G. Andersson, P. Donalek, R. Farmer, N. Hatziargyriou, I. Kamwa et al., Causes of the 2003 major grid blackouts in North America Europe, and recommended means to improve system dynamic performance, IEEE Trans. Power Syst, vol.20, pp.1922-1928, 2005.

J. Antonanzas, N. Osorio, R. Escobar, R. Urraca, F. J. Martinez-de-pison et al., Review of photovoltaic power forecasting, Sol. Energy, 2016.

V. Badescu, C. A. Gueymard, S. Cheval, C. Oprea, M. Baciu et al., Accuracy analysis for fifty-four clear-sky solar radiation models using routine hourly global irradiance measurements in Romania, Renew. Energy, vol.55, pp.85-103, 2013.

J. Badosa, J. Wood, P. Blanc, C. N. Long, L. Vuilleumier et al., Solar irradiances measured using SPN1 radiometers: Uncertainties and clues for development, Atmos. Meas. Tech, vol.7, pp.4267-4283, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01112619

M. Bengulescu, Analyse temps-fréquence des données de rayonnement solaire reçu au sol, 2017.

D. Bernecker, C. Riess, E. Angelopoulou, and J. Hornegger, Continuous short-term irradiance forecasts using sky images, Sol. Energy, vol.110, pp.303-315, 2014.

C. Bertin, S. Cros, L. Saint-antonin, and N. Schmutz, Prediction of optical communication link availability: real-time observation of cloud patterns using a ground-based thermal infrared camera, in: Optics in Atmospheric Propagation and Adaptive Systems XVIII, p.96410, 2015.

H. Beyer, G. Heilscher, and S. Bofinger, A robust model for the MPP performance of different types of PV-modules applied for the performance check of grid connected systems, Eurosun. Freibg, 2004.

H. Beyer, J. P. Martinez, M. Suri, J. Torres, E. Lorenz et al., Report on Benchmarking of Radiation Products, 2009.

M. J. Black and P. Anandan, The robust estimation of multiple motions: Parametric and piecewise-smooth flow fields, Comput. Vis. Image Underst, vol.63, pp.75-104, 1996.

P. Blanc, B. Espinar, N. Geuder, C. Gueymard, R. Meyer et al., Direct normal irradiance related definitions and applications: The circumsolar issue, Sol. Energy, vol.110, pp.561-577, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01084806

P. Blanc, P. Massip, A. Kazantzidis, P. Tzoumanikas, P. Kuhn et al., Short-term forecasting of high resolution local DNI maps with multiple fish-eye cameras in stereoscopic mode, AIP Conference Proceedings, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01449128

P. Blanc, J. Remund, and L. Vallance, 6 -Short-term solar power forecasting based on satellite images, Renewable Energy Forecasting, pp.179-198, 2017.

P. Blanc and L. Wald, The SG2 algorithm for a fast and accurate computation of the position of the Sun for multi-decadal time period, Sol. Energy, vol.86, pp.3072-3083, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00725987

B. Bletterie and T. Pfajfar, Impact of Photovoltaic generation on voltage variationshow stochastic is PV, CIRED 19th Int. Conf. Electr. Distrib, pp.21-24, 2007.

J. F. Blinn, A Generalization of Algebraic Surface Drawing, ACM Trans. Graph, vol.1, pp.235-256, 1982.

S. Boughorbel, F. Jarray, and M. El-anbari, Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric, PLoS One, vol.12, 2017.

E. H. Bristol, Swinging door trending: adaptive trend recording, Proc. ISA Natl. Conf. 45, pp.749-753, 1990.

D. Buie, A. G. Monger, and C. J. Dey, Sunshape distributions for terrestrial solar simulations, Sol. Energy, vol.74, pp.113-122, 2003.

J. Calbó, C. N. Long, J. A. González, J. Augustine, and A. Mccomiskey, The thin border between cloud and aerosol: Sensitivity of several ground based observation techniques, Atmos. Res, vol.196, pp.248-260, 2017.

G. Campbell, J. Purdom, and C. V. Beyond, Asynchronous stereo height and motion estimation from multiple satellite images, Spie, vol.2812, pp.95-110, 1996.

