Ir al contenido

Documat


Formación y aplicación con las TIC para el estudio sobre granjas eólicas mediante el uso de esquemas de asimilación de datos

  • Juan Carlos Calabria-Sarmiento [1] ; Elías D. Niño-Ruiz [1] ; Randy S. Consuegra-Ortega [1]
    1. [1] Universidad del Norte

      Universidad del Norte

      Colombia

  • Localización: Innovación y tecnología en contextos educativos / Enrique Sánchez Rivas (aut.) Árbol académico, Julio Ruiz Palmero (aut.) Árbol académico, 2019, ISBN 9788417449933, págs. 925-938
  • Idioma: español
  • Enlaces
  • Resumen
    • Las técnicas de asimilación de datos han permitido obtener mejores pronósticos para distintos tipos de fenómenos mediante la inclusión de datos observados al modelo. Una de las técnicas más conocidas son los filtros de Kalman. Mediante estas técnicas se puede realizar pronósticos meteorológicos que servirán para localizar granjas eólicas.

  • Referencias bibliográficas
    • Anderson, J. L. (2001). An ensemble adjustment Kalman filter for data assimilation. Monthly Weather Review, 129(12), 2884–2903.
    • Anderson, J. L. (2019). A Nonlinear Rank Regression Method for Ensemble Kalman Filter Data Assimilation. Monthly Weather Review, 147(8), 2847–2860.
    • Bickel, P. J., Levina, E., y others. (2008). Covariance regularization by thresholding. The Annals of Statistics, 36(6), 2577–2604.
    • Burgers, G., van Leeuwen, P., y Evensen, G. (1998). Analysis scheme in the ensemble Kalman filter. Monthly Weather Review, 126(6), 1719–1724.
    • Chen, Y., y Oliver, D. S. (2010). Cross-covariances and localization for EnKF in multiphase flow data assimilation. Computational Geosciences,...
    • Evensen, G. (2003). The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dynamics, 53(4), 343–367.
    • Godinez, H. C., y Moulton, J. D. (2012). An efficient matrix-free algorithm for the ensemble Kalman filter. Computational Geosciences, 16(3),...
    • Greybush, S. J., Kalnay, E., Miyoshi, T., Ide, K., y Hunt, B. R. (2011). Balance and ensemble Kalman filter localization techniques. Monthly...
    • Gustafsson, N. (2007). Discussion on ‘4D-Var or EnKF?’ Tellus A: Dynamic Meteorology and Oceanography, 59(5), 774–777.
    • Gustafsson, N., y Bojarova, J. (2014). Four-dimensional ensemble variational (4D-EnVar) data assimilation for the high resolution limited...
    • Han, Y., Zhang, J., y Sun, D. (2018). Error control and adjustment method for underwater wireless sensor network localization. Applied Acoustics,...
    • Harlim, J., y Hunt, B. R. (2007). Four-dimensional local ensemble transform Kalman filter: numerical experiments with a global circulation...
    • Houtekamer, P. L., y Mitchell, H. L. (1998). Data assimilation using an ensemble Kalman filter technique. Monthly Weather Review, 126(3),...
    • Huang, X.-Y., Xiao, Q., Barker, D. M., Zhang, X., Michalakes, J., Huang, W., … others. (2009). Four-dimensional variational data assimilation...
    • Ito, S., Nagao, H., Yamanaka, A., Tsukada, Y., Koyama, T., Kano, M., y Inoue, J. (2016). Data assimilation for massive autonomous systems...
    • Kalnay, E. (2003). Atmospheric modeling, data assimilation and predictability. Cambridge university press.
    • Kopiske, J., Spieker, S., y Tsatsaronis, G. (2017). Value of power plant flexibility in power systems with high shares of variable renewables:...
    • Lahoz, B. K. W., y Menard, R. (2010). Data assimilation. Springer.
    • Lei, L., Whitaker, J. S., y Bishop, C. (2018). Improving assimilation of radiance observations by implementing model space localization in...
    • Levina, E., Rothman, A., Zhu, J., y others. (2008). Sparse estimation of large covariance matrices via a nested lasso penalty. The Annals...
    • Liu, Z. (2017). China’s strategy for the development of renewable energies. Energy Sources, Part B: Economics, Planning, and Policy, 12(11),...
    • Lorenc, A. C. (2003). The potential of the ensemble Kalman filter for NWP—a comparison with 4D-Var. Quarterly Journal of the Royal Meteorological...
    • Miyoshi, T., y Kunii, M. (2012). The local ensemble transform Kalman filter with the Weather Research and Forecasting model: Experiments with...
    • Nino-Ruiz, E. (2017). A matrix-free posterior ensemble kalman filter implementation based on a modified cholesky decomposition. Atmosphere,...
    • Nino-Ruiz, E. D., Mancilla, A., y Calabria, J. C. (2017). A Posterior Ensemble Kalman Filter Based On A Modified Cholesky Decomposition. Procedia...
    • Nino-Ruiz, E. D., Sandu, A., y Deng, X. (2017). A parallel implementation of the ensemble Kalman filter based on modified Cholesky decomposition....
    • Nino-Ruiz, E. D., Sandu, A., y Deng, X. (2018). An ensemble Kalman filter implementation based on modified Cholesky decomposition for inverse covariance...
    • Reichle, R. H. (2008). Data assimilation methods in the Earth sciences. Advances in Water Resources, 31(11), 1411–1418.
    • Rothman, A. J., Levina, E., y Zhu, J. (2009). Generalized thresholding of large covariance matrices. Journal of the American Statistical Association,...
    • Ruiz, E. D. N., y Sandu, A. (2016). A derivative-free trust region framework for variational data assimilation. Journal of Computational and...
    • Stengel, M., Undén, P., Lindskog, M., Dahlgren, P., Gustafsson, N., y Bennartz, R. (2009). Assimilation of SEVIRI infrared radiances with...
    • Stroud, J. R., Katzfuss, M., y Wikle, C. K. (2018). A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation....
    • Trémolet, Y. (2006). Accounting for an imperfect model in 4D-Var. Quarterly Journal of the Royal Meteorological Society: A Journal of the...
    • Trémolet, Y. (2007). Incremental 4D-Var convergence study. Tellus A: Dynamic Meteorology and Oceanography, 59(5), 706–718.
    • Verzijlbergh, R. A., De Vries, L. J., Dijkema, G. P. J., y Herder, P. M. (2017). Institutional challenges caused by the integration of renewable...
    • Wang, X., Hamill, T. M., Whitaker, J. S., y Bishop, C. H. (2007). A comparison of hybrid ensemble transform Kalman filter--optimum interpolation...
    • Yin, J., Zhan, X., Zheng, Y., Hain, C. R., Liu, J., y Fang, L. (2015). Optimal ensemble size of ensemble Kalman filter in sequential soil...
    • Zhang, X., y Wang, Y. (2017). How to reduce household carbon emissions: A review of experience and policy design considerations. Energy Policy,...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno