@inproceedings{3572ecf07aba4d06b07fc2ab167ea3a5,
title = "Wake-based wind turbine optimisations under yawed conditions",
abstract = "The yawed wind turbines in the upstream can be used to reduce wake losses for the downstream wind turbines. Accurate prediction for the wake aerodynamics performance under yawed operation condition is of significant importance for such a controlling strategy. In the present paper, an improved engineering wake model considering yawed conditions is implemented to simulate the wakes behind yawed wind turbines. Firstly, an improved engineering yaw model is utilized to simulate the wakes under yawed conditions. The improved wake model is based on the unsteady Blade Element Momentum (BEM) method with the induction factor and thrust coefficient as key parameters. Secondly, based on genetic algorithm optimization method, the yawed angles control optimization platform is built with wake model of wind turbine. Finally, the loads and aerodynamic performance are analyzed under optimal yawed angles of multi-wind turbine. The results showed that the improved engineering yawed model and yaw control strategy can be accurately and efficiently utilized in enhancing the wake velocity and aerodynamic performance of the yawed wind turbine.",
keywords = "Wind turbine, Wake model, Yawed operation condition, Optimization",
author = "Jiufa Cao and Xiang Gao and Xiang Shen and Haoyuan Sun and Yi Ju",
year = "2023",
month = mar,
day = "17",
language = "English",
isbn = "9798350333220",
series = "Environment Friendly Energies and Applications (EFEA)",
publisher = "IEEE",
number = "7",
pages = "1--5",
booktitle = "2022 7th International Conference on Environment Friendly Energies and Applications (EFEA)",
address = "United States",
edition = "7th",
note = "7th International Conference on Environment Friendly Energies and Applications, EFEA 2022 ; Conference date: 14-12-2022 Through 16-12-2022",
}