J. Bézian, Un nouveau concept de centrale solaire thermodynamique basé sur un récepteur à lit fluidisé, 13èmes Journées Internationales de Thermique, 2007.

B. Grange, « Modélisation et dimensionnement d'un récepteur solaire à air pressurisé pour le projet PEGASE, Thèse de doct, p.2013

A. Colleoni, « Intensification des transferts de chaleur en régime turbulent pour le développement d'un récepteur solaire surfacique à haute température en céramique, Thèse de doct, 2013.

I. Hischier, Heat Transfer Analysis of a Novel Pressurized Air Receiver for Concentrated Solar Power via Combined Cycles, Journal of Thermal Science and Engineering Applications, vol.1, issue.4, pp.41002-41008, 2009.
DOI : 10.1115/1.4001259

A. Bounaceur, « Interaction lit fluidisé de particules solides-rayonnement solaire concentré pour la mise au point d'un procédé de chauffage de gaz à plus de 1000 K, Thèse de doct. École Nationale Supérieure des Mines de Paris, p.6, 2009.

G. Baud, « Conception de récepteurs solaires à lit fluidisé sous flux radiatif concentré, Thèse de doct. Institut National Polytechnique de Toulouse, p.6, 2011.

G. J. Kolb, Power tower technology roadmap and cost reduction plan, pp.2011-2419, 2011.

H. Hasuike, Demonstration of tokyo tech beam-down solar concentration power system in 100kw pilot plant, Proceedings of 15th SolarPACES Conference, 2009.

R. Osuna, PS10 : a 11.0-MW solar tower power plant with saturated steam receiver, Proceedings 12th SolarPACES International Symposium. Sous la dir. de C. Ramos et J. Huacuz, p.78, 2004.

J. De and L. Torre, « Calculs de sensibilités par la méthode de Monte Carlo pour la conception de procédés à énergie solaire concentrée, Thèse de doct. Institut National Polytechnique de Toulouse, pp.18-21, 2011.

J. De and L. Torre, Monte Carlo advances and concentrated solar applications, Solar Energy, vol.103, pp.653-681, 2014.

P. Garcia, A. Ferrière, and J. J. Bézian, Codes for solar flux calculation dedicated to central receiver system applications: A comparative review, Solar Energy, vol.82, issue.3, pp.189-197, 2008.
DOI : 10.1016/j.solener.2007.08.004

C. K. Ho, Software and Codes for Analysis of Concentrating Solar Power Technologies, Rapp. tech, p.15, 2008.
DOI : 10.2172/946571

P. Leary and J. Hankins, User's guide for MIRVAL : a computer code for comparing designs of heliostat-receiver optics for central receiver solar power plants, Rapp. tech. Sandia Labs, pp.1979-1997
DOI : 10.2172/6371450

T. Wendelin, SolTRACE: A New Optical Modeling Tool for Concentrating Solar Optics, Solar Energy, p.18, 2003.
DOI : 10.1115/ISEC2003-44090

M. J. Blanco, J. M. Amieva, and A. Mancilla, The Tonatiuh Software Development Project: An Open Source Approach to the Simulation of Solar Concentrating Systems, Computers and Information in Engineering, pp.157-164, 2005.
DOI : 10.1115/IMECE2005-81859

]. J. Roccia, Tracing Monte-Carlo software for solar concentrating facilities, Journal of Physics : Conference Series. T. 369. 1, pp.12029-12048, 2012.

B. Belhomme, A New Fast Ray Tracing Tool for High-Precision Simulation of Heliostat Fields, Journal of Solar Energy Engineering, vol.131, issue.3, pp.31002-31021, 2009.
DOI : 10.1115/1.3139139

F. J. Collado and J. Guallar, A review of optimized design layouts for solar power tower plants with campo code, Renewable and Sustainable Energy Reviews, vol.20, pp.142-154, 2013.
DOI : 10.1016/j.rser.2012.11.076

E. Leonardi and B. D. Aguanno, CRS4-2: A numerical code for the calculation of the solar power collected in a central receiver system, Energy, vol.36, issue.8, pp.4828-4837, 2011.
DOI : 10.1016/j.energy.2011.05.017

L. Erminia, « Detailed analysis of the solar power collected in a beam-down central receiver system, Solar Energy, vol.862, pp.734-745, 2012.

P. Perez, Algorithmes de synthèse d'image et propriétés spectrales des gaz de combustion : Méthode de Monte-Carlo pour la simulation des transferts radiatifs dans les procédés à haute température, Thèse de doct. Institut National Polytechnique de Toulouse, 2008.

M. Pharr and G. Humphreys, Physically Based Rendering, second edition : from theory to implementation, p.153, 2010.

N. Metropolis and S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, vol.44, issue.247, pp.335-341, 1949.
DOI : 10.1080/01621459.1949.10483310

J. M. Hammersley and D. C. Handscomb, Monte Carlo Methods, Chapman et Hall, p.22, 1969.

W. L. Dunn and J. K. Shultis, Exploring Monte Carlo methods

J. Howell, The Monte Carlo Method in Radiative Heat Transfer, Journal of Heat Transfer, vol.120, issue.3, pp.547-560, 1998.
DOI : 10.1115/1.2824310

G. Rubino, B. Tuffin, . Simulations, M. Méthodes-de, and . Carlo, url : http: //www.techniques-ingenieur.fr/base-documentaire/sciences-fondame ntales -th8 / mathematiques -pour -l -ingenieur -ti052 / simulations -et - methodes, Techniques de l'ingénieur. AF 600. Éditions T.I, pp.1-15, 2007.

J. F. Blinn, Models of light reflection for computer synthesized pictures, ACM SIGGRAPH Computer Graphics, vol.11, issue.2, pp.192-198, 1977.
DOI : 10.1145/965141.563893

I. Reda and A. Andreas, « Solar position algorithm for solar radiation applications, In : Solar Energy, vol.765, pp.577-589, 2004.

