M. Sengupta and J. Keller, PV ramping in a distributed generation environment: A study using solar measurements, 2012 38th IEEE Photovoltaic Specialists Conference, pp.586-589, 2012.
DOI : 10.1109/PVSC.2012.6317681

R. J. Bessa, V. Miranda, A. Botterud, and J. Wang, Time Adaptive Conditional Kernel Density Estimation for Wind Power Forecasting, IEEE Transactions on Sustainable Energy, vol.3, issue.4, 2012.
DOI : 10.1109/TSTE.2012.2200302

J. Juban, L. Fugon, and G. Kariniotakis, Probabilistic short-term wind power forecasting based on kernel density estimators, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00526011

H. Bludszuweit, J. A. Dominguez-navarro, and A. Llombart, Statistical Analysis of Wind Power Forecast Error, IEEE Transactions on Power Systems, pp.983-991, 2008.
DOI : 10.1109/TPWRS.2008.922526

J. Jeon and J. W. Taylor, Using Conditional Kernel Density Estimation for Wind Power Density Forecasting, Journal of the American Statistical Association, vol.26, issue.497, pp.66-79, 2012.
DOI : 10.1093/jjfinec/nbn007

A. T. Awami and M. , Statistical characterization of wind power output for a given wind power forecast, 41st North American Power Symposium, pp.1-4, 2009.
DOI : 10.1109/NAPS.2009.5484044

A. Manuel, R. J. Matos, and . Bessa, Setting the Operating Reserve Using Probabilistic Wind Power Forecasts, IEEE TRANSACTIONS ON POWER SYSTEMS, vol.26, 2011.

J. Bremnes and . Bjørnar, Probabilistic wind power forecasts using local quantile regression, Wind Energy 2004 v1 Issue, pp.47-54

G. Fu, F. Y. Shih, and H. Wang, A kernel-based parametric method for conditional density estimation, Pattern Recognition, vol.44, issue.2, pp.284-294, 2011.
DOI : 10.1016/j.patcog.2010.08.027

C. Monteiro, I. J. Ramirez-rosado, and L. A. Fernandez-jimenez, Shortterm forecasting model for electric power production of small-hydro power plants, Renewable Energy, issue.6, pp.387-394

R. Williamson, Probabilistic Arithmetic, 1989.