High fidelity actuator line data from 9 turbine wind farm simulations using ExaWind
-
Gopal R Yalla | Sandia National Laboratories
Lawrence Cheung | Sandia National Laboratories
Kenneth Brown | Sandia National Laboratories
Description
This data was generated with the ExaWind code suite (https://github.com/Exawind) to investigate the performance of different Active Wake Mixing turbine control in a wind farm situated in a stable atmospheric boundary layer. All cases correspond to a 3x3 wind farm in a 10km x 10km domain using a total mesh size that varied between 1.6 X 10^9 to 1.85 X 10^9 grid cells. The simulations were run across 1800-2000 GPUs on Frontier. The case description and data generation process is fully documented in Yalla, G. R., Brown, K., Cheung, L., Houck, D., deVelder, N., and Balaji, J. (2025). "Estimating annual energy production of wake mixing control strategies including comparisons to wake steering." Wind Energy Sciences (https://doi.org/10.5194/wes-2025-250).
Funding Information
DOE Contract Number
DE-NA0003525; DE-AC36-08GO28308Originating Research Organization
Sandia National Laboratories, Albuquerque, NM (United States)Other Contributing Organizations
Oak Ridge National Laboratory (ORNL)Sponsoring Organization
Office of Science; Wind Energy Technology Office, Office of Technology CommercializationRelated Works
- IsSourceOf (URL): https://doi.org/10.5194/wes-2025-250
Details
Release Date
April 8, 2026Subject
17 WIND ENERGYKeywords
wind farm, exawindDataset
Dataset Type
ND Numeric DataCite This Dataset:
Yalla, G., Cheung, L., Brown, K. (2026). High fidelity actuator line data from 9 turbine wind farm simulations using ExaWind. Oak Ridge National Laboratory. https://doi.org/10.13139/OLCF/3012440.
Acknowledgements
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Advanced Scientific Computing Research programs in the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.