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Run-time detection and correction of heliostat tracking errors

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  • Chiesi, Matteo
  • Franchi Scarselli, Eleonora
  • Guerrieri, Roberto

Abstract

This paper investigates the effect of tracking errors in heliostats used in solar tower power plants and proposes an approach based on low-cost distributed electronics capable of limiting their impact. An analysis carried out through a parallel model sets the specifications for design of a closed-loop solar tracker based on a low-cost six-axis digital e-compass. A proof of concept system is devised to test the accuracy of the proposed strategy. This approach allows the solar tracker to perform a run-time detection and correction of heliostat tracking errors, with an accuracy of about 3mrad for the azimuth angle and less than 2mrad for the altitude angle, thus leading to a higher concentration ratio than with an open-loop solar-tracker.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:105:y:2017:i:c:p:702-711
    DOI: 10.1016/j.renene.2016.12.093
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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. Behar, Omar & Khellaf, Abdallah & Mohammedi, Kamal, 2013. "A review of studies on central receiver solar thermal power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 12-39.
    3. Siala, F.M.F & Elayeb, M.E, 2001. "Mathematical formulation of a graphical method for a no-blocking heliostat field layout," Renewable Energy, Elsevier, vol. 23(1), pages 77-92.
    4. Kribus, Abraham & Vishnevetsky, Irina & Yogev, Amnon & Rubinov, Tatiana, 2004. "Closed loop control of heliostats," Energy, Elsevier, vol. 29(5), pages 905-913.
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    Cited by:

    1. Carballo, Jose A. & Bonilla, Javier & Berenguel, Manuel & Fernández-Reche, Jesús & García, Ginés, 2019. "New approach for solar tracking systems based on computer vision, low cost hardware and deep learning," Renewable Energy, Elsevier, vol. 133(C), pages 1158-1166.
    2. Rodríguez-Sánchez, M.R. & Leray, C. & Toutant, A. & Ferriere, A. & Olalde, G., 2019. "Development of a new method to estimate the incident solar flux on central receivers from deteriorated heliostats," Renewable Energy, Elsevier, vol. 130(C), pages 182-190.
    3. 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.

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