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An optimized Monte Carlo ray tracing optical simulation model and its applications to line-focus concentrating solar collectors

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  • Fan, Man
  • You, Shijun
  • Xia, Junbao
  • Zheng, Wandong
  • Zhang, Huan
  • Liang, Hongbo
  • Li, Xianli
  • Li, Bojia

Abstract

The Monte Carlo Ray Tracing (MCRT) method has been confirmed flexible and efficient in the optical simulation of Concentrating Solar Collectors (CSCs), but it usually needs higher computing cost and longer runtime or its results fluctuate in multiple runs. The parameters of the way of random number generation, the number of rays, running times, grid numbers, and random number generation times all exerted effects on the simulation results. It was found that running the MCRT model with less number of rays for several more times could mitigate the fluctuation of results and decrease the total runtime simultaneously. Taken the Line-focus CSC with a metal-glass receiver and a parabolic reflector as an example, the maximum (emax) and average (eavg) relative errors of the MCRT method with 1 × 108 rays running for once, 2 × 107 rays running for once and 3 × 106 rays running for five times were all lower than the threshold values (Emax = 5% and Eavg = 0.5%), but the total runtime was about 410 s, 82 s and 63 s respectively. On these bases, an optimized MCRT model was proposed by combining the MCRT method with the iteration method, where the minimum running times (tmin) and the maximum running times (tmax) were introduced, and they could be changed conveniently to meet the requirements of different optical simulations. By applying the proposed model to the Line-focus CSC with a more complex cavity receiver or compound parabolic reflector, the total runtime varied in the range of 268–413 s and 26–102 min respectively, indicating that the runtime reduction was significant when the limit of relative errors were acceptable. The proposed model is beneficial to mitigate the fluctuation, improve the accuracy and reduce the runtime of the MCRT method. It can also be further used to the optical simulation of various kinds of CSCs.

Suggested Citation

  • Fan, Man & You, Shijun & Xia, Junbao & Zheng, Wandong & Zhang, Huan & Liang, Hongbo & Li, Xianli & Li, Bojia, 2018. "An optimized Monte Carlo ray tracing optical simulation model and its applications to line-focus concentrating solar collectors," Applied Energy, Elsevier, vol. 225(C), pages 769-781.
  • Handle: RePEc:eee:appene:v:225:y:2018:i:c:p:769-781
    DOI: 10.1016/j.apenergy.2018.05.067
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    4. Sebastián, Andrés & Abbas, Rubén & Valdés, Manuel & Casanova, Jesús, 2018. "Innovative thermal storage strategies for Fresnel-based concentrating solar plants with East-West orientation," Applied Energy, Elsevier, vol. 230(C), pages 983-995.
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    6. Zheng, Canyang & Zhang, Xueyan & Luo, Huilong & Chen, Fei & Xiao, Liye & Wang, Xin & Gao, Xuerong, 2024. "Optical performance investigation for spatially separated non-imaging concentrator with congruent plane concentrating surface," Energy, Elsevier, vol. 299(C).
    7. Zhang, Xueyan & Jiang, Shuoxun & Lin, Ziming & Gui, Qinghua & Chen, Fei, 2023. "Model construction and performance analysis for asymmetric compound parabolic concentrator with circular absorber," Energy, Elsevier, vol. 267(C).
    8. Liu, Shang & Huang, Congliang & Luo, Xiao & Guo, Chuwen, 2019. "Performance optimization of bi-layer solar steam generation system through tuning porosity of bottom layer," Applied Energy, Elsevier, vol. 239(C), pages 504-513.
    9. Kincaid, Nicholas & Mungas, Greg & Kramer, Nicholas & Wagner, Michael & Zhu, Guangdong, 2018. "An optical performance comparison of three concentrating solar power collector designs in linear Fresnel, parabolic trough, and central receiver," Applied Energy, Elsevier, vol. 231(C), pages 1109-1121.
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