IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i15p3904-d1707185.html
   My bibliography  Save this article

Experimental Study of Solar Hot Water Heating System with Adaptive Control Strategy

Author

Listed:
  • Pawel Znaczko

    (Faculty of Mechanical and Energy Engineering, Koszalin University of Technology, 75-453 Koszalin, Poland)

  • Norbert Chamier-Gliszczynski

    (Faculty of Economics Sciences, Koszalin University of Technology, 75-453 Koszalin, Poland)

  • Kazimierz Kaminski

    (Faculty of Mechanical and Energy Engineering, Koszalin University of Technology, 75-453 Koszalin, Poland)

Abstract

The efficiency of solar water heating systems is strongly influenced by variable weather conditions, making the optimization of control strategies essential for maximizing energy performance. This study presents the development and evaluation of a rule-based adaptive control strategy that dynamically selects one of three predefined control modes—ON–OFF, proportional, or indirect proportional control (IPC)—based on real-time weather classification. The classification algorithm assigns each day to one of four solar irradiance categories, enabling the controller to respond appropriately to current environmental conditions. The proposed adaptive controller was implemented and tested under real operating conditions and compared with a conventional commercial solar controller. Over a 40-day testing period, the adaptive system achieved a 12.7% increase in thermal energy storage efficiency. Specifically, despite receiving 4.8% less solar radiation (719 kWh vs. 755 kWh), the adaptive controller stored 453 kWh of heat in the water tank compared to 416 kWh with the traditional system. This corresponds to an efficiency improvement from 0.55 to 0.63. These results demonstrate the adaptive controller’s superior ability to utilize available solar energy across all weather scenarios. The findings confirm that intelligent control strategies not only enhance technical performance but also improve the economic and environmental value of solar thermal systems.