G. G. Campbell, Asynchronous stereo height and motion analysis: applications, 1998.

G. G. Campbell and K. Holmlund, Geometric cloud heights from Meteosat, Int. J. Remote Sens, vol.25, pp.4505-4519, 2004.

C. Cany, Interactions entre énergie nucléaire et énergies renouvelables variables dans la transition énergétique en France : adaptations du parc électrique vers plus de flexibilité, 2017.

R. Chauvin, Évaluation de la ressource solaire pour la gestion optimisée de centrales CSP, 2016.

R. Chauvin, J. Nou, S. Thil, and S. Grieu, Modelling the clear-sky intensity distribution using a sky imager, Sol. Energy, vol.119, pp.1-17, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01273096

H. Y. Cheng, Hybrid solar irradiance now-casting by fusing Kalman filter and regressor, Renew. Energy, vol.91, pp.434-441, 2016.

G. Chicco, V. Cocina, P. Di-leo, F. Spertino, and A. Massi-pavan, Error assessment of solar irradiance forecasts and AC power from energy conversion model in gridConnected photovoltaic systems, Energies, vol.9, 2016.

C. W. Chow, B. Urquhart, M. Lave, A. Dominguez, J. Kleissl et al., Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed, Sol. Energy, vol.85, pp.2881-2893, 2011.

Y. Chu, H. T. Pedro, M. Li, and C. F. Coimbra, Real-time forecasting of solar irradiance ramps with smart image processing, Sol. Energy, vol.114, pp.91-104, 2015.

P. Crispel and G. Roberts, All-sky photogrammetry techniques to georeference a cloud field, Atmos. Meas. Tech, vol.11, pp.593-609, 2018.

S. Cros, O. Liandrat, N. Sebastien, and N. Schmutz, Extracting cloud motion vectors from satellite images for solar power forecasting, International Geoscience and Remote Sensing Symposium (IGARSS), pp.4123-4126, 2014.
DOI : 10.1109/igarss.2014.6947394

S. Cros, N. Sébastien, O. Liandrat, and N. Schmutz, Cloud pattern prediction from geostationary meteorological satellite images for solar energy forecasting, p.924202, 2014.
DOI : 10.1117/12.2066853

S. Cros, M. Turpin, C. Lallemand, N. Sébastien, and N. Schmutz, Soleksat: A flexible solar irradiance forecasting tool using satellite images and geographic webservices, in: 31st European Photovoltaic Solar Energy Conference and Exhibition, pp.2128-2132, 2015.

M. Cui, J. Zhang, C. Feng, A. R. Florita, Y. Sun et al., Characterizing and analyzing ramping events in wind power, solar power, load, and netload, Renew. Energy, vol.111, pp.227-244, 2017.
DOI : 10.1016/j.renene.2017.04.005

M. Cui, J. Zhang, A. R. Florita, B. M. Hodge, D. Ke et al., An optimized swinging door algorithm for identifying wind ramping events, IEEE Trans. Sustain. Energy, vol.7, pp.150-162, 2016.
DOI : 10.1109/tste.2015.2477244

M. Cui, J. Zhang, A. R. Florita, B. M. Hodge, D. Ke et al., An optimized swinging door algorithm for wind power ramp event detection, IEEE Power Energy Soc. Gen. Meet, 2015.
DOI : 10.1109/pesgm.2015.7286272

N. Cutler, M. Kay, K. Jacka, and T. S. Nielsen, Detecting, categorizing and forecasting large ramps in wind farm power output using meteorological observations and WPPT, Wind Energy, vol.10, pp.453-470, 2007.
DOI : 10.1002/we.235

J. G. Da-silva-fonseca, T. Oozeki, H. Ohtake, K. I. Shimose, T. Takashima et al., Forecasting regional photovoltaic power generation -A comparison of strategies to obtain one-day-ahead data, Energy Procedia, pp.1337-1345, 2014.

R. Dambreville, Prévision du rayonnement solaire global par télédétection pour la gestion de la production d'énergie photovoltaïque, 2014.

T. Delta-devices, Sunshine Pyranometer The new SPN1 measures Global ( Total ) and Diffuse radiation and Sunshine Duration -in one instrument, 2011.

M. Derrien and H. Le-gléau, MSG/SEVIRI cloud mask and type from SAFNWC, Int. J. Remote Sens, vol.26, pp.4707-4732, 2005.
DOI : 10.1080/01431160500166128

H. M. Diagne, M. David, P. Lauret, and J. Boland, Solar irradiation forecasting: state-of-the-art and proposition for future developments for small-scale insular grids, World Renew. Energy Forum, pp.1-8, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00918150

M. Diagne, M. David, P. Lauret, J. Boland, and N. Schmutz, Review of solar irradiance forecasting methods and a proposition for small-scale insular grids, Renew. Sustain. Energy Rev, 2013.
URL : https://hal.archives-ouvertes.fr/hal-01090087

Y. Dobashi, T. Nishita, H. Yamashita, and T. Okita, Using metaballs to modeling and animate clouds from satellite images, Vis. Comput, vol.15, pp.471-482, 1999.
DOI : 10.1007/s003710050193

P. Du, R. Baldick, and A. Tuohy, Integration of Large-Scale Renewable Energy into Bulk Power Systems, 2017.

E. Ela, V. Diakov, E. Ibanez, and M. Heaney, Impacts of Variability and Uncertainty in Solar Photovoltaic Generation at Multiple Timescales, Natl. Renew. Energy Lab, 2013.

N. A. Engerer and F. P. Mills, Validating nine clear sky radiation models in Australia, Sol. Energy, vol.120, pp.9-24, 2015.
DOI : 10.1016/j.solener.2015.06.044

H. Escrig, F. J. Batlles, J. Alonso, F. M. Baena, J. L. Bosch et al., Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast, Energy, vol.55, pp.853-859, 2013.
DOI : 10.1016/j.energy.2013.01.054

B. Espinar, L. Ramírez, A. Drews, H. G. Beyer, L. F. Zarzalejo et al., Analysis of different comparison parameters applied to solar radiation data from satellite and German radiometric stations, Sol. Energy, vol.83, pp.118-125, 2009.

K. F. Evans, The Spherical Harmonics Discrete Ordinate Method for ThreeDimensional Atmospheric Radiative Transfer, Journal of the Atmospheric Sciences, 1998.
DOI : 10.1175/1520-0469(1998)055<0429:tshdom>2.0.co;2

C. Ferreira, J. Gama, L. Matias, A. Botterud, and J. Wang, A survey on wind power ramp forecasting, Argonne Natl. Lab, 2011.
DOI : 10.2172/1008309

URL : https://digital.library.unt.edu/ark:/67531/metadc832671/m2/1/high_res_d/1008309.pdf

A. Florita, B. M. Hodge, and K. Orwig, Identifying wind and solar ramping events, IEEE Green Technol. Conf, pp.147-152, 2013.
DOI : 10.1109/greentech.2013.30

R. A. Frey, S. A. Ackerman, Y. Liu, K. I. Strabala, H. Zhang et al., Cloud detection with MODIS. Part I: Improvements in the MODIS cloud mask for Collection 5, J. Atmos. Ocean. Technol, vol.25, pp.1057-1072, 2008.

L. Frías-paredes, F. Mallor, M. Gastón-romeo, and T. León, Assessing energy forecasting inaccuracy by simultaneously considering temporal and absolute errors, Energy Convers. Manag, 2017.

L. Frías-paredes, F. Mallor, T. León, and M. Gastón-romeo, Introducing the Temporal Distortion Index to perform a bidimensional analysis of renewable energy forecast, Energy, vol.94, pp.180-194, 2016.

C. L. Fu and H. Y. Cheng, Predicting solar irradiance with all-sky image features via regression, Sol. Energy, vol.97, pp.537-550, 2013.
DOI : 10.1016/j.solener.2013.09.016

M. Gastón-romeo, T. Leon, F. Mallor, and L. Ramírez-santigosa, A Morphological Clustering Method for daily solar radiation curves, Sol. Energy, vol.85, pp.1824-1836, 2011.

C. Gauchet, P. Blanc, B. Espinar, B. Charbonnier, and D. Demengel, Surface solar irradiance estimation with low-cost fish-eye camera. COST WIRE Work, Remote Sens. Meas. Renew. Energy, vol.4, p.pp, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00741620

J. L. Gaumet, J. C. Heinrich, M. Cluzeau, P. Pierrard, and J. Prieur, Cloud-base height measurements with a single-pulse erbium-glass laser ceilometer, J. Atmos. Ocean. Technol, vol.15, pp.37-45, 1998.
DOI : 10.1175/1520-0426(1998)015<0037:cbhmwa>2.0.co;2

. Gcos, Implementation plan for the global observing system for climate in support of the UNFCCC, World Meteorol. Organ, vol.138, p.180, 2010.

