Beyond the First Generation of Wind Modeling for Resource Assessment and Siting: From Meteorology to Uncertainty Quantification
Abstract
:1. Introduction
An Exceptional Multi-Disciplinary Problem
2. Some Wind Energy Meteorology
2.1. Describing the Parameter Space for Wind
- ABL Rossby number [21];
2.2. First Applications of Meteorology in Wind Energy
2.3. Meteorology Beyond the Surface-Layer
2.4. Modeling Advancements and Their Consequences
2.4.1. RANS Modeling
2.4.2. Mesoscale Modeling
3. Appropriate Statistical Characterization, from Theory to Practice
3.1. Rational Averaging Implicit in Classic WRA
3.2. Refined Modeling and Consequent Sampling Issues
3.3. Averaging Issues Arising with Time Series Use or Comparisons
4. Uncertainty Quantification
Uncertainty in the Complex ABL System
5. Industrial Application
5.1. Wind Resources
5.1.1. Wind Uncertainty Components
- Measurement
- Long-Term Correction
- Flow Modeling and Horizontal Extrapolation
- Vertical Extrapolation
- Year-to-Year Project Variability
- Wakes and Blockage
5.1.2. Combination of Uncertainty Components
5.1.3. From Wind to Energy
5.2. Forecasting
5.3. Wind Atlases and Assessments Without Measurements
5.4. Siting, Design, and Standards
5.5. Distinction from Risk
6. Summary
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ABL | Atmospheric boundary layer. |
AEP | Annual energy production. |
ASL | Atmospheric surface layer. |
CFD | Computational Fluid Dynamics. |
EWA | European wind atlas (method). |
EYA | Energy yield assessment. |
GDL | Geostrophic drag law. |
GWA | Global wind atlas. |
HE | Horizontal extrapolation. |
IBL | Internal boundary layer (due to surface roughness changes). |
LES | Large-eddy simulation. |
LT | Long term. |
LTC | Long-term correction. |
ML | Machine learning. |
M-O | Monin-Obukhov (similarity theory) |
NWP | Numerical weather prediction. |
PBL | Planetary boundary layer (for NWP models). |
Probability density function. | |
PIRT | Phenomenon identification and ranking table. |
RANS | Reynolds-averaged Navier–Stokes. |
UQ | Uncertainty quantification. |
VE | Vertical extrapolation. |
V&V | Validation and verification. |
WRA | Wind resource assessment. |
WRF | Weather research and forecasting model. |
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Component (bold) or subcomponent (italic) |
Measurement Uncertainty |
Wind speed measurement |
Wind direction measurement/rose |
Other atmospheric parameters |
Data integrity and documentation |
Historical Wind Resource (LTC) |
Representativeness of long-term reference period |
Reference data consistency |
Long-term correction method |
On-site gap-filling/synthesis |
Representativeness of measured data |
Wind distribution fit |
Horizontal Extrapolation and flow modeling |
Model inputs |
Model “stress” (deviation from operational envelope) |
Model appropriateness |
Vertical (power-law) Extrapolation |
Model representativeness † |
Excess uncertainty propagated by VE-model |
Project Evaluation Period Variability |
Interannual variability (IAV) of wind speed |
Climate change |
(IAV of plant performance) ‡ |
Plant Performance |
Turbine interaction/wake and blockage effects |
(Non-wind elements) ‡ |
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Kelly, M. Beyond the First Generation of Wind Modeling for Resource Assessment and Siting: From Meteorology to Uncertainty Quantification. Energies 2025, 18, 1589. https://doi.org/10.3390/en18071589
Kelly M. Beyond the First Generation of Wind Modeling for Resource Assessment and Siting: From Meteorology to Uncertainty Quantification. Energies. 2025; 18(7):1589. https://doi.org/10.3390/en18071589
Chicago/Turabian StyleKelly, Mark. 2025. "Beyond the First Generation of Wind Modeling for Resource Assessment and Siting: From Meteorology to Uncertainty Quantification" Energies 18, no. 7: 1589. https://doi.org/10.3390/en18071589
APA StyleKelly, M. (2025). Beyond the First Generation of Wind Modeling for Resource Assessment and Siting: From Meteorology to Uncertainty Quantification. Energies, 18(7), 1589. https://doi.org/10.3390/en18071589