Fully Automated Wind Site Assessment in Complex Terrain Using Satellite Data and Global Circulation Models.
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| Title: | Fully Automated Wind Site Assessment in Complex Terrain Using Satellite Data and Global Circulation Models. |
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| Authors: | Horvath, Andras1 (AUTHOR), Gutjahr, Karlheinz2 (AUTHOR), Kuttner, Christian1 (AUTHOR), Hofer-Schmitz, Katharina2 (AUTHOR), Perko, Roland2 (AUTHOR) roland.perko@joanneum.at |
| Source: | Remote Sensing. May2026, Vol. 18 Issue 9, p1403. 42p. |
| Subjects: | General circulation model, Wind energy conversion systems, Flow simulations, Deep learning, Computer simulation, Remote sensing, Topography |
| Abstract: | Highlights: What are the main findings? Data from Earth observation, global circulation models, and high-resolution fluid dynamics simulations are combined in an automated simulation workflow. The model accuracy challenges non-automated state-of-the-art simulation methods. What are the implications of the main findings? The model is applicable globally with minimal manual input. De-risking investments might become feasible without costly on-site measurements. A globally applicable and fully automated simulation method based on satellite-derived Earth Observation (EO) data and global circulation models was developed and validated. Inputs to the simulation are DSM/DTM layers, surface roughness layer, forest canopy layer, and single-level point data from the European Centre for Medium-Range Weather Forecasts fifth-generation ECMWF reanalysis (ECMWF ERA5, a global circulation model produced by the Copernicus Climate Change Service (C3S)). High-resolution roughness length maps are produced by deep learning from optical satellite data. Velocity fields are predicted by fluid dynamics simulations in OpenFOAM using the IDDES turbulence model, a 3D resolved tree canopy implemented as isotropic momentum sinks, and a corrector step based on sub-grid-scale dynamic downscaling of ERA5 data. No calibration data from wind measurements close to the target are necessary to achieve results accurate enough for site assessments and wind park planning. The presented method is suitable for the prediction of average wind speeds and average power densities in complex terrain with high ruggedness indices for WEC (wind energy converter) installations closer to the ground and at hub heights of typical large-scale WECs. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? Data from Earth observation, global circulation models, and high-resolution fluid dynamics simulations are combined in an automated simulation workflow. The model accuracy challenges non-automated state-of-the-art simulation methods. What are the implications of the main findings? The model is applicable globally with minimal manual input. De-risking investments might become feasible without costly on-site measurements. A globally applicable and fully automated simulation method based on satellite-derived Earth Observation (EO) data and global circulation models was developed and validated. Inputs to the simulation are DSM/DTM layers, surface roughness layer, forest canopy layer, and single-level point data from the European Centre for Medium-Range Weather Forecasts fifth-generation ECMWF reanalysis (ECMWF ERA5, a global circulation model produced by the Copernicus Climate Change Service (C3S)). High-resolution roughness length maps are produced by deep learning from optical satellite data. Velocity fields are predicted by fluid dynamics simulations in OpenFOAM using the IDDES turbulence model, a 3D resolved tree canopy implemented as isotropic momentum sinks, and a corrector step based on sub-grid-scale dynamic downscaling of ERA5 data. No calibration data from wind measurements close to the target are necessary to achieve results accurate enough for site assessments and wind park planning. The presented method is suitable for the prediction of average wind speeds and average power densities in complex terrain with high ruggedness indices for WEC (wind energy converter) installations closer to the ground and at hub heights of typical large-scale WECs. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18091403 |