M. S. Ghonima, B. Urquhart, C. W. Chow, J. E. Shields, A. Cazorla et al., A method for cloud detection and opacity classification based on ground based sky imagery, Atmos. Meas. Tech, vol.5, pp.2881-2892, 2012.
DOI : 10.5194/amtd-5-4535-2012

C. A. Gueymard, Cloud and albedo enhancement impacts on solar irradiance using high-frequency measurements from thermopile and photodiode radiometers. Part 1: Impacts on global horizontal irradiance, Sol. Energy, vol.153, pp.755-765, 2017.
DOI : 10.1016/j.solener.2017.05.004

C. A. Gueymard, Clear-sky irradiance predictions for solar resource mapping and large-scale applications: Improved validation methodology and detailed performance analysis of 18 broadband radiative models, Sol. Energy, vol.86, pp.2145-2169, 2012.

S. Harrouni, Fractal Classification of Typical Meteorological Days from Global Solar Irradiance: Application to Five Sites of Different Climates, in: Modeling Solar Radiation at the Earth's Surface, pp.29-55, 2008.

S. Harrouni, A. Guessoum, and A. Maafi, Classification of daily solar irradiation by fractional analysis of 10-min-means of solar irradiance, Theor. Appl. Climatol, vol.80, pp.27-36, 2005.

A. Heinle, A. Macke, and A. Srivastav, Automatic cloud classification of whole sky images, Atmos. Meas. Tech, vol.3, pp.557-567, 2010.
DOI : 10.5194/amtd-3-269-2010

URL : http://oceanrep.geomar.de/13359/1/Heinle.pdf

T. E. Hoff and R. Perez, 01 . Modeling PV fleet output variability, Sol. Energy, vol.86, pp.177-2189

T. E. Hoff and R. Perez, Quantifying PV power Output Variability, Sol. Energy, vol.84, pp.1782-1793, 2010.
DOI : 10.1016/j.solener.2010.07.003

T. E. Hoff, R. Perez, J. Kleissl, D. Renne, and J. Stein, Reporting of irradiance modeling relative prediction errors, Prog. Photovoltaics Res. Appl, vol.21, pp.1514-1519, 2013.
DOI : 10.1002/pip.2225

Á. Horváth and R. Davies, Simultaneous retrieval of cloud motion and height from polar-orbiter multiangle measurements, Geophys. Res. Lett, vol.28, pp.2915-2918, 2001.

H. Huang, S. Yoo, D. Yu, D. Huang, and H. Qin, Correlation and local feature based cloud motion estimation, Proc. Twelfth Int. Work. Multimed. Data Min. 1-9, 2012.
DOI : 10.1145/2343862.2343863

P. Ineichen, Validation of models that estimate the clear sky global and beam solar irradiance, Sol. Energy, vol.132, pp.332-344, 2016.

P. Ineichen, Conversion function between the Linke turbidity and the atmospheric water vapor and aerosol content, Sol. Energy, vol.82, pp.1095-1097, 2008.

P. Ineichen, Comparison of eight clear sky broadband models against 16 independent data banks, Sol. Energy, vol.80, pp.468-478, 2006.
DOI : 10.1016/j.solener.2005.04.018

URL : https://archive-ouverte.unige.ch/unige:17213/ATTACHMENT01

R. H. Inman, H. T. Pedro, and C. F. Coimbra, Solar forecasting methods for renewable energy integration, Prog. Energy Combust. Sci, vol.39, pp.535-576, 2013.
DOI : 10.1016/j.pecs.2013.06.002

, Key world energy statistics, 2017.

, Solar Photovoltaic Energy, Technology Roadmap. International energy agency report, p.763, 2014.

A. Jarvis, H. I. Reuter, A. Nelson, and E. Guevara, Hole-filled seamless SRTM data V4, Int. Cent. Trop. Agric, 2008.

G. Jeanjean and B. De-metz-noblat, Stabilité dynamique des réseaux électriques industriels, Cah. Tech, vol.185, 1997.

R. W. Johnson, W. S. Hering, and J. E. Shields, Automated visibility & cloud cover measurements with a solid-state imaging system, 1989.

