve the wind farm power production. An optimization strategy is proposed to adjust the wind farm yaw angles. The optimization strategy is based on the wake model and an intelligent algorithm.