A. Purvins, A. Zubaryeva, M. Llorente, E. Tzimas, and A. Mercier, Challenges and options for a large wind power uptake by the European electricity system, Applied Energy, vol.88, issue.5, pp.88-1461, 2011.
DOI : 10.1016/j.apenergy.2010.12.017

G. Montes and E. Martín, Protability of wind energy: short-term risk factors and possible improvements, Renewable and Sustainable Energy Reviews, vol.11, p.21912200, 2007.

U. Focken, M. Lange, and H. , Previento -a wind power prediction system with innovative upscaling algorithm, Proc. Europ. Wind Energy Conf. EWEC

I. Marti, What performance can be expected by short-term wind power prediction models depending on site characteristics?, CD- Rom Proceedings
URL : https://hal.archives-ouvertes.fr/hal-00529266

P. Pinson, Estimation of the uncertainty in wind power forecasting, 2006.
URL : https://hal.archives-ouvertes.fr/pastel-00002187

P. Pinson, C. Chevallier, and G. Kariniotakis, Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power, IEEE Transactions on Power Systems, vol.22, issue.3, 2007.
DOI : 10.1109/TPWRS.2007.901117
URL : https://hal.archives-ouvertes.fr/hal-00617685

F. Bourry, Management of uncertainties related to renewable generation participation in electricity market, 2009.

V. Marano, G. Rizzo, and F. A. Tiano, Application of dynamic programming to the optimal management of a hybrid power plant with wind turbines, photovoltaic panels and compressed air energy storage, Applied Energy, vol.97, 2012.
DOI : 10.1016/j.apenergy.2011.12.086

J. Morales, A. Conejo, and J. Perez-ruiz, Short-term trading for a wind power producer, Power Systems, IEEE Transactions on, pp.25-554, 2010.

O. Grothe and J. Schnieders, Spatial dependence in wind and optimal wind power allocation: A copula-based analysis, Energy Policy, vol.39, issue.9, p.4754, 2011.
DOI : 10.1016/j.enpol.2011.06.052

J. Lin, Y. Zhang-sun, L. Cheng, and W. Zhong-gao, Assessment of the power reduction of wind farms under extreme wind condition by a high resolution simulation model, Applied Energy, vol.96, 2011.
DOI : 10.1016/j.apenergy.2011.10.028

D. Pudjianto, C. Ramsay, and G. Strbac, Virtual power plant and system integration of distributed energy resources, IET Renewable Power Generation, vol.1, issue.1, p.16, 2007.
DOI : 10.1049/iet-rpg:20060023

L. Frias, U. Irigoyen, E. Pascal, E. Cantero, Y. Loureiro et al., Functional data analysis applied to the problem of wind farm aggregation, Proc. of the European Wind Energy Conference

A. Saltelli and S. Tarantola, On the Relative Importance of Input Factors in Mathematical Models, Journal of the American Statistical Association, vol.97, issue.459, p.702709, 2002.
DOI : 10.1198/016214502388618447

A. Liaw and M. Wiener, Classication and regression by randomforest, p.1822, 2002.

R. Development and C. Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, 2011.

J. Matevosyan and L. Soder, Minimization of imbalance cost trading wind power on the short-term power market, Power Systems, IEEE Transactions on, vol.21, issue.1396, p.1404, 2006.

L. Baringo and A. Conejo, Wind power investment within a market environment, Applied Energy, vol.88, issue.9, p.3247, 2011.
DOI : 10.1016/j.apenergy.2011.03.023

C. Ruiz and A. Conejo, Pool strategy of a producer with endogenous formation of locational marginal prices, Power Systems, IEEE Transactions on, vol.24, issue.1855, p.1866, 2009.

A. Tindal, K. Harman, C. Johnson, A. Schwarz, A. Garrad et al., Hassan Validation of the GH energy and uncertainty predictions by comparison to actual production, Proc. of the AWEA Wind Resource and Project Energy Assessment Workshop, 2007.