J. W. Kaiser, V. Peuch, A. Benedetti, O. J. Boucher, E. Holzer-popp et al., The pre-operational GMES atmospheric service in MACC-II and its potential usage of SENTINEL-3 observations, ESA Spec. Publ. SP, vol.708, pp.4-7, 2012.

C. Kamath, Understanding wind ramp events through analysis of historical data, IEEE PES Transm. Distrib. Conf. Expo. Smart Solut. a Chang. World, 2010.

A. Kaur, L. Nonnenmacher, H. T. Pedro, and C. F. Coimbra, Benefits of solar forecasting for energy imbalance markets, Renew. Energy, vol.86, pp.819-830, 2016.

A. Kazantzidis, P. Tzoumanikas, A. F. Bais, S. Fotopoulos, and G. Economou, Cloud detection and classification with the use of whole-sky ground-based images, Atmos. Res, vol.113, pp.80-88, 2012.

A. Kazantzidis, P. Tzoumanikas, P. Blanc, P. Massip, S. Wilbert et al., Short-term forecasting based on all-sky cameras, Renewable Energy Forecasting: From Models to Applications, pp.153-178, 2017.
DOI : 10.1016/b978-0-08-100504-0.00005-6

J. Kleissl, Solar energy forecasting and resource assessment, 2013.

I. Koren, L. A. Remer, Y. J. Kaufman, Y. Rudich, and J. V. Martins, On the twilight zone between clouds and aerosols, Geophys. Res. Lett, vol.34, 2007.

V. Kostylev and A. Pavlovski, Solar Power Forecasting Performance -Towards Industry Standards, in: 1st International Workshop on the Integration of Solar Power into Power Systems, 2011.

S. Kudo, Characterising collective ramp events of distributed photovoltaic systems in, 2015.

P. Kuhn, S. Wilbert, C. Prahl, D. Schüler, T. Haase et al., Shadow camera system for the generation of solar irradiance maps, Sol. Energy, vol.157, pp.157-170, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01577222

, Photovoltaic Specialist Conference, PVSC 2015

A. Maafi and S. Harrouni, Preliminary results of the fractal classification of daily solar irradiances, Sol. Energy, vol.75, pp.53-61, 2003.

R. Macrae and S. Dixon, Accurate Real-time Windowed Time Warping, pp.423-428, 2010.

S. E. Mahani, X. Gao, S. Sorooshian, and B. Imam, Estimating cloud top height and spatial displacement from scan-synchronous GOES images using simplified IR-based stereoscopic analysis, J. Geophys. Res. Atmos, vol.105, pp.15597-15608, 2000.
DOI : 10.1029/2000jd900064

URL : https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000JD900064

R. Marquez and C. F. Coimbra, Intra-hour DNI forecasting based on cloud tracking image analysis, Sol. Energy, vol.91, pp.327-336, 2013.
DOI : 10.1016/j.solener.2012.09.018

R. Marquez and C. F. Coimbra, Proposed Metric for Evaluation of Solar Forecasting Models, J. Sol. Energy Eng, vol.135, p.11016, 2012.

R. Marquez, H. T. Pedro, and C. F. Coimbra, Hybrid solar forecasting method uses satellite imaging and ground telemetry as inputs to, ANNs. Sol. Energy, vol.92, pp.176-188, 2013.
DOI : 10.1016/j.solener.2013.02.023

P. Mathiesen and J. Kleissl, Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States, Sol. Energy, vol.85, pp.967-977, 2011.

B. W. Matthews, Comparison of the predicted and observed secondary structure of T4 phage lysozyme, pp.442-451, 1975.

B. Mayer and A. Kylling, Technical note: The libRadtran software package for radiative transfer calculations -description and examples of use, Atmos. Chem. Phys, vol.5, pp.1855-1877, 2005.
URL : https://hal.archives-ouvertes.fr/hal-00295701

F. Mejia, Remote sensing of clouds for solar forecasting applications, 2017.

A. Mellit and A. M. Pavan, A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy. Sol. Energy, vol.84, pp.807-821, 2010.

W. P. Menzel, Cloud Tracking with Satellite Imagery: From the Pioneering Work of Ted Fujita to the Present, Bull. Am. Meteorol. Soc, vol.82, pp.33-47, 2001.