G. J. Kolb, Heliostat cost reduction study

F. Lipps and L. Vant-hull, A cellwise method for the optimization of large central receiver systems, Solar Energy, vol.20, issue.6, pp.505-516, 1978.
DOI : 10.1016/0038-092X(78)90067-1

P. K. Falcone, A handbook for solar central receiver design, Rapp. tech. Sandia National Labs, vol.34, p.32, 1986.
DOI : 10.2172/6545992

F. M. Siala and M. E. Elayeb, Mathematical formulation of a graphical method for a no-blocking heliostat field layout, Renewable Energy, vol.23, issue.1, pp.77-92, 2001.
DOI : 10.1016/S0960-1481(00)00159-2

M. Mokhtar, Heliostat field efficiency test of beam down csp pilot plant experimenatal results, Proceedings of 16th SolarPACES Conference, p.32, 2010.

A. Segal, Optimization of heliostat field layout for the beam down optics, pp.116-125

M. Sánchez and M. Romero, Methodology for generation of heliostat field layout in central receiver systems based on yearly normalized energy surfaces, Solar Energy, vol.80, issue.7, pp.861-874, 2006.
DOI : 10.1016/j.solener.2005.05.014

C. J. Noone, M. Torrilhon, and A. Mitsos, Heliostat field optimization: A new computationally efficient model and biomimetic layout, Solar Energy, vol.86, issue.2, pp.792-803, 2012.
DOI : 10.1016/j.solener.2011.12.007

T. Pylkanen, Personnal communication

R. Osuna, PS10 : A 10 MW solar thermal power plant for southern spain, Proceedings of 10th SolarPACES Conference, pp.37-78, 2000.

M. Mustafa, S. Abdelhady, and A. Elweteedy, Analytical Study of an Innovated Solar Power Tower (PS10) in Aswan, International Journal of Energy Engineering, vol.2, issue.6, pp.273-278, 2012.
DOI : 10.5923/j.ijee.20120206.01

R. Osuna, A 10 MW Solar Tower Power Plant for Southern Spain, Proceedings of the 8th International Energy Forum. Sous la dir, pp.37-78, 2000.

M. Romero, R. Buck, and J. E. Pacheco, An Update on Solar Central Receiver Systems, Projects, and Technologies, Journal of solar energy engineering 124, pp.98-108, 2002.
DOI : 10.1115/1.1467921

P. Garcia, A. Ferrière, and J. J. Bézian, Codes for solar flux calculation dedicated to central receiver system applications: A comparative review, Solar Energy, vol.82, issue.3, pp.189-197, 2008.
DOI : 10.1016/j.solener.2007.08.004

W. L. Dunn and J. K. Shultis, Exploring Monte Carlo methods

M. Sánchez and M. Romero, Methodology for generation of heliostat field layout in central receiver systems based on yearly normalized energy surfaces, Solar Energy, vol.80, issue.7, pp.861-874, 2006.
DOI : 10.1016/j.solener.2005.05.014

P. Schwarzbözl, R. Pitz-paal, and M. Schmitz, « Visual HFLCAL -A software tool for layout and optimization of heliostat fields, Proceedings of 15th SolarPACES Conference, p.46, 2009.

P. Gilman, Solar advisor model user guide for version 2.0, p.46, 2008.
DOI : 10.2172/937349

F. J. Collado, Quick evaluation of the annual heliostat field efficiency, Solar Energy, vol.82, issue.4, pp.379-384, 2008.
DOI : 10.1016/j.solener.2007.10.007

R. Osuna, R. Olavarría, and R. R. Morillo, « Construction of a 11MW Solar Thermal Tower Plant in Seville, Spain, Proceeding of 13 th Solar PACES Symposium, pp.48-78, 2006.

O. Farges, Simulation of yearly energy for solar heating systems, Proceedings of 18th SolarPACES Conference, pp.2012-52

R. Osuna, PS10 : a 11.0-MW solar tower power plant with saturated steam receiver, Proceedings 12th SolarPACES International Symposium. Sous la dir. de C. Ramos et J. Huacuz, p.78, 2004.

J. Dauchet, « Analyse radiative des photobioréacteurs, Thèse de doct, pp.134-146

R. Osuna, PS10 : A 10 MW solar thermal power plant for southern spain, Proceedings of 10th SolarPACES Conference, pp.37-78, 2000.

R. Osuna, A 10 MW Solar Tower Power Plant for Southern Spain, Proceedings of the 8th International Energy Forum. Sous la dir, pp.37-78, 2000.

R. Osuna, R. Olavarría, and R. R. Morillo, « Construction of a 11MW Solar Thermal Tower Plant in Seville, Spain, Proceeding of 13 th Solar PACES Symposium, pp.48-78, 2006.

B. D. Ehrhart and D. D. Gill, Evaluation of annual efficiencies of high temperature central receiver concentrated solar power plants with thermal energy storage, Rapp. tech. Sandia National Laboratories (SNL-NM), pp.2013-79

E. Koepf, A novel beam-down, gravity-fed, solar thermochemical receiver/reactor for direct solid particle decomposition: Design, modeling, and experimentation, International Journal of Hydrogen Energy, vol.37, issue.22, p.82, 2012.
DOI : 10.1016/j.ijhydene.2012.08.086

R. Pitz-paal, N. B. Botero, and A. Steinfeld, Heliostat field layout optimization for high-temperature solar thermochemical processing, Solar Energy, vol.85, issue.2, pp.334-343, 2011.
DOI : 10.1016/j.solener.2010.11.018

L. Schunk, W. Lipi?ski, and A. Steinfeld, Heat transfer model of a solar receiver-reactor for the thermal dissociation of ZnO-Experimental validation at 10 kW and scale-up to 1 MW », In : Chemical Engineering Journal, vol.150, issue.92, pp.2-3, 2009.

