[1] W.-Y. Chang, "An RBF Neural Network Combined with OLS Algorithm and Genetic Algorithm for Short-Term Wind Power Forecasting," Journal of Applied Mathematics, vol. 2013, p. 9, 2013.
[2] C. Peiyuan, T. Pedersen, B. Bak-Jensen, and C. Zhe, "ARIMA-Based Time Series Model of Stochastic Wind Power Generation," Power Systems, IEEE Transactions on, vol. 25, pp. 667-676, 2010.
[3] J. Jung and R. P. Broadwater, "Current status and future advances for wind speed and power forecasting," Renewable and Sustainable Energy Reviews, vol. 31, pp. 762-777, 3// 2014.
[4] C. Monteiro, R. Bessa, V. Miranda, A. Botterud, J. Wang, G. Conzelmann, et al., "Wind power forecasting : state-of-the-art 2009," ANL/DIS-10-1; TRN: US200924%%351 United States10.2172/968212TRN: US200924%%351Thu Dec 31 07:14:26 EST 2009ANLENGLISH, 2009.
[5] J. Mendes, R. J. Bessa, H. Keko, J. Sumaili, V. Miranda, C. Ferreira, et al., "Development and testing of improved statistical wind power forecasting methods," ANL/DIS-11-7; TRN: US201201%%722 United States10.2172/1031455TRN: US201201%%722Thu Jan 26 07:19:05 EST 2012ANLENGLISH, 2011.
[6] Y. Zhang, J. Wang, and X. Wang, "Review on probabilistic forecasting of wind power generation," Renewable and Sustainable Energy Reviews, vol. 32, pp. 255-270, 4// 2014.
[7] B. Santos, C. Monteiro, C. Soares, J. Catalão, G. Osório, J. Rojas, et al., "Report on the mathematical formulation of the different forecasting models and data analysis," Singular2012.
[8] G. Giebel, R. Brownsword, G. Kariniotakis, M. Denhard, and C. Draxl, "The State-Of-The-Art in Short-Term Prediction of Wind Power A Literature Overview, 2nd Edition," Project report for the Anemos.plus and SafeWind projects2011.
[9] C. Monteiro, L. A. Fernandez-Jimenez, I. J. Ramirez-Rosado, A. Muñoz-Jimenez, and P. M. Lara-Santillan, "Short-Term Forecasting Models for Photovoltaic Plants: Analytical versus Soft-Computing Techniques," Mathematical Problems in Engineering, vol. 2013, p. 9, 2013.
[10] W. Glassley, J. Kleissl, C. P. C. v. Dam, H. Shiu, J. Huang, G. Braun, et al., "Appendix B - Wind Energy Forecasting: A Review of State-of-the Art and Recommendations for Better Forecasts," California Renewable Energy Forecasting, Resource Data and Mapping, 2010.
[11] W. Chang, "A Literature Review of Wind Forecasting Methods," Journal of Power and Energy Engineering, vol. 2, pp. 161-168, (2014).
[12] A. Tascikaraoglu and M. Uzunoglu, "A review of combined approaches for prediction of short-term wind speed and power," Renewable and Sustainable Energy Reviews, vol. 34, pp. 243-254, 6// 2014.
[13] H. Madsen, P. Pinson, G. Kariniotakis, H. A. Nielsen, and T. Nielsen, "Standardizing the Performance Evaluation of ShortTerm Wind Power Prediction Models," Wind Engineering, vol. 29, pp. 475-489, 12/01/ 2005.
[14] P. Pinson and G. Kariniotakis, "On-line assessment of prediction risk for wind power production forecasts," Wind Energy, vol. 7, pp. 119-132, 2004.
[15] J. Juban, L. Fugon, and G. Kariniotakis, "Uncertainty estimation of wind power forecasts: Comparison of Probabilistic Modelling Approaches," presented at the European Wind Energy Conference & Exhibition EWEC 2008, Bruxelas, Bélgica, 2008.
[16] H. A. Nielsen, T. S. Nielsen, H. Madsen, G. Giebel, J. Badger, L. Landbergt, et al., "From wind ensembles to probabilistic information about future wind power production -- results from an actual application," in Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on, 2006, pp. 1-8.
[17] T. Gneiting, F. Balabdaoui, and A. E. Raftery, "Probabilistic forecasts, calibration and sharpness," Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 69, pp. 243-268, 2007.
[18] P. Pinson, H. A. Nielsen, J. K. Møller, H. Madsen, and G. N. Kariniotakis, "Non-parametric probabilistic forecasts of wind power: required properties and evaluation," Wind Energy, vol. 10, pp. 497-516, 2007.
[19] J. Juban, L. Fugon, and G. Kariniotakis, "Probabilistic short-term wind power forecasting based on kernel density estimators," in European Wind Energy Conference and exhibition, EWEC 2007, 2007, p. http:/ewec2007proceedings. info/>.
[20] J. Juban, N. Siebert, and G. N. Kariniotakis, "Probabilistic Short-term Wind Power Forecasting for the Optimal Management of Wind Generation," in Power Tech, 2007 IEEE Lausanne, 2007, pp. 683-688.
[21] R. J. Bessa, V. Miranda, A. Botterud, W. Jianhui, and E. M. Constantinescu, "Time Adaptive Conditional Kernel Density Estimation for Wind Power Forecasting," Sustainable Energy, IEEE Transactions on, vol. 3, pp. 660-669, 2012.
[22] A. d. S. Pires, "Improving electrical production forecasting using GPU," Faculdade de Engenharia da Universidade do Porto, 2013.
[23] P. M. N. d. Fonte, "Advanced forecast and scheduling of power systems with highly variable sources," Faculdade de Engenharia da Universidade do Porto, 2015.
[24] P. Billingsley, Probability and Measure, Third Edition: New York, Toronto, London: John Wiley and Sons Inc, 1995.
[25] E. A. Nadaraya, "On Estimating Regression," Theory of Probability & Its Applications, vol. 9, pp. 141-142, 1964.
[26] G. S. Watson, "Smooth regression analysis," Sankhya Ser., 26:359-372, 1964.