The Future of High-Performance Computing for Wind Energy

The key to optimizing wind energy is the ability to predict and understand the complex interplay of turbulent atmospheric fluid dynamics, turbine wakes, and turbine dynamics. That complexity increases as turbines become larger, wind farms increase in number, and are built in complex terrain both on land and offshore. Predictive simulation of wind plants requires resolving an extreme range of scales, going from sub-millimeter-scale blade boundary layers to kilometer-scale wind plant domains.

Principal Scientist Michael Sprague hosted this webinar in which a panel of wind energy science and technology leaders discussed the creation and application of a new open-source modeling and simulation environment for wind energy called ExaWind. The ExaWind project is a close collaboration among more than 40 researchers from NREL, Sandia National Laboratories, Oak Ridge National Laboratory, the University of Texas at Austin, and Parallel Geometric Algorithms LLC. Our team is assembling and creating a suite of computational fluid dynamics and computational structural dynamics codes for wind turbines and wind plants. ExaWind is funded by the U.S. Department of Energy's Exascale Computing Project (https://www.exascaleproject.org/).