E. J. Hoogenboom, Zero-Variance Monte Carlo Schemes Revisited, Nuclear Science and Engineering, vol.160, issue.1, pp.1-22, 2008.
DOI : 10.13182/NSE160-01

R. Assaraf and M. Caffarel, Zero-Variance Principle for Monte Carlo Algorithms, Physical Review Letters, vol.83, issue.23, pp.4682-89, 1999.
DOI : 10.1103/PhysRevLett.83.4682

W. Spendley, G. R. Hext, and F. Himsworth, Sequential Application of Simplex Designs in Optimisation and Evolutionary Operation, Technometrics, vol.39, issue.4, pp.441-461, 1962.
DOI : 10.1214/aoms/1177707047

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, Computer journal 7, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

J. E. Dennis-jr and V. Torczon, Direct Search Methods on Parallel Machines, SIAM Journal on Optimization, vol.1, issue.4, pp.448-474, 1991.
DOI : 10.1137/0801027

D. Winfield, Function Minimization by Interpolation in a Data Table, IMA Journal of Applied Mathematics, vol.12, issue.3, pp.339-347, 1973.
DOI : 10.1093/imamat/12.3.339

M. J. Powell, A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation, pp.51-67, 1994.
DOI : 10.1007/978-94-015-8330-5_4

M. J. Powell, A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation, pp.51-67, 1994.
DOI : 10.1007/978-94-015-8330-5_4

A. R. Conn, K. Scheinberg, and P. L. Toint, Recent progress in unconstrained nonlinear optimization without derivatives, Mathematical programming 79, pp.1-3, 1997.
DOI : 10.1007/BF02614326

A. R. Conn, K. Scheinberg, and P. L. Toint, « On the convergence of derivativefree methods for unconstrained optimization ». In : Approximation theory and optimization : tributes to MJD Powell, pp.83-108, 1997.

M. Marazzi and J. Nocedal, Wedge trust region methods for derivative free optimization, Mathematical programming 91, pp.289-305, 2002.
DOI : 10.1007/s101070100264

C. A. Coello, A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques, Knowledge and Information Systems, vol.265, issue.2, pp.129-156, 1999.
DOI : 10.1007/BF03325101

J. H. Holland, Adaptation in natural and artificial systems : An introductory analysis with applications to biology, control, and artificial intelligence, 1975.

D. E. Goldberg, Genetic algorithms in search, optimization, and machine learning. T. 412, 1989.

J. Kennedy and R. Eberhart, Particle swarm optimization, Proceedings of ICNN'95, International Conference on Neural Networks
DOI : 10.1109/ICNN.1995.488968

K. Al-sultan and M. , A tabu search Hooke and Jeeves algorithm for unconstrained optimization, European Journal of Operational Research, vol.103, issue.1, pp.198-208, 1997.
DOI : 10.1016/S0377-2217(96)00282-2

C. Price, B. Robertson, and M. Reale, « A hybrid Hooke and Jeeves-direct method for non-smooth optimization », In : Advanced Modeling and Optimization, vol.111, pp.43-61, 2009.

K. Premalatha and A. Natarajan, « Hybrid PSO and GA for global maximization, Int. J. Open Problems Compt. Math, vol.2, issue.4, pp.597-608, 2009.

T. Niknam, A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem, Applied Energy, vol.87, issue.1, pp.327-339, 2010.
DOI : 10.1016/j.apenergy.2009.05.016

S. S. Fan and E. Zahara, A hybrid simplex search and particle swarm optimization for unconstrained optimization, European Journal of Operational Research, vol.181, issue.2, pp.527-548, 2007.
DOI : 10.1016/j.ejor.2006.06.034

R. Banos, Optimization methods applied to renewable and sustainable energy : A review, Renewable and Sustainable Energy Reviews, vol.154, pp.1753-1766, 2011.

B. Belhomme, R. Pitz-paal, and P. Schwarzbözl, Optimization of Heliostat Aim Point Selection for Central Receiver Systems Based on the Ant Colony Optimization Metaheuristic, Journal of Solar Energy Engineering, vol.136, issue.1, pp.11005-105, 2013.
DOI : 10.1115/1.4024738

O. Farges, Particle swarm optimization of solar central receiver systems from a Monte Carlo direct model ». In : IPDO 2013 : 4th Inverse problems, design and optimization symposium. IPDO 2013 : 4th Inverse problems , design and optimization symposium
URL : https://hal.archives-ouvertes.fr/hal-01163826

G. Battaglia and . Dulikravich, Ecole des Mines d'Albi-Carmaux, juin 2013 (cf, p.105

D. A. Van-veldhuizen, Multiobjective Evolutionary Algorithms : Classifications , Analyses, and New Innovations, Rapp. tech. Evolutionary Computation, p.105, 1999.

D. A. Van-veldhuizen and G. B. Lamont, Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art, Evolutionary Computation, vol.8, issue.2, pp.125-147, 2000.
DOI : 10.1109/4235.797969

A. Ramos and F. Ramos, Strategies in tower solar power plant optimization, Solar Energy, vol.86, issue.9, p.105, 2012.
DOI : 10.1016/j.solener.2012.05.024

M. Wetter and J. Wright, A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization, Building and Environment, vol.39, issue.8, pp.989-999, 2004.
DOI : 10.1016/j.buildenv.2004.01.022

F. Van-den, A. P. Bergh, and . Engelbrecht, A new locally convergent particle swarm optimiser, IEEE International Conference on Systems, Man and Cybernetics, pp.6-105, 2002.
DOI : 10.1109/ICSMC.2002.1176018

J. Schutte, Parallel global optimization with the particle swarm algorithm, International Journal for Numerical Methods in Engineering, vol.28, issue.13, pp.2296-2315, 2004.
DOI : 10.1002/nme.1149

R. Poli, J. Kennedy, and T. Blackwell, Particle swarm optimization, Swarm Intelligence, vol.393, issue.6, pp.33-57, 2007.
DOI : 10.1007/s11721-007-0002-0

URL : https://hal.archives-ouvertes.fr/hal-01169049

C. K. Monson and K. D. Seppi, The Kalman Swarm, pp.140-150, 2004.
DOI : 10.1007/978-3-540-24854-5_13

R. A. Krohling and E. Mendel, Bare Bones Particle Swarm Optimization with Gaussian or Cauchy jumps, 2009 IEEE Congress on Evolutionary Computation, pp.3285-3291, 2009.
DOI : 10.1109/CEC.2009.4983361

J. Kennedy, Bare bones particle swarms, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706), pp.80-87, 2003.
DOI : 10.1109/SIS.2003.1202251

P. Andras, A Bayesian Interpretation of the Particle Swarm Optimization and Its Kernel Extension, PLoS ONE, vol.2006, issue.11, pp.48710-105, 2012.
DOI : 10.1371/journal.pone.0048710.t002

C. W. Reynolds, « Flocks, herds and schools : A distributed behavioral model, ACM SIGGRAPH Computer Graphics. T. 21. 4. ACM, pp.25-34, 1987.

