Sensitivity Analysis of the WRF Model: Wind-Resource Assessment for Complex Terrain

Author:

Fernández-González Sergio1,Martín María Luisa2,García-Ortega Eduardo3,Merino Andrés3,Lorenzana Jesús4,Sánchez José Luis3,Valero Francisco1,Rodrigo Javier Sanz5

Affiliation:

1. a Department of Earth Physics, Astronomy and Astrophysics II, Faculty of Physics, Complutense University of Madrid, Madrid, Spain

2. b Department of Applied Mathematics, Faculty of Computer Engineering, University of Valladolid, Segovia, Spain

3. c Atmospheric Physics Group, Instituto de Matemática Interdisciplinar, University of León, León, Spain

4. d Supercomputing Center of Castile and León, University of León, León, Spain

5. e National Renewable Energy Centre (CENER), Sarriguren, Spain

Abstract

AbstractWind energy requires accurate forecasts for adequate integration into the electric grid system. In addition, global atmospheric models are not able to simulate local winds in complex terrain, where wind farms are sometimes placed. For this reason, the use of mesoscale models is vital for estimating wind speed at wind turbine hub height. In this regard, the Weather Research and Forecasting (WRF) Model allows a user to apply different initial and boundary conditions as well as physical parameterizations. In this research, a sensitivity analysis of several physical schemes and initial and boundary conditions was performed for the Alaiz mountain range in the northern Iberian Peninsula, where several wind farms are located. Model performance was evaluated under various atmospheric stabilities and wind speeds. For validation purposes, a mast with anemometers installed at 40, 78, 90, and 118 m above ground level was used. The results indicate that performance of the Global Forecast System analysis and European Centre for Medium-Range Weather Forecasts interim reanalysis (ERA-Interim) as initial and boundary conditions was similar, although each performed better under certain meteorological conditions. With regard to physical schemes, there is no single combination of parameterizations that performs best during all weather conditions. Nevertheless, some combinations have been identified as inefficient, and therefore their use is discouraged. As a result, the validation of an ensemble prediction system composed of the best 12 deterministic simulations shows the most accurate results, obtaining relative errors in wind speed forecasts that are <15%.

Funder

Secretaría de Estado de Investigación, Desarrollo e Innovación

Publisher

American Meteorological Society

Subject

Atmospheric Science

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