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Mesoscale wind speed simulation using CALMET model and reanalysis information: An application to wind potential

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  • Morales, Luis
  • Lang, Francisco
  • Mattar, Cristian

Abstract

This work presents a simple methodology to simulate the mesoscale wind field using dynamic modeling and complementary meteorological data. Meteorological information obtained from the project developed by the National Center of Environmental Research (NCEP) and the National Center of Atmospheric Research (NCAR), meteorological stations, a digital elevation model and a land use data were used in this study. All these data were input for the simulation of wind fields at three different heights (20, 30 and 40 m) through the CALMET model. Simulations were made for an area corresponding to the south central region of Chile, known as the Maule Region. The results show that the simulated spatial resolution (1 × 1 km) in the CALMET model yields good results, yielding an RMSE value near 1 m s−1 for all the heights simulated, with a greater RMSE at 40 m (1.15 m s−1) and a lesser RMSE at 20 m (1.10 m s−1). The direction of the simulated wind fields was also evaluated, yielding an RMSE near 31° at 40 m. The determination of the wind potential is presented as a direct application of the method shown in this work.

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  • Morales, Luis & Lang, Francisco & Mattar, Cristian, 2012. "Mesoscale wind speed simulation using CALMET model and reanalysis information: An application to wind potential," Renewable Energy, Elsevier, vol. 48(C), pages 57-71.
    • Handle: RePEc:eee:renene:v:48:y:2012:i:c:p:57-71
    DOI: 10.1016/j.renene.2012.04.048
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    2. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    3. Watts, David & Oses, Nicolás & Pérez, Rodrigo, 2016. "Assessment of wind energy potential in Chile: A project-based regional wind supply function approach," Renewable Energy, Elsevier, vol. 96(PA), pages 738-755.
    4. Gualtieri, Giovanni & Secci, Sauro, 2014. "Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy," Renewable Energy, Elsevier, vol. 62(C), pages 164-176.
    5. Gualtieri, Giovanni, 2015. "Surface turbulence intensity as a predictor of extrapolated wind resource to the turbine hub height," Renewable Energy, Elsevier, vol. 78(C), pages 68-81.
    6. Siyal, Shahid Hussain & Mörtberg, Ulla & Mentis, Dimitris & Welsch, Manuel & Babelon, Ian & Howells, Mark, 2015. "Wind energy assessment considering geographic and environmental restrictions in Sweden: A GIS-based approach," Energy, Elsevier, vol. 83(C), pages 447-461.
    7. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    8. Milanese, Marco & Tornese, Ljuba & Colangelo, Gianpiero & Laforgia, Domenico & de Risi, Arturo, 2017. "Numerical method for wind energy analysis applied to Apulia Region, Italy," Energy, Elsevier, vol. 128(C), pages 1-10.

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