A. Banks, J. Vincent, and C. Anyakoha, A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications, Natural Computing, vol.1, issue.1, pp.109-124, 2008.
DOI : 10.1007/s11047-007-9050-z

A. Segal, M. Epstein, F. Romeu, and F. , The reflective solar tower as an option for high temperature central receivers, 9th SolarPACES International Symposium on Solar Thermal Concentrating Technologies (STCT 9), pp.53-58, 1998.
DOI : 10.1051/jp4:1999308

F. Veynandt, « Cogénération héliothermodynamique avec concentrateur linéaire de Fresnel : modélisation de l'ensemble du procédé, Thèse de doct. Institut National Polytechnique de Toulouse, pp.10-129, 2011.

A. Segal, Optimization of heliostat field layout for the beam down optics, pp.116-125

C. J. Noone, M. Torrilhon, and A. Mitsos, Heliostat field optimization: A new computationally efficient model and biomimetic layout, Solar Energy, vol.86, issue.2, pp.792-803, 2012.
DOI : 10.1016/j.solener.2011.12.007

A. Segal and M. Epstein, The optics of the solar tower reflector, Solar Energy, vol.69, issue.2, pp.229-241, 2001.
DOI : 10.1016/S0038-092X(00)00137-7

R. Ben-zvi, A. Segal, and M. Epstein, Beam-Down Mirror: Thermal and Stress Analyses, Journal of Solar Energy Engineering, vol.131, issue.4, pp.41003-115, 2009.
DOI : 10.1115/1.3197536

A. Segal and M. Epstein, « Practical considerations in designing large scale « Beam Down » optical systems Journal of solar energy engineering - TRANS, 13th SOLAR- PACES International Symposium on Concentrated Solar Power and Chemical Energy Technologies, p.116, 2006.

M. Yuasa, Multi-tower effect of Tokyo Tech Beam Down System, Proceedings of JSES/JWEA Joint Conference. T, pp.107-110, 2008.

J. De and L. Torre, Monte Carlo advances and concentrated solar applications, Solar Energy, vol.103, pp.653-681, 2014.

J. Roccia, Tracing Monte-Carlo software for solar concentrating facilities, Journal of Physics : Conference Series. T. 369. 1, pp.12029-12048, 2012.

M. Roger, Monte Carlo Estimates of Domain-Deformation Sensitivities, Physical Review Letters, vol.95, issue.18, p.151, 2005.
DOI : 10.1103/PhysRevLett.95.180601

M. Roger, APPLICATIONS OF SENSITIVITY ESTIMATIONS BY MONTE CARLO METHODS, Proceeding of the 4th International Symposium on Radiative Transfer, p.131, 2004.
DOI : 10.1615/ICHMT.2004.RAD-4.50

M. Roger, « Modèles de sensibilité dans le cadre de la méthode de Monte-Carlo : illustrations en transfert radiatif, Thèse de doct, pp.134-135

A. De-guilhem-de-lataillade, Monte Carlo method and sensitivity estimations, Journal of Quantitative Spectroscopy and Radiative Transfer, vol.75, issue.5, pp.529-538, 2002.
DOI : 10.1016/S0022-4073(02)00027-4

A. De-guilhem-de-lataillade, « Modélisation détaillée des transferts radiatifs et couplage avec la cinétique chimique dans des systèmes en combustion, Thèse de doct. Institut National Polytechnique de Toulouse, p.134, 2001.

B. .. Figures, 1. Transformation suivant le vecteur vitesse de déformation, p.162

J. Dauchet, « Analyse radiative des photobioréacteurs, Thèse de doct, pp.134-146

M. Pharr and G. Humphreys, Physically Based Rendering, second edition : from theory to implementation, p.153, 2010.

M. Roger, Monte Carlo Estimates of Domain-Deformation Sensitivities, Physical Review Letters, vol.95, issue.18, p.151, 2005.
DOI : 10.1103/PhysRevLett.95.180601

M. Roger, « Modèles de sensibilité dans le cadre de la méthode de Monte-Carlo : illustrations en transfert radiatif, Thèse de doct, pp.134-135

T. D. Badia, Mardi 20 août, l'humanité entre en période de « dette écologique ». 20 août 2013. url : http://www.lemonde.fr/planete/article, 2013.

R. Pachauri and A. Reisinger, Changements Climatiques, GIEC, vol.103, issue.2, 2007.

D. Mills, Advances in solar thermal electricity technology, Solar Energy, vol.76, issue.1-3, pp.19-31, 2004.
DOI : 10.1016/S0038-092X(03)00102-6

R. Osuna, PS10 : a 11.0-MW solar tower power plant with saturated steam receiver, Proceedings 12th SolarPACES International Symposium. Sous la dir. de C. Ramos et J. Huacuz, p.78, 2004.

J. I. Burgaleta, S. Arias, and D. Ramirez, « Gemasolar, the first tower thermosolar commercial plant with molten salt storage, pp.20-23, 2011.

J. Marks, Israel Announces Plans for 121 MW Solar Power Station in the Negev Desert Sous la dir. d'inhabitant.com. 2012. url : http : //inhabitat.com/israel-to-build-121-mw-solar-power-station-in-the- negev-desert/israel_solar_brightsource

L. Woods, First solar tower in South Africa completed by Abengoa. url : http : / / www . pv -tech . org / news / first _ solar _ tower _ in _ south _ africa_completed_by_abengoa_6754, p.5, 2013.

B. Prior, As one solar thermal project dies, another is born. url : http://www.greentechmedia.com/articles/read/as-one-solar-thermalproject-dies-another-is-born, p.5, 2013.

