IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v77y2015icp64-78.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148114008271
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2014.12.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Amrizal, N. & Chemisana, D. & Rosell, J.I. & Barrau, J., 2012. "A dynamic model based on the piston flow concept for the thermal characterization of solar collectors," Applied Energy, Elsevier, vol. 94(C), pages 244-250.
    2. 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.
    3. Kalogirou, Soteris A., 2000. "Applications of artificial neural-networks for energy systems," Applied Energy, Elsevier, vol. 67(1-2), pages 17-35, September.
    4. Fontalvo, Armando & Garcia, Jesus & Sanjuan, Marco & Padilla, Ricardo Vasquez, 2014. "Automatic control strategies for hybrid solar-fossil fuel power plants," Renewable Energy, Elsevier, vol. 62(C), pages 424-431.
    5. Kicsiny, R. & Nagy, J. & Szalóki, Cs., 2014. "Extended ordinary differential equation models for solar heating systems with pipes," Applied Energy, Elsevier, vol. 129(C), pages 166-176.
    6. Buzás, J. & Kicsiny, R., 2014. "Transfer functions of solar collectors for dynamical analysis and control design," Renewable Energy, Elsevier, vol. 68(C), pages 146-155.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Buzás, J. & Kicsiny, R., 2014. "Transfer functions of solar collectors for dynamical analysis and control design," Renewable Energy, Elsevier, vol. 68(C), pages 146-155.
    3. 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.
    4. 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.
    5. 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.
    6. Mehleri, E.D. & Zervas, P.L. & Sarimveis, H. & Palyvos, J.A. & Markatos, N.C., 2010. "A new neural network model for evaluating the performance of various hourly slope irradiation models: Implementation for the region of Athens," Renewable Energy, Elsevier, vol. 35(7), pages 1357-1362.
    7. Leung, Philip C.M. & Lee, Eric W.M., 2013. "Estimation of electrical power consumption in subway station design by intelligent approach," Applied Energy, Elsevier, vol. 101(C), pages 634-643.
    8. Jorge E. De León-Ruiz & Ignacio Carvajal-Mariscal & Antonin Ponsich, 2019. "Feasibility Analysis and Performance Evaluation and Optimization of a DXSAHP Water Heater Based on the Thermal Capacity of the System: A Case Study," Energies, MDPI, vol. 12(20), pages 1-38, October.
    9. Selimefendigil, Fatih & Öztop, Hakan F., 2020. "Identification of pulsating flow effects with CNT nanoparticles on the performance enhancements of thermoelectric generator (TEG) module in renewable energy applications," Renewable Energy, Elsevier, vol. 162(C), pages 1076-1086.
    10. Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2017. "Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 352-366.
    11. Khan, Waqas & Walker, Shalika & Zeiler, Wim, 2022. "Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach," Energy, Elsevier, vol. 240(C).
    12. Souliotis, M. & Kalogirou, S. & Tripanagnostopoulos, Y., 2009. "Modelling of an ICS solar water heater using artificial neural networks and TRNSYS," Renewable Energy, Elsevier, vol. 34(5), pages 1333-1339.
    13. Ata, Rasit, 2015. "Artificial neural networks applications in wind energy systems: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 534-562.
    14. Abu Bakar, Nur Najihah & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Abdullah, Md Pauzi & Hussin, Faridah & Bandi, Masilah, 2015. "Energy efficiency index as an indicator for measuring building energy performance: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 1-11.
    15. Bhowmik, Chiranjib & Bhowmik, Sumit & Ray, Amitava & Pandey, Krishna Murari, 2017. "Optimal green energy planning for sustainable development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 796-813.
    16. Hannah Jessie Rani R. & Aruldoss Albert Victoire T., 2018. "Training radial basis function networks for wind speed prediction using PSO enhanced differential search optimizer," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-35, May.
    17. Lidia Roca & Jorge A. Sánchez & Francisco Rodríguez & Javier Bonilla & Alberto De la Calle & Manuel Berenguel, 2016. "Predictive Control Applied to a Solar Desalination Plant Connected to a Greenhouse with Daily Variation of Irrigation Water Demand," Energies, MDPI, vol. 9(3), pages 1-17, March.
    18. Waqar Muhammad Ashraf & Ghulam Moeen Uddin & Syed Muhammad Arafat & Sher Afghan & Ahmad Hassan Kamal & Muhammad Asim & Muhammad Haider Khan & Muhammad Waqas Rafique & Uwe Naumann & Sajawal Gul Niazi &, 2020. "Optimization of a 660 MW e Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency," Energies, MDPI, vol. 13(21), pages 1-33, October.
    19. Kicsiny, Richárd, 2018. "Black-box model for solar storage tanks based on multiple linear regression," Renewable Energy, Elsevier, vol. 125(C), pages 857-865.
    20. Mohanraj, M. & Belyayev, Ye. & Jayaraj, S. & Kaltayev, A., 2018. "Research and developments on solar assisted compression heat pump systems – A comprehensive review (Part A: Modeling and modifications)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 90-123.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:77:y:2015:i:c:p:64-78. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.