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Implementation of a generalized actuator disk model into WRF v4.3: A validation study for a real-scale wind turbine.
- Source :
-
Renewable Energy: An International Journal . Sep2022, Vol. 197, p810-827. 18p. - Publication Year :
- 2022
-
Abstract
- A validation study is carried out for a generalized actuator disk model (GAD) implemented into the Weather Research and Forecasting model, an open-source numerical weather prediction code, in order to simulate the aerodynamic behavior of a real-scale wind turbine under varying atmospheric conditions. Multiple large-eddy simulations (LESs) are performed to resolve energy-containing eddies of turbulent motions utilizing the GAD model, which calculates the wind turbine-induced forces distributed over the rotor disk. The benchmarks defined at the Scaled Wind Technology Facility (SWiFT) campaign, (for details see Doubrawa et al., 2020), were chosen to validate the performance of the GAD model in terms of its capability to reproduce the wake and aerodynamic loading on the rotor. Meteorological data are available from a 60 m meteorological tower located 65 m upstream of the wind turbine, and the aerodynamic data, including scans of downstream velocity profiles, are available for the Vestas V27 wind turbine thanks to DTU's nacelle-mounted, rear-facing SpinnerLidar (Mikkelsen et al., 2013). Rotor performance and wake recovery results obtained from the GAD model are compared with field experiments and other LES data. • Large-eddy simulations of the Vestas V27 wind turbine under varying atmospheric conditions are presented. • A generalized actuator disk model is validated based on field measurements and available LES data. • The wake behavior and aerodynamic response of the wind turbine are investigated for different ABL conditions. • Accurate modeling of wind turbine wakes under stably-stratified ABL is highly dependent on grid resolution. • The generalized actuator disk model performs as good as a generalized actuator line model in certain situations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09601481
- Volume :
- 197
- Database :
- Academic Search Index
- Journal :
- Renewable Energy: An International Journal
- Publication Type :
- Academic Journal
- Accession number :
- 159011313
- Full Text :
- https://doi.org/10.1016/j.renene.2022.07.119