]. A. Plocek, Spanish Government Selects SolarReserve's Solar Thermal Project in Competitive Tender. url : http://www.prnewswire.com/news- releases/spanish-government-selects-solarreserves-solar-thermal- project-in-competitive-tender-124603333.html

T. Woody, Pasadena's ESolar lands 2,000-megawatt deal in China Sous la dir. de L. A. Times, 2010.

S. Relloso and J. Lata, « Molten salt thermal storage : a proven solution to increase plant dispatchability. Experience in Gemasolar Tower plant, pp.1-6, 2011.

R. I. Dunn, P. J. Hearps, and M. N. Wright, Molten-Salt Power Towers: Newly Commercial Concentrating Solar Storage, Proceedings of the IEEE 100, pp.504-515, 2012.
DOI : 10.1109/JPROC.2011.2163739

. Torresol, Gemasolar solar power plant reaches 24 hours of uninterrupted production, Company website, p.5, 2011.

J. Bézian, Un nouveau concept de centrale solaire thermodynamique basé sur un récepteur à lit fluidisé, 13èmes Journées Internationales de Thermique, 2007.

B. Grange, « Modélisation et dimensionnement d'un récepteur solaire à air pressurisé pour le projet PEGASE, Thèse de doct, p.2013

A. Colleoni, « Intensification des transferts de chaleur en régime turbulent pour le développement d'un récepteur solaire surfacique à haute température en céramique, Thèse de doct, 2013.

I. Hischier, Heat Transfer Analysis of a Novel Pressurized Air Receiver for Concentrated Solar Power via Combined Cycles, Journal of Thermal Science and Engineering Applications, vol.1, issue.4, pp.41002-41008, 2009.
DOI : 10.1115/1.4001259

A. Bounaceur, « Interaction lit fluidisé de particules solides-rayonnement solaire concentré pour la mise au point d'un procédé de chauffage de gaz à plus de 1000 K, Thèse de doct. École Nationale Supérieure des Mines de Paris, p.6, 2009.

G. Baud, « Conception de récepteurs solaires à lit fluidisé sous flux radiatif concentré, Thèse de doct. Institut National Polytechnique de Toulouse, p.6, 2011.

G. J. Kolb, Power tower technology roadmap and cost reduction plan, pp.2011-2419, 2011.

H. Hasuike, Demonstration of tokyo tech beam-down solar concentration power system in 100kw pilot plant, Proceedings of 15th SolarPACES Conference, 2009.

Y. Tamaura, Development of tokyo tech beam-down solar concentration power system (tokyotech-cosmo-masdar project), Proceedings of 15th SolarPACES Conference, pp.114-115, 2009.

Y. Tamaura, A novel beam-down system for solar power generation with multi-ring central reflectors and molten salt thermal storage, Proceedings of 13th International Symposium on Concentrated Solar Power and Chemical Energy Technologies (cf, p.7

A. Segal and M. Epstein, COMPARATIVE PERFORMANCES OF `TOWER-TOP' AND `TOWER-REFLECTOR' CENTRAL SOLAR RECEIVERS, Solar Energy, vol.65, issue.4, pp.207-226, 1999.
DOI : 10.1016/S0038-092X(98)00138-8

A. Segal, M. Epstein, F. Romeu, and F. , The reflective solar tower as an option for high temperature central receivers, 9th SolarPACES International Symposium on Solar Thermal Concentrating Technologies (STCT 9), pp.53-58, 1998.
DOI : 10.1051/jp4:1999308

J. De and L. Torre, « Calculs de sensibilités par la méthode de Monte Carlo pour la conception de procédés à énergie solaire concentrée, Thèse de doct. Institut National Polytechnique de Toulouse, pp.18-21, 2011.

F. Veynandt, « Cogénération héliothermodynamique avec concentrateur linéaire de Fresnel : modélisation de l'ensemble du procédé, Thèse de doct. Institut National Polytechnique de Toulouse, pp.10-129, 2011.

J. Dauchet, « Analyse radiative des photobioréacteurs, Thèse de doct, pp.134-146

J. De and L. Torre, Monte Carlo advances and concentrated solar applications, Solar Energy, vol.103, pp.653-681, 2014.

P. Garcia, A. Ferrière, and J. J. Bézian, Codes for solar flux calculation dedicated to central receiver system applications: A comparative review, Solar Energy, vol.82, issue.3, pp.189-197, 2008.
DOI : 10.1016/j.solener.2007.08.004

C. K. Ho, Software and Codes for Analysis of Concentrating Solar Power Technologies, Rapp. tech, p.15, 2008.
DOI : 10.2172/946571

P. Leary and J. Hankins, User's guide for MIRVAL : a computer code for comparing designs of heliostat-receiver optics for central receiver solar power plants, Rapp. tech. Sandia Labs, pp.1979-1997
DOI : 10.2172/6371450

T. Wendelin, SolTRACE: A New Optical Modeling Tool for Concentrating Solar Optics, Solar Energy, p.18, 2003.
DOI : 10.1115/ISEC2003-44090

M. J. Blanco, J. M. Amieva, and A. Mancilla, The Tonatiuh Software Development Project: An Open Source Approach to the Simulation of Solar Concentrating Systems, Computers and Information in Engineering, pp.157-164, 2005.
DOI : 10.1115/IMECE2005-81859

J. Roccia, Tracing Monte-Carlo software for solar concentrating facilities, Journal of Physics : Conference Series. T. 369. 1, pp.12029-12048, 2012.

B. Belhomme, A New Fast Ray Tracing Tool for High-Precision Simulation of Heliostat Fields, Journal of Solar Energy Engineering, vol.131, issue.3, pp.31002-31021, 2009.
DOI : 10.1115/1.3139139

F. J. Collado and J. Guallar, A review of optimized design layouts for solar power tower plants with campo code, Renewable and Sustainable Energy Reviews, vol.20, pp.142-154, 2013.
DOI : 10.1016/j.rser.2012.11.076

E. Leonardi and B. D. Aguanno, CRS4-2: A numerical code for the calculation of the solar power collected in a central receiver system, Energy, vol.36, issue.8, pp.4828-4837, 2011.
DOI : 10.1016/j.energy.2011.05.017

L. Erminia, « Detailed analysis of the solar power collected in a beam-down central receiver system, Solar Energy, vol.862, pp.734-745, 2012.