A. Mills, Understanding Variability and Uncertainty of Photovoltaics for Integration with the Electric Power System, Electr. J, 2010.

A. Mills and R. Wiser, Implications of Wide-Area Geographic Diversity for ShortTerm Variability of Solar Power, 2010.

. Ministère-de-l&apos;écologie, Chiffres clés du climat -France et monde. Serv. l'observation des Stat, vol.52, p.17

J. Morcrette, H. Barker, J. Cole, M. Iacono, and R. Pincus, Impact of a new radiation package, McRad, in the ECMWF integrated forecasting system, Mon. Weather Rev, vol.136, pp.4773-4798, 2008.

J. Müller, G. Fowler, K. Dammann, C. Rogers, Y. Buhler et al., MSG Level 1.5 Image Data Format Description, 2013.

D. Oberländer, C. Prahl, S. Wilbert, S. Müller, B. Stanicki et al., Cloud shadow maps from whole sky imagers and voxel carving, International Conference Energy & Meteorology, 2015.

A. Ohmura, E. G. Dutton, B. Forgan, C. Fröhlich, H. Gilgen et al., Baseline Surface Radiation Network (BSRN/WCRP): New Precision Radiometry for Climate Research, Bull. Am. Meteorol. Soc, vol.79, pp.2115-2136, 1998.
DOI : 10.1175/1520-0477(1998)079<2115:bsrnbw>2.0.co;2

URL : http://journals.ametsoc.org/doi/pdf/10.1175/1520-0477%281998%29079%3C2115%3ABSRNBW%3E2.0.CO%3B2

N. Otsu, A threshold selection method from gray-level histograms, Automatica, 1975.
DOI : 10.1109/tsmc.1979.4310076

A. Oumbe, Z. Qu, P. Blanc, M. Lefèvre, L. Wald et al., Decoupling the effects of clear atmosphere and clouds to simplify calculations of the broadband solar irradiance at ground level, Geosci. Model Dev, vol.7, pp.1661-1669, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01061973

S. Pelland, J. Remund, J. Kleissl, T. Oozeki, K. Brabandere et al., Photovoltaic and Solar Forecasting: State of the Art, Int. Energy Agency Photovolt. Power Syst. Program. Rep. IEA PVPS, 2013.

Z. Peng, D. Yu, D. Huang, J. Heiser, S. Yoo et al., 3D cloud detection and tracking system for solar forecast using multiple sky imagers, Sol. Energy, vol.118, pp.496-519, 2015.
DOI : 10.1016/j.solener.2015.05.037

URL : https://manuscript.elsevier.com/S0038092X15002972/pdf/S0038092X15002972.pdf

R. Perez, M. David, T. E. Hoff, M. Jamaly, S. Kivalov et al., Spatial and Temporal Variability of Solar Energy. Found. Trends® Renew. Energy, vol.1, pp.1-44, 2016.

R. Perez, S. Kivalov, J. Schlemmer, K. Hemker, D. Renné et al., Validation of short and medium term operational solar radiation forecasts in the US, Sol. Energy, vol.84, pp.2161-2172, 2010.

R. Perez, S. Kivalov, J. Schlemmer, K. J. Hemker, and A. Zelenka, Improving the performance of satellite-to-irradiance models using the satellite's infrared sensors, 2010.

, Proc. Am. Sol. Energy Soc. Annu. Conf

R. Perez, E. Lorenz, S. Pelland, M. Beauharnois, G. Van-knowe et al., Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe. Sol. Energy, vol.94, pp.305-326, 2013.

C. F. Peruchena and A. F. Amores, Uncertainty in monthly GHI due to daily data gaps, Sol. Energy, vol.157, pp.827-829, 2017.

V. Peuch, L. Rouil, L. Tarrason, and H. Elbern, Towards European-scale Air Quality operational services for GMES Atmosphere, 9th EMS Annu. Meet. 9th Eur, 2009.

G. Pfister, R. L. Mckenzie, J. B. Liley, A. Thomas, B. W. Forgan et al., Cloud Coverage Based on All-Sky Imaging and Its Impact on Surface Solar Irradiance, J. Appl. Meteorol, vol.42, pp.1421-1434, 2003.

