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GPU-based Monte Carlo ray tracing simulation considering refraction for central receiver system

Author

Listed:
  • Lin, Xiaoxia
  • He, Caitou
  • Huang, Wenjun
  • Zhao, Yuhong
  • Feng, Jieqing
Abstract
The heliostat in the central receiver system usually adopts silvered-glass reflectors, where a glass layer covers a specular reflection layer. Previous flux density distribution simulation methods ignored the refraction effects caused by the glass layer. This paper proposes a more accurate Monte Carlo ray-tracing simulation method considering refraction and total internal reflection (TIR) effects caused by the ray transmission in the glass layer. The proposed simulation method is fully designed and implemented on a graphics processing unit (GPU), which enables the algorithm performance to remain effective even when the simulation is more consistent with the real situation. Experiments and simulations reveal that refraction has non-negligible effects on the simulation results. Compared with the classical Monte Carlo ray-tracing simulation method that only considers the ray's reflection, refraction reduces the maximum radiative flux and total energy by up to 80% and 50%, respectively. Refraction also causes the flux spot reflected on the receiver panel to spread greatly. In several extreme cases, the ray is trapped in the glass due to TIR.

Suggested Citation

  • Lin, Xiaoxia & He, Caitou & Huang, Wenjun & Zhao, Yuhong & Feng, Jieqing, 2022. "GPU-based Monte Carlo ray tracing simulation considering refraction for central receiver system," Renewable Energy, Elsevier, vol. 193(C), pages 367-382.
  • Handle: RePEc:eee:renene:v:193:y:2022:i:c:p:367-382
    DOI: 10.1016/j.renene.2022.04.151
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    References listed on IDEAS

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    1. Chiesi, Matteo & Vanzolini, Luca & Franchi Scarselli, Eleonora & Guerrieri, Roberto, 2013. "Accurate optical model for design and analysis of solar fields based on heterogeneous multicore systems," Renewable Energy, Elsevier, vol. 55(C), pages 241-251.
    2. Cruz, N.C. & Salhi, S. & Redondo, J.L. & Álvarez, J.D. & Berenguel, M. & Ortigosa, P.M., 2018. "Hector, a new methodology for continuous and pattern-free heliostat field optimization," Applied Energy, Elsevier, vol. 225(C), pages 1123-1131.
    3. He, Caitou & Zhao, Yuhong & Feng, Jieqing, 2019. "An improved flux density distribution model for a flat heliostat (iHFLCAL) compared with HFLCAL," Energy, Elsevier, vol. 189(C).
    4. Bonanos, A.M. & Faka, M. & Abate, D. & Hermon, S. & Blanco, M.J., 2019. "Heliostat surface shape characterization for accurate flux prediction," Renewable Energy, Elsevier, vol. 142(C), pages 30-40.
    5. Cheng, Z.D. & He, Y.L. & Cui, F.Q., 2013. "A new modelling method and unified code with MCRT for concentrating solar collectors and its applications," Applied Energy, Elsevier, vol. 101(C), pages 686-698.
    6. Fernández, Angel G. & Gomez-Vidal, Judith & Oró, Eduard & Kruizenga, Alan & Solé, Aran & Cabeza, Luisa F., 2019. "Mainstreaming commercial CSP systems: A technology review," Renewable Energy, Elsevier, vol. 140(C), pages 152-176.
    7. Chiesi, Matteo & Franchi Scarselli, Eleonora & Guerrieri, Roberto, 2017. "Run-time detection and correction of heliostat tracking errors," Renewable Energy, Elsevier, vol. 105(C), pages 702-711.
    8. Alonso-Montesinos, J. & Polo, Jesús & Ballestrín, Jesús & Batlles, F.J. & Portillo, C., 2019. "Impact of DNI forecasting on CSP tower plant power production," Renewable Energy, Elsevier, vol. 138(C), pages 368-377.
    9. Huang, Weidong & Yu, Liang & Hu, Peng, 2019. "An analytical solution for the solar flux density produced by a round focusing heliostat," Renewable Energy, Elsevier, vol. 134(C), pages 306-320.
    10. He, Caitou & Duan, Xiaoyue & Zhao, Yuhong & Feng, Jieqing, 2019. "An analytical flux density distribution model with a closed-form expression for a flat heliostat," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    11. Ballestrín, J. & Monterreal, R. & Carra, M.E. & Fernández-Reche, J. & Polo, J. & Enrique, R. & Rodríguez, J. & Casanova, M. & Barbero, F.J. & Alonso-Montesinos, J. & López, G. & Bosch, J.L. & Batlles,, 2018. "Solar extinction measurement system based on digital cameras. Application to solar tower plants," Renewable Energy, Elsevier, vol. 125(C), pages 648-654.
    12. Sánchez-González, Alberto & Santana, Domingo, 2015. "Solar flux distribution on central receivers: A projection method from analytic function," Renewable Energy, Elsevier, vol. 74(C), pages 576-587.
    13. He, Caitou & Zhao, Hanli & He, Qi & Zhao, Yuhong & Feng, Jieqing, 2021. "Analytical radiative flux model via convolution integral and image plane mapping," Energy, Elsevier, vol. 222(C).
    14. Elsayed, M.M. & Fathalah, K.A., 1994. "Solar flux density distribution using a separation of variables/superposition technique," Renewable Energy, Elsevier, vol. 4(1), pages 77-87.
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    Cited by:

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