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The Architecture for Testing Central Heating Control Algorithms with Feedback from Wireless Temperature Sensors

Author

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  • Michał Markiewicz

    (Faculty of Mathematics and Computer Science, Jagiellonian University, ul. prof. Stanisława Łojasiewicza 6, 30-348 Cracow, Poland
    Atner Sp. z o.o., ul. Podole 60, 30-394 Cracow, Poland)

  • Aleksander Skała

    (Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Kraków, al. Mickiewicza 30, 30-059 Cracow, Poland)

  • Jakub Grela

    (Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Kraków, al. Mickiewicza 30, 30-059 Cracow, Poland)

  • Szymon Janusz

    (Atner Sp. z o.o., ul. Podole 60, 30-394 Cracow, Poland)

  • Tadeusz Stasiak

    (Honeywell Sp. z o.o., ul. Domaniewska 39, 02-672 Warsaw, Poland)

  • Dominik Latoń

    (Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Kraków, al. Mickiewicza 30, 30-059 Cracow, Poland)

  • Andrzej Bielecki

    (Chair of Applied Computer Science, Faculty of Electrical Engineering, Automation, Computer Science and Biomedical Engineering, AGH University of Kraków, 30-059 Cracow, Poland)

  • Katarzyna Bańczyk

    (Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Kraków, al. Mickiewicza 30, 30-059 Cracow, Poland)

Abstract

The energy consumption of buildings is a significant contributor to overall energy consumption in developed countries. Therefore, there is great demand for intelligent buildings in which energy consumption is optimized. Online control is a crucial aspect of such optimization. The implementation of modern algorithms that take advantage of developments in information technology, artificial intelligence, machine learning, sensors, and the Internet of Things (IoT) is used in this context. In this paper, an architecture for testing central heating control algorithms as well as the control algorithms of the heating system of the building is presented. In particular, evaluation metrics, the method for seamless integration, and the mechanism for real-time performance monitoring and control are put forward. The proposed tools have been successfully tested in a residential building, and the conducted tests confirmed the efficiency of the proposed solution.

Suggested Citation

  • Michał Markiewicz & Aleksander Skała & Jakub Grela & Szymon Janusz & Tadeusz Stasiak & Dominik Latoń & Andrzej Bielecki & Katarzyna Bańczyk, 2023. "The Architecture for Testing Central Heating Control Algorithms with Feedback from Wireless Temperature Sensors," Energies, MDPI, vol. 16(14), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5584-:d:1201537
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    References listed on IDEAS

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    1. Farinaz Behrooz & Norman Mariun & Mohammad Hamiruce Marhaban & Mohd Amran Mohd Radzi & Abdul Rahman Ramli, 2018. "Review of Control Techniques for HVAC Systems—Nonlinearity Approaches Based on Fuzzy Cognitive Maps," Energies, MDPI, vol. 11(3), pages 1-41, February.
    2. Rolf Golombek & Sverre Kittelsen & Ingjerd Haddeland, 2012. "Climate change: impacts on electricity markets in Western Europe," Climatic Change, Springer, vol. 113(2), pages 357-370, July.
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    Cited by:

    1. Dominik Latoń & Jakub Grela & Andrzej Ożadowicz, 2024. "Applications of Deep Reinforcement Learning for Home Energy Management Systems: A Review," Energies, MDPI, vol. 17(24), pages 1-30, December.

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