Suggested Citation

  • Pawel Znaczko & Norbert Chamier-Gliszczynski & Kazimierz Kaminski, 2025. "Experimental Study of Solar Hot Water Heating System with Adaptive Control Strategy," Energies, MDPI, vol. 18(15), pages 1-18, July.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:3904-:d:1707185
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/15/3904/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/15/3904/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wiktor Olchowik & Marcin Bednarek & Tadeusz Dąbrowski & Adam Rosiński, 2023. "Application of the Energy Efficiency Mathematical Model to Diagnose Photovoltaic Micro-Systems," Energies, MDPI, vol. 16(18), pages 1-24, September.
    2. Unterberger, Viktor & Lichtenegger, Klaus & Kaisermayer, Valentin & Gölles, Markus & Horn, Martin, 2021. "An adaptive short-term forecasting method for the energy yield of flat-plate solar collector systems," Applied Energy, Elsevier, vol. 293(C).
    3. Tamás Orosz & Anton Rassõlkin & Pedro Arsénio & Peter Poór & Daniil Valme & Ádám Sleisz, 2024. "Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels," Energies, MDPI, vol. 17(6), pages 1-22, March.
    4. Dariusz Kurz & Artur Bugała & Damian Głuchy & Leszek Kasprzyk & Jan Szymenderski & Andrzej Tomczewski & Grzegorz Trzmiel, 2024. "The Use of Renewable Energy Sources in Road Construction and Public Transport: A Review," Energies, MDPI, vol. 17(9), pages 1-46, April.
    5. Paweł Kelm & Rozmysław Mieński & Irena Wasiak, 2024. "Modular PV System for Applications in Prosumer Installations with Uncontrolled, Unbalanced and Non-Linear Loads," Energies, MDPI, vol. 17(7), pages 1-13, March.
    6. Xin, Xin & Liu, Yanfeng & Zhang, Zhihao & Zheng, Huifan & Zhou, Yong, 2025. "A day-ahead operational regulation method for solar district heating systems based on model predictive control," Applied Energy, Elsevier, vol. 377(PC).
    7. 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.
    8. Ntsaluba, Sula & Zhu, Bing & Xia, Xiaohua, 2016. "Optimal flow control of a forced circulation solar water heating system with energy storage units and connecting pipes," Renewable Energy, Elsevier, vol. 89(C), pages 108-124.
    9. 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.
    10. Rozmysław Mieński & Irena Wasiak & Paweł Kelm, 2023. "Integration of PV Sources in Prosumer Installations Eliminating Their Negative Impact on the Supplying Grid and Optimizing the Microgrid Operation," Energies, MDPI, vol. 16(8), pages 1-17, April.
    11. Edyta Dudkiewicz & Natalia Fidorów-Kaprawy, 2020. "Hybrid Domestic Hot Water System Performance in Industrial Hall," Resources, MDPI, vol. 9(6), pages 1-12, May.
    12. Ioan Sarbu & Calin Sebarchievici, 2018. "A Comprehensive Review of Thermal Energy Storage," Sustainability, MDPI, vol. 10(1), pages 1-32, January.
    13. Madalina Barbu & George Darie & Monica Siroux, 2020. "A Parametric Study of a Hybrid Photovoltaic Thermal (PVT) System Coupled with a Domestic Hot Water (DHW) Storage Tank," Energies, MDPI, vol. 13(24), pages 1-18, December.
    14. Yang, Moucun & Moghimi, M.A. & Loillier, R. & Markides, C.N. & Kadivar, M., 2023. "Design of a latent heat thermal energy storage system under simultaneous charging and discharging for solar domestic hot water applications," Applied Energy, Elsevier, vol. 336(C).
    15. Nahin Tasmin & Shahjadi Hisan Farjana & Md Rashed Hossain & Santu Golder & M. A. Parvez Mahmud, 2022. "Integration of Solar Process Heat in Industries: A Review," Clean Technol., MDPI, vol. 4(1), pages 1-35, February.
    16. Pawel Znaczko & Kazimierz Kaminski & Norbert Chamier-Gliszczynski & Emilian Szczepanski & Paweł Gołda, 2021. "Experimental Analysis of Control Methods in Solar Water Heating Systems," Energies, MDPI, vol. 14(24), pages 1-16, December.
    17. Yin, Linfei & Xiong, Yi, 2024. "Fast-apply deep autoregressive recurrent proximal policy optimization for controlling hot water systems," Applied Energy, Elsevier, vol. 367(C).
    18. Marcin Olkiewicz & Joanna Alicja Dyczkowska & Anna Maria Olkiewicz, 2023. "Financial Aspects of Energy Investments in the Era of Shaping Stable Energy Development in Poland: A Case Study," Energies, MDPI, vol. 16(23), pages 1-21, November.
    19. Dariusz Kurz & Arkadiusz Dobrzycki & Ewelina Krawczak & Jarosław Jajczyk & Jakub Mielczarek & Waldemar Woźniak & Michał Sąsiadek & Olga Orynycz & Karol Tucki & Ewa Badzińska, 2025. "An Analysis of the Increase in Energy Efficiency of Photovoltaic Installations by Using Bifacial Modules," Energies, MDPI, vol. 18(5), pages 1-25, March.
    Full references (including those not matched with items on IDEAS)