P. Perez, Algorithmes de synthèse d'image et propriétés spectrales des gaz de combustion : Méthode de Monte-Carlo pour la simulation des transferts radiatifs dans les procédés à haute température, Thèse de doct. Institut National Polytechnique de Toulouse, 2008.

M. Pharr and G. Humphreys, Physically Based Rendering, second edition : from theory to implementation, p.153, 2010.

N. Metropolis and S. Ulam, The Monte Carlo Method, Journal of the American Statistical Association, vol.44, issue.247, pp.335-341, 1949.
DOI : 10.1080/01621459.1949.10483310

J. M. Hammersley and D. C. Handscomb, Monte Carlo Methods, Chapman et Hall, p.22, 1969.

W. L. Dunn and J. K. Shultis, Exploring Monte Carlo methods

J. Howell, The Monte Carlo Method in Radiative Heat Transfer, Journal of Heat Transfer, vol.120, issue.3, pp.547-560, 1998.
DOI : 10.1115/1.2824310

G. Rubino, B. Tuffin, . Simulations, M. Méthodes-de, and . Carlo, url : http: //www.techniques-ingenieur.fr/base-documentaire/sciences-fondame ntales -th8 / mathematiques -pour -l -ingenieur -ti052 / simulations -et - methodes, Techniques de l'ingénieur. AF 600. Éditions T.I, pp.1-15, 2007.

J. F. Blinn, Models of light reflection for computer synthesized pictures, ACM SIGGRAPH Computer Graphics, vol.11, issue.2, pp.192-198, 1977.
DOI : 10.1145/965141.563893

I. Reda and A. Andreas, « Solar position algorithm for solar radiation applications, In : Solar Energy, vol.765, pp.577-589, 2004.

G. J. Kolb, Heliostat cost reduction study

F. Lipps and L. Vant-hull, A cellwise method for the optimization of large central receiver systems, Solar Energy, vol.20, issue.6, pp.505-516, 1978.
DOI : 10.1016/0038-092X(78)90067-1

P. K. Falcone, A handbook for solar central receiver design, Rapp. tech. Sandia National Labs, vol.34, p.32, 1986.
DOI : 10.2172/6545992

F. M. Siala and M. E. Elayeb, Mathematical formulation of a graphical method for a no-blocking heliostat field layout, Renewable Energy, vol.23, issue.1, pp.77-92, 2001.
DOI : 10.1016/S0960-1481(00)00159-2

M. Mokhtar, Heliostat field efficiency test of beam down csp pilot plant experimenatal results, Proceedings of 16th SolarPACES Conference, p.32, 2010.

A. Segal, Optimization of heliostat field layout for the beam down optics, pp.116-125

M. Sánchez and M. Romero, Methodology for generation of heliostat field layout in central receiver systems based on yearly normalized energy surfaces, Solar Energy, vol.80, issue.7, pp.861-874, 2006.
DOI : 10.1016/j.solener.2005.05.014

C. J. Noone, M. Torrilhon, and A. Mitsos, Heliostat field optimization: A new computationally efficient model and biomimetic layout, Solar Energy, vol.86, issue.2, pp.792-803, 2012.
DOI : 10.1016/j.solener.2011.12.007

T. Pylkanen, Personnal communication

R. Osuna, PS10 : A 10 MW solar thermal power plant for southern spain, Proceedings of 10th SolarPACES Conference, pp.37-78, 2000.

M. Mustafa, S. Abdelhady, and A. Elweteedy, Analytical Study of an Innovated Solar Power Tower (PS10) in Aswan, International Journal of Energy Engineering, vol.2, issue.6, pp.273-278, 2012.
DOI : 10.5923/j.ijee.20120206.01

R. Osuna, A 10 MW Solar Tower Power Plant for Southern Spain, Proceedings of the 8th International Energy Forum. Sous la dir, pp.37-78, 2000.

M. Romero, R. Buck, and J. E. Pacheco, An Update on Solar Central Receiver Systems, Projects, and Technologies, Journal of solar energy engineering 124, pp.98-108, 2002.
DOI : 10.1115/1.1467921

P. Schwarzbözl, R. Pitz-paal, and M. Schmitz, « Visual HFLCAL -A software tool for layout and optimization of heliostat fields, Proceedings of 15th SolarPACES Conference, p.46, 2009.

P. Gilman, Solar advisor model user guide for version 2.0, p.46, 2008.
DOI : 10.2172/937349

F. J. Collado, Quick evaluation of the annual heliostat field efficiency, Solar Energy, vol.82, issue.4, pp.379-384, 2008.
DOI : 10.1016/j.solener.2007.10.007

R. Osuna, R. Olavarría, and R. R. Morillo, « Construction of a 11MW Solar Thermal Tower Plant in Seville, Spain, Proceeding of 13 th Solar PACES Symposium, pp.48-78, 2006.

O. Farges, Simulation of yearly energy for solar heating systems, Proceedings of 18th SolarPACES Conference, pp.2012-52

B. D. Ehrhart and D. D. Gill, Evaluation of annual efficiencies of high temperature central receiver concentrated solar power plants with thermal energy storage, Rapp. tech. Sandia National Laboratories (SNL-NM), pp.2013-79

E. Koepf, A novel beam-down, gravity-fed, solar thermochemical receiver/reactor for direct solid particle decomposition: Design, modeling, and experimentation, International Journal of Hydrogen Energy, vol.37, issue.22, p.82, 2012.
DOI : 10.1016/j.ijhydene.2012.08.086

R. Pitz-paal, N. B. Botero, and A. Steinfeld, Heliostat field layout optimization for high-temperature solar thermochemical processing, Solar Energy, vol.85, issue.2, pp.334-343, 2011.
DOI : 10.1016/j.solener.2010.11.018

L. Schunk, W. Lipi?ski, and A. Steinfeld, Heat transfer model of a solar receiver-reactor for the thermal dissociation of ZnO-Experimental validation at 10 kW and scale-up to 1 MW », In : Chemical Engineering Journal, vol.150, issue.92, pp.2-3, 2009.

