Analytic ray tracer on GPU for central receiver systems

被引:0
|
作者
Hoevelmann, F. [1 ]
Aldenhoff, L. [1 ]
Richter, P. [1 ]
机构
[1] Rhein Westfal TH Aachen, Dept Comp Sci, Res Grp Theory Hybrid Syst, Ahornstr 55, D-52074 Aachen, Germany
关键词
Central receiver system; Ray tracer; Monte Carlo method; Convolution method; Flux map; GPU; FLUX DISTRIBUTION; HELIOSTAT FIELD;
D O I
10.1016/j.solener.2023.112149
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
An accurate ray tracer is essential to calculate the efficiency of central receiver systems. Furthermore, its runtime has a direct influence on the applicable optimization method for finding optimal layouts of heliostat fields. Developing a ray tracer that achieves both objectives is the main focus of this study. There exist several different ray tracing techniques, starting from the classical Monte Carlo method to analytical convolution methods. Within this work, we introduce a new analytical ray tracer with high accuracy at low runtime. This is achieved by integrating over the bivariate Gaussian distributions used in our convolution ray tracer. In such a way the raytracer is capable of including the effect of multiple solar rays without the need of simulating each ray. Besides the overall efficiency, the new ray tracer can also compute accurate flux maps with thousand times fewer rays than the Monte Carlo method. To further improve the overall model accuracy, a new equation to convolute the sun, slope and tracking error is derived. We show that it perfectly matches the results of a separate accounting for these errors. The newly integrated convolution ray tracer is developed on the same platform as a bidirectional Monte Carlo ray tracer and a convolution method. Besides a large cross-validation of the results, this allows for a reasonable direct run time comparison. With extensive case studies, the quality of the solution, the run time, and various other aspects are investigated. Furthermore, all ray tracers are also implemented on the GPU improving the run time compared to the CPU version by a factor of 50. We show that the integrated convolution ray tracer running on the GPU achieves an accuracy of 99.95% for an annual simulation in 0.7 s for the PS10 and in 1.8 s for the Gemasolar.
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页数:14
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