Revisión de literatura de modelos computacionales para la predicción de la velocidad del viento de 2004 a 2016

• Tripp-Barba, Carolina ^[1]
  1. [1] Universidad Autónoma de Sinaloa

     Universidad Autónoma de Sinaloa

     México

     
• Localización: Revista de Investigación en Tecnologías de la Información: RITI, ISSN-e 2387-0893, Vol. 8, Nº. 15, 2020 (Ejemplar dedicado a: Enero-Junio), págs. 27-40
• Idioma: español
• DOI: 10.36825/RITI.08.15.004
• Títulos paralelos:
  • A survey of computational models for wind speed forecasting from 2004 to 2016
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    El pronóstico de la velocidad del viento es un tema ampliamente investigado en la actualidad. Un factor clave a tener en cuenta es su importancia en el diseño y el cálculo de estructuras para edificios de tamaño considerable que se construirán en zonas de huracanes de alto riesgo. Otra rama de esta línea de investigación incluye su utilidad en la predicción de energía eólica, que no es un tema para discutir en este artículo. Aquí se presenta una clasificación de modelos computacionales para el pronóstico de la velocidad del viento de acuerdo con la técnica matemática utilizada para el pronóstico y basada en la revisión de la literatura. Las técnicas utilizadas para clasificar son: regresión lineal multivariante, redes neuronales artificiales, series de tiempo, lógica difusa y el proceso gaussiano. A lo largo del desarrollo de esta investigación, las redes neuronales artificiales y las aplicaciones de lógica difusa se identificaron como futuras líneas de investigación combinadas con un trabajo eficiente de minería de datos. Palabras clave: Modelos computacionales, Modelos de pronóstico, Velocidad del viento, Revisión de literatura.doi: https://doi.org/10.36825/RITI.08.15.004

  • English

    Wind speed forecast is a topic broadly researched in the present day. Its importance in the design and calculations of structures for considerably sized buildings to be built in high risk hurricane zones is a key factor to consider. Another branch off this line of research includes its utility in Eolic energy prediction, which is not a subject to discuss in this article. Here a classification of computational models for wind speed forecasting is presented according to the mathematic technique used for forecasting and based on literature review. The techniques used to classify are: multivariate lineal regression, artificial neural networks, time series, fuzzy logic, and the Gaussian process. Throughout the development of this research, artificial neural networks and fuzzy logic applications were identified as future lines of research both combined with efficient data mining work.Keywords:Computational Models, Forecasting Models, Wind Speed, Literature Review.