E. J. Hoogenboom, Zero-Variance Monte Carlo Schemes Revisited, Nuclear Science and Engineering, vol.160, issue.1, pp.1-22, 2008.
DOI : 10.13182/NSE160-01

R. Assaraf and M. Caffarel, Zero-Variance Principle for Monte Carlo Algorithms, Physical Review Letters, vol.83, issue.23, pp.4682-89, 1999.
DOI : 10.1103/PhysRevLett.83.4682

N. Sharma, Stochastic techniques used for optimization in solar systems: A review, Renewable and Sustainable Energy Reviews, vol.16, issue.3, pp.1399-1411, 2012.
DOI : 10.1016/j.rser.2011.11.019

S. A. Kalogirou, Optimization of solar systems using artificial neural-networks and genetic algorithms, Applied Energy, vol.77, issue.4, pp.383-405, 2004.
DOI : 10.1016/S0306-2619(03)00153-3

S. A. Rukolaine, Regular solution of inverse optimal design problems for axisymmetric systems of radiative heat transfer, High Temperature, vol.46, issue.1, pp.115-123, 2008.
DOI : 10.1134/s10740-008-1016-z

H. H. Rosenbrock, An Automatic Method for Finding the Greatest or Least Value of a Function, The Computer Journal, vol.3, issue.3, pp.175-184, 1960.
DOI : 10.1093/comjnl/3.3.175

W. Spendley, G. R. Hext, and F. Himsworth, Sequential Application of Simplex Designs in Optimisation and Evolutionary Operation, Technometrics, vol.39, issue.4, pp.441-461, 1962.
DOI : 10.1214/aoms/1177707047

J. A. Nelder and R. Mead, A Simplex Method for Function Minimization, Computer journal 7, pp.308-313, 1965.
DOI : 10.1093/comjnl/7.4.308

J. E. Dennis-jr and V. Torczon, Direct Search Methods on Parallel Machines, SIAM Journal on Optimization, vol.1, issue.4, pp.448-474, 1991.
DOI : 10.1137/0801027

D. Winfield, Function Minimization by Interpolation in a Data Table, IMA Journal of Applied Mathematics, vol.12, issue.3, pp.339-347, 1973.
DOI : 10.1093/imamat/12.3.339

M. J. Powell, A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation, pp.51-67, 1994.
DOI : 10.1007/978-94-015-8330-5_4

M. J. Powell, A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation, pp.51-67, 1994.
DOI : 10.1007/978-94-015-8330-5_4

A. R. Conn, K. Scheinberg, and P. L. Toint, Recent progress in unconstrained nonlinear optimization without derivatives, Mathematical programming 79, pp.1-3, 1997.
DOI : 10.1007/BF02614326

A. R. Conn, K. Scheinberg, and P. L. Toint, « On the convergence of derivativefree methods for unconstrained optimization ». In : Approximation theory and optimization : tributes to MJD Powell, pp.83-108, 1997.

M. Marazzi and J. Nocedal, Wedge trust region methods for derivative free optimization, Mathematical programming 91, pp.289-305, 2002.
DOI : 10.1007/s101070100264

C. A. Coello, A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques, Knowledge and Information Systems, vol.265, issue.2, pp.129-156, 1999.
DOI : 10.1007/BF03325101

J. H. Holland, Adaptation in natural and artificial systems : An introductory analysis with applications to biology, control, and artificial intelligence, 1975.

D. E. Goldberg, Genetic algorithms in search, optimization, and machine learning. T. 412, 1989.

J. Kennedy and R. Eberhart, Particle swarm optimization, Proceedings of ICNN'95, International Conference on Neural Networks, pp.1942-1948, 1995.
DOI : 10.1109/ICNN.1995.488968

K. Al-sultan and M. , A tabu search Hooke and Jeeves algorithm for unconstrained optimization, European Journal of Operational Research, vol.103, issue.1, pp.198-208, 1997.
DOI : 10.1016/S0377-2217(96)00282-2

C. Price, B. Robertson, and M. Reale, « A hybrid Hooke and Jeeves-direct method for non-smooth optimization », In : Advanced Modeling and Optimization, vol.111, pp.43-61, 2009.

K. Premalatha and A. Natarajan, « Hybrid PSO and GA for global maximization, Int. J. Open Problems Compt. Math, vol.2, issue.4, pp.597-608, 2009.

T. Niknam, A new fuzzy adaptive hybrid particle swarm optimization algorithm for non-linear, non-smooth and non-convex economic dispatch problem, Applied Energy, vol.87, issue.1, pp.327-339, 2010.
DOI : 10.1016/j.apenergy.2009.05.016

S. S. Fan and E. Zahara, A hybrid simplex search and particle swarm optimization for unconstrained optimization, European Journal of Operational Research, vol.181, issue.2, pp.527-548, 2007.
DOI : 10.1016/j.ejor.2006.06.034

R. Banos, Optimization methods applied to renewable and sustainable energy : A review, Renewable and Sustainable Energy Reviews, vol.154, pp.1753-1766, 2011.

B. Belhomme, R. Pitz-paal, and P. Schwarzbözl, Optimization of Heliostat Aim Point Selection for Central Receiver Systems Based on the Ant Colony Optimization Metaheuristic, Journal of Solar Energy Engineering, vol.136, issue.1, pp.11005-105, 2013.
DOI : 10.1115/1.4024738

O. Farges, Particle swarm optimization of solar central receiver systems from a Monte Carlo direct model ». In : IPDO 2013 : 4th Inverse problems, design and optimization symposium. IPDO 2013 : 4th Inverse problems , design and optimization symposium
URL : https://hal.archives-ouvertes.fr/hal-01163826

G. Battaglia and . Dulikravich, Ecole des Mines d'Albi-Carmaux, juin 2013 (cf, p.105

D. A. Van-veldhuizen, Multiobjective Evolutionary Algorithms : Classifications , Analyses, and New Innovations, Rapp. tech. Evolutionary Computation, p.105, 1999.

