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A detailed account of calculation of shading and blocking factor of a heliostat field

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  • Rizvi, Arslan A.
  • Yang, Dong

Abstract

The shading and blocking factor plays a significant role in the design of a heliostat field. It is the most computationally expensive task during the optimization process of a heliostat field. Over time, different methods have been developed to calculate the extent of the optical losses associated with shading and blocking. This paper focuses on the famous center point projection method and its implementation using Matlab. This work provides detailed procedures from the perspective of programming and simulation of central receiver systems. The underlying assumptions, the algorithm's strengths, and weaknesses are highlighted. The procedure and simulation parameters will help in developing optimization algorithms for designing high-efficiency heliostat fields. A dense radial staggered heliostat field is used for testing the performance of the algorithm. The field efficiency is calculated at different design points. The results show that the shading loss of the field changes with time, whereas there is negligible variation in the blocking loss. The instantaneous shading loss of a dense radial staggered field on December 21, noontime is 2.12%, whereas the blocking loss is 1.52%.

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  • Rizvi, Arslan A. & Yang, Dong, 2022. "A detailed account of calculation of shading and blocking factor of a heliostat field," Renewable Energy, Elsevier, vol. 181(C), pages 292-303.
    • Handle: RePEc:eee:renene:v:181:y:2022:i:c:p:292-303
    DOI: 10.1016/j.renene.2021.09.045
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    References listed on IDEAS

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    1. Zhang, Maolong & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "An efficient code to optimize the heliostat field and comparisons between the biomimetic spiral and staggered layout," Renewable Energy, Elsevier, vol. 87(P1), pages 720-730.
    2. Ortega, Guillermo & Rovira, Antonio, 2020. "A new method for the selection of candidates for shading and blocking in central receiver systems," Renewable Energy, Elsevier, vol. 152(C), pages 961-973.
    3. Saghafifar, Mohammad & Gadalla, Mohamed & Mohammadi, Kasra, 2019. "Thermo-economic analysis and optimization of heliostat fields using AINEH code: Analysis of implementation of non-equal heliostats (AINEH)," Renewable Energy, Elsevier, vol. 135(C), pages 920-935.
    4. Piroozmand, Pasha & Boroushaki, Mehrdad, 2016. "A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions," Energy, Elsevier, vol. 106(C), pages 240-252.
    5. Collado, Francisco J. & Guallar, Jesus, 2019. "Quick design of regular heliostat fields for commercial solar tower power plants," Energy, Elsevier, vol. 178(C), pages 115-125.
    6. Leonardi, Erminia & D’Aguanno, Bruno, 2011. "CRS4-2: A numerical code for the calculation of the solar power collected in a central receiver system," Energy, Elsevier, vol. 36(8), pages 4828-4837.
    7. Collado, Francisco J. & Guallar, Jesús, 2012. "Campo: Generation of regular heliostat fields," Renewable Energy, Elsevier, vol. 46(C), pages 49-59.
    8. Besarati, Saeb M. & Yogi Goswami, D., 2014. "A computationally efficient method for the design of the heliostat field for solar power tower plant," Renewable Energy, Elsevier, vol. 69(C), pages 226-232.
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