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Heliostat surface shape characterization for accurate flux prediction

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  • Bonanos, A.M.
  • Faka, M.
  • Abate, D.
  • Hermon, S.
  • Blanco, M.J.

Abstract

The performance of a heliostat field is directly related to the optical quality of the mirror surfaces used to reflect solar radiation onto the receiver. In this paper, two methods are used to characterize the actual shape of the surface of a heliostat, using laser scanning and photogrammetry. The accuracy of each technique for the intended purpose is reported, while the methodology for analyzing the resulting point clouds is presented. The shape of the reflecting surface is reconstructed from the point clouds generated by each one of the methods used to characterize the actual shape of the heliostat surface. The Tonatiuh ray tracing program is used to compare the flux distributions of the heliostat obtained in this way, with the intended ideal parabolic shape of the heliostat. The flux distributions are also compared to optical images of the heliostat reflection on a plane target. Surface reconstruction from the photogrammetry point cloud results in a better agreement between the optical and simulated flux distributions on the target. Comparing results from the reconstructed surfaces and the ideal parabolic surface to optical images, a 20% improvement in prediction is achieved by using the photogrammetry point cloud as opposed to the ideal parabolic shape.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:142:y:2019:i:c:p:30-40
    DOI: 10.1016/j.renene.2019.04.051
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    References listed on IDEAS

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    1. Xiao, Jun & Wei, Xiudong & Lu, Zhenwu & Yu, Weixing & Wu, Hongsheng, 2012. "A review of available methods for surface shape measurement of solar concentrator in solar thermal power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2539-2544.
    2. Arancibia-Bulnes, Camilo A. & Peña-Cruz, Manuel I. & Mutuberría, Amaia & Díaz-Uribe, Rufino & Sánchez-González, Marcelino, 2017. "A survey of methods for the evaluation of reflective solar concentrator optics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 673-684.
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    Cited by:

    1. 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).
    2. 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.
    3. Isaías Moreno-Cruz & Juan Carlos Castro & Omar Álvarez-Brito & Hilda B. Mota-Nava & Guillermo Ramírez-Zúñiga & José J. Quiñones-Aguilar & Camilo A. Arancibia-Bulnes, 2020. "Development of an Elevation–Fresnel Linked Mini-Heliostat Array," Energies, MDPI, vol. 13(15), pages 1-19, August.

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