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| DOI | 10.1016/J.ENERGY.2019.116027 | ||||
| Año | 2019 | ||||
| Tipo | artículo de investigación |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
In this work, a comprehensive analysis of WRF initial conditions was performed to estimate the offshore wind power on the coasts of the IV region of Coquimbo, Chile. Three configurations of atmospheric physical models accounting for the planetary boundary layer and surface layer were put under consideration. In addition, sensitivity was estimated by using four physical-numerical simulations: spectral nudging, surface model, 10-days restart and definition of vertical levels. Simulations were carried out for January and July 2013. The results show that the initial condition composed of physical schemes MYNN3 - MYNN - Noah (C3) has the lowest RMSE and highest r(2) with 1.748 m s(-1) and 0.755 for January, and 2.512 m s(-1) RMSE and 0.472 r(2) for July. In the sensitivity analysis, the configuration of vertical levels (S3) has the lowest RMSE with 1.812 m s(-1) and the highest r(2) with 0.732. High seasonal variability between January and July 2013 and WRF initial conditions have an impact on the estimation of the wind power and technical feasibility indicators in the study area, with differences between simulated and LV data in the range of 0.01%-36.3%. (C) 2019 Elsevier Ltd. All rights reserved.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | G. Alonso-de-Linaje, Nicolás | - |
Universidad de Chile - Chile
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| 2 | MATTAR-BADER, CRISTIAN | Hombre |
Universidad de Aysen - Chile
Laboratory of Geosciences of the University of Aysén - Chile |
| 3 | BORVARAN-BAEZ, DAGER ISRAEL | - |
Universidad de Chile - Chile
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| Fuente |
|---|
| Fondo Nacional de Desarrollo Científico y Tecnológico |
| Fondecyt Regular |
| Fondo Nacional de Desarrollo CientÃfico y Tecnológico |
| National Laboratory of High Performance Computing (NLHPC) |
| Wind Energy Department of the Technical University of Denmark |
| National Laboratory of High Performance Computing |
| Key Laboratory of High Performance Computing and Stochastic Information Processing |
| Danmarks Tekniske Universitet |
| Agradecimiento |
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| The author would like to thank to Andrea Hahmman of the Wind Energy Department of the Technical University of Denmark for her great collaboration on this work. This study was partially supported by the National Laboratory of High Performance Computing (NLHPC) and the FONDECYT Regular - Project Code ref. 1181155. |
| The author would like to thank to Andrea Hahmman of the Wind Energy Department of the Technical University of Denmark for her great collaboration on this work. This study was partially supported by the National Laboratory of High Performance Computing (NLHPC) and the FONDECYT Regular - Project Code ref. 1181155. |