Wind turbine (WT) experiments in wind tunnels can benefit the efficient utilization of wind
energy in many aspects, such as the testing of new products, the validation of numerical …

With the growing number of wind farms over the last few decades and the availability of
large datasets, research in wind-farm flow modeling—one of the key components in …

Yaw control is one of the most promising active wake control strategies to maximize the total
power generation of wind farms. Meanwhile, structural performance needs to be considered …

In the wind industry, power prediction of wind farm is commonly implemented by analytical
wake models, which is low-cost but insufficient in accuracy for high-turbulent wake …

Abstract Machine learning techniques have received a lot of interest in the exploration to
minimize the computational cost of computational fluid dynamics simulation. The present …

To improve the efficiency and reliability of wind power generation, condition monitoring of
wind turbines has drawn extensive attention worldwide. However, blade health monitoring is …

This study used explainable machine learning (XML), a new branch of Machine Learning
(ML), to elucidate how ML models make predictions. Three tree-based regression models …

Wake interactions between wind turbines have a great impact on the overall performance of
a wind farm. In this work, a novel deep learning method, called Bilateral Convolutional …

The development of a more advanced three-dimensional wake model for wind power
generation is presented based on a multivariate Gaussian distribution. The newly-presented …

Layout optimization of wind farms constitutes an important and challenging task in complex
terrain. This is especially due to the complex interactions of the boundary layer flows in …