D. A. Van-veldhuizen and G. B. Lamont, Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art, Evolutionary Computation, vol.8, issue.2, pp.125-147, 2000.
DOI : 10.1109/4235.797969

A. Ramos and F. Ramos, Strategies in tower solar power plant optimization, Solar Energy, vol.86, issue.9, p.105, 2012.
DOI : 10.1016/j.solener.2012.05.024

M. Wetter and J. Wright, A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization, Building and Environment, vol.39, issue.8, pp.989-999, 2004.
DOI : 10.1016/j.buildenv.2004.01.022

F. Van-den, A. P. Bergh, and . Engelbrecht, A new locally convergent particle swarm optimiser, IEEE International Conference on Systems, Man and Cybernetics, pp.6-105, 2002.
DOI : 10.1109/ICSMC.2002.1176018

J. Schutte, Parallel global optimization with the particle swarm algorithm, International Journal for Numerical Methods in Engineering, vol.28, issue.13, pp.2296-2315, 2004.
DOI : 10.1002/nme.1149

R. Poli, J. Kennedy, and T. Blackwell, Particle swarm optimization, Swarm Intelligence, vol.393, issue.6, pp.33-57, 2007.
DOI : 10.1007/s11721-007-0002-0

URL : https://hal.archives-ouvertes.fr/hal-01169049

C. K. Monson and K. D. Seppi, The Kalman Swarm, Genetic and Evolutionary Computation?GECCO 2004, pp.140-150, 2004.
DOI : 10.1007/978-3-540-24854-5_13

R. A. Krohling and E. Mendel, Bare Bones Particle Swarm Optimization with Gaussian or Cauchy jumps, 2009 IEEE Congress on Evolutionary Computation, pp.3285-3291, 2009.
DOI : 10.1109/CEC.2009.4983361

J. Kennedy, Bare bones particle swarms, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706), pp.80-87, 2003.
DOI : 10.1109/SIS.2003.1202251

P. Andras, A Bayesian Interpretation of the Particle Swarm Optimization and Its Kernel Extension, PLoS ONE, vol.2006, issue.11, pp.48710-105, 2012.
DOI : 10.1371/journal.pone.0048710.t002

C. W. Reynolds, « Flocks, herds and schools : A distributed behavioral model, ACM SIGGRAPH Computer Graphics. T. 21. 4. ACM, pp.25-34, 1987.

A. Banks, J. Vincent, and C. Anyakoha, A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications, Natural Computing, vol.1, issue.1, pp.109-124, 2008.
DOI : 10.1007/s11047-007-9050-z

A. Segal and M. Epstein, The optics of the solar tower reflector, Solar Energy, vol.69, issue.2, pp.229-241, 2001.
DOI : 10.1016/S0038-092X(00)00137-7

R. Ben-zvi, A. Segal, and M. Epstein, Beam-Down Mirror: Thermal and Stress Analyses, Journal of Solar Energy Engineering, vol.131, issue.4, pp.41003-115, 2009.
DOI : 10.1115/1.3197536

A. Segal and M. Epstein, « Practical considerations in designing large scale « Beam Down » optical systems Journal of solar energy engineering - TRANS, 13th SOLAR- PACES International Symposium on Concentrated Solar Power and Chemical Energy Technologies, p.116, 2006.

M. Yuasa, Multi-tower effect of Tokyo Tech Beam Down System, Proceedings of JSES/JWEA Joint Conference. T, pp.107-110, 2008.

M. Roger, Monte Carlo Estimates of Domain-Deformation Sensitivities, Physical Review Letters, vol.95, issue.18, p.151, 2005.
DOI : 10.1103/PhysRevLett.95.180601

M. Roger, APPLICATIONS OF SENSITIVITY ESTIMATIONS BY MONTE CARLO METHODS, Proceeding of the 4th International Symposium on Radiative Transfer, p.131, 2004.
DOI : 10.1615/ICHMT.2004.RAD-4.50

M. Roger, « Modèles de sensibilité dans le cadre de la méthode de Monte-Carlo : illustrations en transfert radiatif, Thèse de doct, pp.134-135

A. De-guilhem-de-lataillade, Monte Carlo method and sensitivity estimations, Journal of Quantitative Spectroscopy and Radiative Transfer, vol.75, issue.5, pp.529-538, 2002.
DOI : 10.1016/S0022-4073(02)00027-4

A. De-guilhem-de-lataillade, « Modélisation détaillée des transferts radiatifs et couplage avec la cinétique chimique dans des systèmes en combustion, Thèse de doct. Institut National Polytechnique de Toulouse, p.134, 2001.

J. J. Bernoulli, ?. Bernoulli, and . Wikipedia, The Free Encyclopedia . [Online ; accessed 15-03, 2010.

C. Darwin, ?. Charles-darwin, and . Wikipedia, The Free Encyclopedia . [Online ; accessed 15-03, 2010.

P. Dirac, ?. Paul-dirac, and . Wikipedia, The Free Encyclopedia. [Online ; accessed 15-03, 2010.

A. A. Fresnel, ?. Fresnel, and . Wikipedia, The Free Encyclopedia . [Online ; accessed 15-03, 2010.

O. Heaviside, ?. Oliver-heaviside, and . Wikipedia, The Free Encyclopedia . [Online ; accessed 15-03, 2010.

I. Newton, ?. Isaac-newton, and . Wikipedia, The Free Encyclopedia. [Online ; accessed 15-03, 2010.

. Photobioréacteur, ?. Photobioréacteur, and . Wikipedia, The Free Encyclopedia . [Online ; accessed 18-03, 2010.

O. Programmation-orientée, Programmation orientée objet ? Wikipedia The Free Encyclopedia. [Online ; accessed 15-03, 2010.

B. B. Taylor, ?. Taylor, and . Wikipedia, The Free Encyclopedia. [Online ; accessed 15-03, 2010.