The power performance and the wind velocity field of an onshore wind farm are predicted
with machine learning models and the pseudo‐2D RANS model, then assessed against …

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 …

The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused
on gathering critical observations of wind farm–atmosphere interactions. These interactions …

Flow modifications induced by wind turbine rotors on the incoming atmospheric boundary
layer (ABL), such as blockage and speedups, can be important factors affecting the power …

In this article, we provide a methodological framework for designing the scanning strategies
of nacelle-mounted scanning lidars for wind energy field experiments, and apply it at two …

In this study, we consider the impact of large-scale, convective structures in an unstable
atmospheric boundary layer on wind turbine wakes. Simulation data from a high-fidelity …

Reynolds-averaged Navier-Stokes (RANS) simulations of wind turbine wakes are usually
conducted with two-equation turbulence models based on the Boussinesq hypothesis …

To maximize the profitability of wind power plants, wind farms are often characterized by
high wind turbine density leading to operations with reduced turbine spacing. As a …

Neglecting the velocity reduction in the induction zone of wind turbines can lead to
overestimates of power production predictions, and, thus, of the annual energy production …

With the increased availability of experimental measurements aiming at probing wind
resources and wind turbine operations, machine learning (ML) models are poised to …