As grid-connected wind farms become more common in the modern power system, the
question of how to maximize wind power generation while limiting downtime has been a …

The wake management of offshore wind farms (OWFs) mainly considers the wake effect.
Wake effects commonly occur in offshore wind farms, which cause a 5–10% reduction in …

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 …

To track the dynamics of AI and wind power technology knowledge interaction and predict
future interaction directions, this study proposes a multiview and multilayer patent analysis …

This study describes a deep reinforcement learning (DRL) based decentralized yaw
optimization method to maximize the power production of wind farms. Specifically, we apply …

The presence of wake flows caused by wind turbines (WTs) diminish the expected power
generation of wind energy and exacerbate structural vibrations. To mitigate these issues …

The main objective of this study is to employ the Extreme Gradient Boosting (XGBoost)
machine learning algorithm to predict the power, wake, and turbulent characteristics of …

The modeling of wake effects plays an essential role in wind farm optimal design and
operation. In this study, a novel deep learning method, called Super-Fidelity Network …

Wake effect is a significant factor contributing to power loss in wind farms. Studies have
shown that wake steering control can mitigate this power loss. Currently, wind farm wake …

Wind turbine wake prediction considering yawed condition is of great importance for wind
farm applications. Tremendous efforts have been made on yawed wind turbine wake …