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 …

In this study, four NNs models are designed by three types of data: CFD data of original (no-
dimpled), dimpled blades, and experimental data. These data are used to estimate torque …

In the past few decades, wind energy technology has undergone rapid development, with
large-scale wind farms bringing about significant wake effect. Since the wake effect can …

Subject to the inherent high uncertainty of wind, the prediction for its speed and direction
may be insufficiently accurate, the resulting decision actions of active yaw control (AYC) may …

Previous studies on wake of horizontal-axis wind turbines (HAWTs) mainly focus on the
spatial distribution but ignore the time-varying characteristics of the wake profile which …

Data-driven techniques can enable enhanced insights into wind turbine operations by
efficiently extracting information from turbine data. This work outlines a data-driven strategy …

Greenhouse climate control is important to provide sufficient fresh food for the growing
population in an economical and sustainable manner. However, the developed crop-climate …

The random fluctuations of wind energy and external grid voltage disturbances can both
lead to serious voltage fluctuations and voltage deviations in the wind farm (WF) …

The exploitation of nature to convert energy to electrical power is the most important rule in
power generation. Wind energy is one of the most important of those energies that are …

Abstract Dynamic Mode Decomposition (DMD) is a data-driven analysis method for plenty of
snapshots, which has good application prospects in the combustion diagnostics base on …