Monte Carlo advances and concentrated solar applications

J. Delatorre (1) , Germain Baud (1) , Jean-Jacques Bézian (1) , Stéphane Blanco (2) , Cyril Caliot (3) , J. F. Cornet , C. Coustet , J. Dauchet , Mouna El-Hafi (1) , Vincent Eymet (1) , Richard A Fournier (2) , J. Gautrais (4) , Olivier Gourmel (5) , D. Joseph , N. Meilhac (6) , Anthony Pajot (5) , Mathias Paulin (7) , P. Perez (8) , B. Piaud , Maxime Roger (9) , J. Rolland (1) , F. Veynandt (1) , Sebastian Weitz (6)

1 RAPSODEE - Centre de recherche d'Albi en génie des procédés des solides divisés, de l'énergie et de l'environnement
2 LAPLACE-GREPHE - Groupe de Recherche Energétique, Plasmas et Hors Equilibre
3 PROMES - Procédés, Matériaux et Energie Solaire
4 CRCA - Centre de Recherches sur la Cognition Animale - UMR5169
5 IRIT - Institut de recherche en informatique de Toulouse
6 LAPLACE - LAboratoire PLasma et Conversion d'Energie
7 IRIT-STORM - Structural Models and Tools in Computer Graphics
8 ONERA
9 Technical University of Lisbon

The Monte Carlo method is partially reviewed with the objective of illustrating how some of the most recent methodological advances can benefit to concentrated solar research. This review puts forward the practical consequences of writing down and handling the integral formulation associated to each Monte Carlo algorithm. Starting with simple examples and up to the most complex multiple reflection, multiple scattering configurations, we try to argue that these formulations are very much accessible to the non specialist and that they allow a straightforward entry to sensitivity computations (for assistance in design optimization processes) and to convergence enhancement techniques involving subtle concepts such as control variate and zero variance. All illustration examples makePROMES - UPR CNRS 8521 - 7, rue du Four Solaire, 66120 Font Romeu Odeillo, France use of the public domain development environment EDStar (including advanced parallelized computer graphics libraries) and are meant to serve as start basis either for the upgrading of existing Monte Carlo codes, or for fast implementation of ad hoc codes when specific needs cannot be answered with standard concentrated solar codes (in particular as far as the new generation of solar receivers is concerned). (C) 2013 Elsevier Ltd. All rights reserved.

Mots clés: Solar energy flux density distribution; Monte Carlo algorithm; Concentrated solar energy; Solar concentrators design optimization; Sensitivity computation

Domaines: Sciences de l'ingénieur [physics]

J. Delatorre, Germain Baud, Jean-Jacques Bézian, Stéphane Blanco, Cyril Caliot, et al.. Monte Carlo advances and concentrated solar applications. Solar Energy, 2014, 103, p.653-681. ⟨10.1016/j.solener.2013.02.035⟩. ⟨hal-01625034⟩