• Referencias bibliográficas
  • Gott, E. (1969). Linear Regression of Interlevel Wind Velocities. IEEE Transactions on Geoscience Electronics, 7 (1), 44-47. doi: https://doi.org/10.1109/TGE.1969.271346
  • British Electrical and Allied Industries Research Association. (1935). Wind Pressure on Latticed Towers—Tests on Models. IEEE Journal of the...
  • El-Fouly, T. H., El-Saadany, E. F., (2012). Grey Predictors for Hourly Wind Speed and Power Forecasting. In: S. Muyeen (Ed.), Wind Energy...
  • Damousis, I. G., Alexiadis, M. C., Theocharis, J. B., Dokopoulos, P. S. (2004). A Fuzzy Model for Wind Speed Prediction and Power Generation...
  • Arjun, N. N., Prema, V., Kumar, D. K., Prashanth, P., Preekshit, V. S., Rao, K. R. (2014). Multivariate Regression models for prediction of...
  • Cadenas, E., Rivera, W., Campos-Amezcua, R., Cadenas, R. (2015). Wind speed forecasting using the NARX model, case: La Mata, Oaxaca, México....
  • Yesilbudak, M., Sagiroglu, S., Colak, I. (2013). A new approach to very short term wind speed prediction using k-nearest neighbor classification....
  • Yu, J., Chen, K., Mori, J., Rashid, M. M. (2013). A Gaussian mixture copula model based localized Gaussian process regression approach for...
  • Wang, J., Zhang, W., Wang, J., Han, T., Kong, L. (2014). A novel hybrid approach for wind speed prediction. Information Sciences, 273, pp....
  • Wang, Y., Su, Z. (2015). A Prediction Method for Wind Speed Based on the Correlation Analysis of Measured Data of Adjacent Wind Turbine. En...
  • Wang, J., Hu, J. (2015). A robust combination approach for short-term wind speed forecasting and analysis e Combination of the ARIMA (Autoregressive...
  • Wu, X., Zhu, Z., Su, X., Fan, S., Du, Z., Chang, Y., Zeng, Q. (2015). A study of single multiplicative neuron model with nonlinear filters...
  • Ak, R., Vitelli, V., Zio, E. (2015). An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction....
  • Bilgili, M., Sahin, B. (2010). Comparative analysis of regression and artificial neural network models for wind speed prediction. Meteorology...
  • Zhang, G., Li, H. X., Gan, M. (2012). Design a Wind Speed Prediction Model Using Probabilistic Fuzzy System. IEEE Transactions on Industrial...
  • Lee, J., Park, G. L., Kim, E. H. (2012). Development of Wind Speed Prediction Model in Jeju City. Computer Applications for Modeling, Simulation...
  • Hervás-Martínez, C., Salcedo-Sanz, S., Gutiérrez, P. A., Ortiz-García, E. G., Prieto, L. (2012). Evolutionary product unit neural networks...
  • Lujano-Rojas, J. M., Bernal-Agustín, J. L., Dufo-López, R., Domínguez-Navarro, J. A. (2011). Forecast of Hourly Average Wind Speed Using ARMA...
  • Kiplangat, D. C., Asokan, K., Kumar, K. S. (2016). Improved week-ahead predictions of wind speed using simple linear models with wavelet decomposition....
  • Lydia, M., Suresh Kumar, S., Immanuel Selvakumara, A., Edwin Prem Kumarc, G. (2016). Linear and non-linear autoregressive models for short-term...
  • Barbounis, T. G., Theocharis, J. B. (2007). Locally recurrent neural networks for wind speed prediction using spatial correlation. Information...
  • Cardenas-Barrera, J. L., Castillo-Guerra, E., Meng, J., Chang, L. (2013). Multi-step-ahead, Short-Term Prediction of Wind Speed Using a Fusion...
  • Gnana Sheela, K., Deepa, S. N. (2013). Neural network based hybrid computing model for wind speed prediction. Neurocomputing, 122, 425-429....
  • El-Fouly, T. H., El-Saadany, E., Salama, M. A. (2008). One Day Ahead Prediction of Wind Speed and Direction. IEEE Transactions on Energy Conversion,...
  • Gnana Sheela, K., Deepa, S. N. (2013). Performance Analysis of Modeling Framework for Prediction in Wind Farms Employing Artificial Neural...
  • Heinermann, J., Kramer, O. (2015). Short-Term Wind Power Prediction with Combination of Speed and Power Time Series. En S. Hölldobler, R....
  • Kusiak, A., Zhang, Z. (2010). Short-Horizon Prediction of Wind Power: A Data-Driven Approach. IEEE Transaction on Energy Conversion, 25 (4),...
  • Doucoure, B., Agbossou, K., Cardenas, A. (2011). Time series prediction using artificial wavelet neural network and multi-resolution analysis:...
  • Kulkarni, M., Patil, S., Rama, G. V., Sen, P. N. (2008). Wind speed prediction using statistical regression and neural network. Journal of...
  • Hu, Q., Zhang, R., Zhou, Y. (2015). Transfer learning for short-term wind speed prediction with deep neural networks. Renewable Energy, 85,...
  • Ghorbani, M. A., Khatibi, R., Hosseini, B., Bilgili, M. (2013). Relative importance of parameters affecting wind speed prediction using artificial...
  • Deligiorgi, D., Philippopoulos, K., Kouroupetroglou, G. (2013). Artificial Neural Network Based Methodologies for the Estimation of Wind Speed....
  • Ernst, B., Oakleaf, B., Ahlstrom, M. L., Lange, M., Moehrlen, C., Lange, B., Focken, U., Rohrig, K. (2007). Predicting the Wind. IEEE Power...