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Transfer functions of solar heating systems for dynamic analysis and control design

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  • Kicsiny, Richárd

Abstract

Mathematical modelling is the theoretically established tool for developing solar heating systems, e.g. with using transfer functions. If we know the transfer functions of the system, the outlet temperature can be predicted as a function of the input variables (solar irradiance, inlet temperature, environment temperatures), dynamic analysis can be carried out, and stable system control can be effectively designed based on the well-tried methods of control engineering. For these purposes, new, validated transfer functions for solar heating systems are worked out in this study based on a mathematical model, which can be found in the literature and has been applied successfully in the field. The transfer functions are used for dynamic analysis and control design of solar heating systems. The dynamic analysis is presented and the efficiency of the proposed stable control is demonstrated with respect to a real solar heating system.

Suggested Citation

  • Kicsiny, Richárd, 2015. "Transfer functions of solar heating systems for dynamic analysis and control design," Renewable Energy, Elsevier, vol. 77(C), pages 64-78.
    • Handle: RePEc:eee:renene:v:77:y:2015:i:c:p:64-78
    DOI: 10.1016/j.renene.2014.12.001
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    References listed on IDEAS

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    1. Ayala, Claudio O. & Roca, Lidia & Guzman, Jose Luis & Normey-Rico, Julio E. & Berenguel, Manolo & Yebra, Luis, 2011. "Local model predictive controller in a solar desalination plant collector field," Renewable Energy, Elsevier, vol. 36(11), pages 3001-3012.
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    Cited by:

    1. Araújo, António & Pereira, Vítor, 2017. "Solar thermal modeling for rapid estimation of auxiliary energy requirements in domestic hot water production: Proportional flow rate control," Energy, Elsevier, vol. 138(C), pages 668-681.
    2. Araújo, António & Silva, Rui, 2020. "Energy modeling of solar water heating systems with on-off control and thermally stratified storage using a fast computation algorithm," Renewable Energy, Elsevier, vol. 150(C), pages 891-906.
    3. Araújo, António & Pereira, Vítor, 2017. "Solar thermal modeling for rapid estimation of auxiliary energy requirements in domestic hot water production: On-off flow rate control," Energy, Elsevier, vol. 119(C), pages 637-651.
    4. Tilahun, Fitsum Bekele & Bhandari, Ramchandra & Mamo, Mengesha, 2019. "Design optimization and control approach for a solar-augmented industrial heating," Energy, Elsevier, vol. 179(C), pages 186-198.
    5. Badescu, Viorel & Abed, Qahtan A. & Ciocanea, Adrian & Soriga, Iuliana, 2017. "The stability of the radiative regime does influence the daily performance of solar air heaters," Renewable Energy, Elsevier, vol. 107(C), pages 403-416.
    6. Kicsiny, Richárd, 2016. "Improved multiple linear regression based models for solar collectors," Renewable Energy, Elsevier, vol. 91(C), pages 224-232.

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