    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. Zheng, Zhihang & Jin, Yipeng & Zhou, Jin & Yang, Ying & Xu, Feng & Liu, Hongcheng, 2025. "A novel dynamic operation method for solar assisted air source heat pump systems: Optimization control and performance analysis," Energy, Elsevier, vol. 316(C).
    3. Kicsiny, Richárd, 2018. "Black-box model for solar storage tanks based on multiple linear regression," Renewable Energy, Elsevier, vol. 125(C), pages 857-865.
    4. Hall, Rebecca & Kenway, Steven & O'Brien, Katherine & Memon, Fayyaz, 2025. "Quantification of residential water-related energy needs cohesion, validation and global representation to unlock efficiency gains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    5. Laurynas Šriupša & Mindaugas Vaitkūnas & Artūras Baronas & Gytis Svinkūnas & Julius Dosinas & Andrius Knyš & Saulius Gudžius & Audrius Jonaitis & Darius Serva, 2025. "Enhancing the Efficiency of Photovoltaic Power Flows Management in Three-Phase Prosumer Grids," Sustainability, MDPI, vol. 17(5), pages 1-21, March.
    6. 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.
    7. Taler, Dawid & Sobota, Tomasz & Jaremkiewicz, Magdalena & Taler, Jan, 2022. "Control of the temperature in the hot liquid tank by using a digital PID controller considering the random errors of the thermometer indications," Energy, Elsevier, vol. 239(PE).
    8. Weeratunge, Hansani & Aditya, Gregorius Riyan & Dunstall, Simon & de Hoog, Julian & Narsilio, Guillermo & Halgamuge, Saman, 2021. "Feasibility and performance analysis of hybrid ground source heat pump systems in fourteen cities," Energy, Elsevier, vol. 234(C).
    9. Dawid Taler & Jan Taler & Tomasz Sobota & Jarosław Tokarczyk, 2022. "Cooling Modelling of an Electrically Heated Ceramic Heat Accumulator," Energies, MDPI, vol. 15(16), pages 1-26, August.
    10. Van Thillo, L. & Verbeke, S. & Audenaert, A., 2022. "The potential of building automation and control systems to lower the energy demand in residential buildings: A review of their performance and influencing parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    11. Sihvonen, Ville & Ollila, Iisa & Jaanto, Jasmin & Grönman, Aki & Honkapuro, Samuli & Riikonen, Juhani & Price, Alisdair, 2024. "Role of power-to-heat and thermal energy storage in decarbonization of district heating," Energy, Elsevier, vol. 305(C).
    12. Yin, Linfei & Xiong, Yi, 2024. "Incremental learning user profile and deep reinforcement learning for managing building energy in heating water," Energy, Elsevier, vol. 313(C).
    13. Fernando Venâncio Mucomole & Carlos Augusto Santos Silva & Lourenço Lázaro Magaia, 2025. "Parametric Forecast of Solar Energy over Time by Applying Machine Learning Techniques: Systematic Review," Energies, MDPI, vol. 18(6), pages 1-51, March.
    14. David-Hernández, Marco A. & Calderon-Vásquez, Ignacio & Battisti, Felipe G. & Cardemil, José M. & Cazorla-Marín, Antonio, 2024. "Design and assessment of a concentrating solar thermal system for industrial process heat with a copper slag packed-bed thermal energy storage," Applied Energy, Elsevier, vol. 376(PA).
    15. Laura Canale & Anna Rita Di Fazio & Mario Russo & Andrea Frattolillo & Marco Dell’Isola, 2021. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings," Energies, MDPI, vol. 14(4), pages 1-33, February.
    16. Balderrama Prieto, Silvino A. & Sabharwall, Piyush, 2024. "Technical and economic evaluation of heat transfer fluids for a TES system integrated to an advanced nuclear reactor," Applied Energy, Elsevier, vol. 360(C).
    17. Zhao, Yongliang & Song, Jian & Liu, Ming & Zhao, Yao & Olympios, Andreas V. & Sapin, Paul & Yan, Junjie & Markides, Christos N., 2022. "Thermo-economic assessments of pumped-thermal electricity storage systems employing sensible heat storage materials," Renewable Energy, Elsevier, vol. 186(C), pages 431-456.
    18. Diana Isabel Berrocal & Juan Blandon Rodriguez & Maria De Los Angeles Ortega Del Rosario & Itamar Harris & Arthur M. James Rivas, 2024. "Heat Transfer Enhancements Assessment in Hot Water Generation with Phase Change Materials (PCMs): A Review," Energies, MDPI, vol. 17(10), pages 1-35, May.
    19. Clark, Ruby-Jean & Farid, Mohammed, 2022. "Experimental investigation into cascade thermochemical energy storage system using SrCl2-cement and zeolite-13X materials," Applied Energy, Elsevier, vol. 316(C).
    20. Correa-Jullian, Camila & López Droguett, Enrique & Cardemil, José Miguel, 2020. "Operation scheduling in a solar thermal system: A reinforcement learning-based framework," Applied Energy, Elsevier, vol. 268(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jeners:v:18:y:2025:i:15:p:3904-:d:1707185. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.