S. Platnick, M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum et al., The MODIS cloud products: Algorithms and examples from terra, IEEE Trans. Geosci. Remote Sens, vol.41, pp.459-472, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00820985

Z. Qu, A. Oumbe, P. Blanc, B. Espinar, G. Gesell et al., Fast radiative transfer parameterisation for assessing the surface solar irradiance: The Heliosat-4 method, Energy Meteorol, vol.26, pp.33-57, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01512589

S. Quesada-ruiz, Y. Chu, J. Tovar-pescador, H. T. Pedro, and C. F. Coimbra, Cloud-tracking methodology for intra-hour DNI forecasting, Sol. Energy, vol.102, pp.267-275, 2014.

S. Ransome and P. Funtan, Why hourly averaged measurement data is insufficient to model PV system performance accurately, 20th European Photovoltaic Solar Energy Conference, 2005.

J. Remund, L. Wald, M. Lefèvre, T. Ranchin, and J. Page, Worldwide Linke Turbdidity Information, p.41, 2003.

, REN21, 2017. Renewables 2017: global status report, Renewable and Sustainable Energy Reviews

M. J. Reno and C. W. Hansen, Identification of periods of clear sky irradiance in time series of GHI measurements, Renew. Energy, vol.90, pp.520-531, 2016.

C. Rigollier, M. Lefèvre, and L. Wald, The method Heliosat-2 for deriving shortwave solar radiation from satellite images, Sol. Energy, vol.77, pp.159-169, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00361364

R. Roebeling, A. Feijt, P. Stammes, . D20, A. Roesch et al., Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17, J. Geophys. Res. Atmos, vol.111, pp.339-354, 2006.

M. Roser and A. Geiger, Video-based raindrop detection for improved image registration, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pp.570-577, 2009.

G. Roy, S. Hayman, and W. Julian, Sky analysis from CCD images: cloud cover, Light. Res. Technol, vol.33, pp.211-221, 2001.

J. A. Ruiz-arias, H. Alsamamra, J. Tovar-pescador, and D. Pozo-vázquez, Proposal of a regressive model for the hourly diffuse solar radiation under all sky conditions, Energy Convers. Manag, vol.51, pp.881-893, 2010.

Y. Saint-drenan, L. Wald, T. Ranchin, L. Dubus, and A. Troccoli, An approach for the estimation of the aggregated photovoltaic power generated in several European countries from meteorological data, Adv. Sci. Res, vol.15, pp.51-62, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01782565

H. Sakoe and S. Chiba, Dynamic programming algorithm optimization for spoken word recognition, IEEE Trans. Acoust, vol.26, pp.43-49, 1978.

S. Sayeef, S. Heslop, D. Cornforth, T. Moore, S. Percy et al., 01 . Solar intermittency: Australia's clean energy challenge

D. Scaramuzza, A. Martinelli, and R. Siegwart, A toolbox for easily calibrating omnidirectional cameras, IEEE International Conference on Intelligent Robots and Systems. IEEE/RSJ, pp.5695-5701, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00359941

M. Schroedter-homscheidt, The Copernicus Atmosphere Monitoring Service (CAMS) Radiation Service in a nutshell, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01386187

G. Seiz, Ground-and satellite-based multi-view photogrammetric determination of 3D cloud geometry, 2003.

G. Seiz, S. Tjemkes, and P. Watts, Multiview cloud-top height and wind retrieval with photogrammetric methods: Application to Meteosat-8 HRV observations, J. Appl. Meteorol. Climatol, vol.46, pp.1182-1195, 2007.

M. Sengupta, A. Habte, S. Kurtz, A. Dobos, S. Wilbert et al., Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01184753

J. Shields, M. Karr, A. Burden, R. Johnson, V. Mikuls et al., , 2009.

J. E. Shields, M. E. Karr, A. R. Burden, V. W. Mikuls, J. R. Streeter et al., Whole Sky Imager Characterization of Sky Obscuration by Clouds for the Starfire Optical Range 102, 2010.

M. S. Stengel, A. K. Kniffka, J. F. Meirink, M. L. Lockhoff, J. T. Tan et al., CLAAS: The CM SAF cloud property data set using SEVIRI, Atmos. Chem. Phys, vol.14, pp.4297-4311, 2014.

N. Stern, Stern Review Report on the Economics of Climate Change, 2006.

R. Tapakis and A. G. Charalambides, Equipment and methodologies for cloud detection and classification: A review, Sol. Energy, vol.95, 2013.

