Monte Carlo advances and concentrated solar applications

Abstract

International audienceThe 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

Global optimization of solar power tower systems using a Monte Carlo algorithm: Application to a redesign of the PS10 solar thermal power plant

“…This Monte Carlo algorithm, previously presented as the MCST 1 algorithm (Farges et al, 2015), takes advantage of Monte Carlo integral formulation as outlined by de La Torre et al (2014). An overview of the specific Monte Carlo algorithm, dealing with the sun's positions in the sky, is presented in fig.…”

“…Some dates are sampled using an importance sampling approach, then locations on the heliostat field where the sun rays are first reflected are uniformly sampled, after which the algorithm follows the behaviour of the rays in the SPT, ie computes reflections until each ray hits the final receiver or is lost. The MCST algorithm is thoroughly explained in (de La Torre et al, 2014), so it was decided not to go into detail here but only to reintroduce this algorithm with the addition of the yearly heliostat field optical efficiency estimation:…”

“…The direct model is implemented in the numerical framework EDStaR (de La Torre et al, 2014). This tool yields the practical implementation of a Monte Carlo algorithm for the radiative heat transfer model, making use of an integral formulation, and takes into consideration zero-variance approaches and sensitivity estimation as presented by Hoogenboom (2008) and Roger et al (2005).…”

“…It benefits from all the modern possibilities of computing such as massive parallelization and acceleration of ray tracing in a complex geometry. Different solar applications have already been simulated with this tool (de La Torre et al, 2014). EDStaR permits very efficient implementation of the direct model.…”

High-flux optical systems for solar thermochemistry

“…Differences among the existing Monte Carlo ray tracing simulation packages include the programming language, the use of parallelization, the available surface geometries, light source (including sunshape) models, surface error and optical property models, the user interface, the post-processing capabilities, and the level of technical support. The field is dynamic, and recent advances in Monte Carlo ray tracing modeling are being presently evaluated for solar concentrated power applications (Delatorre et al, 2014).…”