Sponsor
This work was authored in part by the National Renewable Energy Laboratory (NREL) for the US Department of Energy (DOE), operated under grant no. DE-AC36- 08GO28308. Funding was provided by the DOE Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office.
Published In
Wind Energy Science
Document Type
Article
Publication Date
11-30-2025
Subjects
Turbulence -- Computer simulation, Large eddy simulation -- Data processing, Wind farms -- Computer simulation, Wind turbines -- Aerodynamics, Atmospheric turbulence -- Mathematical models, Fluid dynamics -- Databases
Abstract
This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical and some large-eddy simulation datasets of canonical turbulent flows, JHTDB-wind stores the full space-time (4D) history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 6 X 10 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. This data comprises one hour of flow field data (velocity, pressure, potential temperature, and others, approximately 15 TB) and wind turbine data—including both turbine-level operational quantities and blade-level aerodynamic quantities (approximately 1.3 TB)—stored in Zarr and Parquet formats, respectively. Data retrieval is facilitated by the Giverny Python package, allowing remote users to query the database in Python or Matlab (C and Fortran support are available for flow field data). This paper details the simulation setup and demonstrates data access through examples that analyze wind farm flow structures and turbine performance. The framework is extensible to future datasets, including the JHTDB-wind diurnal cycle simulation analyzed in Xiao et. al (2025).
Rights
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
Locate the Document
DOI
10.5194/wes-10-2821-2025
Persistent Identifier
https://archives.pdx.edu/ds/psu/44276
Publisher
Copernicus GmbH
Citation Details
Zhu, X., Xiao, S., Narasimhan, G., Martinez-Tossas, L. A., Schnaubelt, M., Lemson, G., Yao, H., Szalay, A. S., Gayme, D. F., & Meneveau, C. (2025). JHTDB-wind: a web-accessible large-eddy simulation database of a wind farm with virtual sensor querying. Wind Energy Science, 10(12), 2821–2840.