, The Paris Agreement, 2015.

G. M. Tina, S. De-fiore, and C. Ventura, Analysis of forecast errors for irradiance on the horizontal plane, Energy Convers. Manag, vol.64, pp.533-540, 2012.

L. Vallance, B. Charbonnier, N. Paul, S. Dubost, and P. Blanc, Towards a standardized procedure to assess solar forecast accuracy: A new ramp and time alignment metric, Sol. Energy, vol.150, pp.408-422, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01522453

M. Van-der-laan, K. Pollard, and J. Bryan, A new partitioning around medoids algorithm, J. Stat. Comput. Simul, vol.73, pp.575-584, 2003.

C. Vernay, P. Blanc, and S. Pitaval, Characterizing measurements campaigns for an innovative calibration approach of the global horizontal irradiation estimated by HelioClim-3, Renew. Energy, vol.57, pp.339-347, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00799172

C. Voyant, Prédiction de séries temporelles de rayonnement solaire global et de production d'énergie photovoltaïque à partir de réseaux de neurones artificiels 6134, p.257, 2011.

L. Vuilleumier, C. Félix, F. Vignola, P. Blanc, J. Badosa et al., Performance evaluation of radiation sensors for the solar energy sector, Meteorol. Zeitschrift, vol.26, pp.485-505, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01449199

L. Wald, Some terms of reference in data fusion, IEEE Trans. Geosci. Remote Sens, vol.37, pp.1190-1193, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00356150

G. Wang, B. Kurtz, and J. Kleissl, Cloud base height from sky imager and cloud speed sensor, Sol. Energy, vol.131, pp.208-221, 2016.

P. Wood-bradley, J. Zapata, and J. Pye, Cloud tracking with optical flow for shortterm solar forecasting. 50Th Conf, Aust. Sol. Energy Soc, pp.2-7, 2012.

M. Yamashita, Cloud cover estimation using multitemporal hemisphere imageries, Proc. XXth Congr. Int. Soc. Photogramm. Remote Sens, pp.818-821, 2004.

D. Yang, J. Kleissl, C. A. Gueymard, H. T. Pedro, and C. F. Coimbra, History and trends in solar irradiance and PV power forecasting: A preliminary assessment and review using text mining, Sol. Energy, vol.168, pp.60-101, 2018.

D. Yang, H. Quan, V. R. Disfani, and L. Liu, Reconciling solar forecasts: Geographical hierarchy, Sol. Energy, vol.146, pp.276-286, 2017.

D. Yang, H. Quan, V. R. Disfani, and C. D. Rodríguez-gallegos, Reconciling solar forecasts: Temporal hierarchy, Sol. Energy, vol.158, pp.332-346, 2017.

D. Yang, W. M. Walsh, D. Zibo, P. Jirutitijaroen, and T. G. Reindl, Block matching algorithms: Their applications and limitations in solar irradiance forecasting, Energy Procedia, vol.33, pp.335-342, 2013.

J. Yang, W. Lu, Y. Ma, and W. Yao, An automated cirrus cloud detection method for a ground-based cloud image, J. Atmos. Ocean. Technol, vol.29, pp.527-537, 2012.

J. Yang, Q. Min, W. Lu, Y. Ma, W. Yao et al., A total sky cloud detection method using real clear sky background, Atmos. Meas. Tech, vol.9, 2016.

S. You and R. Tan, Adherent raindrops detection and removal in video, Computer Vision and Pattern Recognition (CVPR), pp.2-3, 2013.

S. Younes, R. Claywell, and T. Muneer, Quality control of solar radiation data: Present status and proposed new approaches. Energy, vol.30, pp.1533-1549, 2005.

L. A. Zadeh, Fuzzy logic and approximate reasoning, vol.30, 1975.

J. Zhang, A. Florita, B. Hodge, and J. Freedman, Ramp forecasting performance from improved short-term wind power forecasting, Proceedings of the ASME Design Engineering Technical Conference, 2014.

J. Zhang, B. Hodge, A. Florita, S. Lu, H. F. Hamann et al., Metrics for Evaluating the Accuracy of Solar Power Forecasting, Work. Integr. Sol. Power into Power Syst, vol.17436, pp.1-10, 2013.