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Smart Home Innovative Heat Test Analysis for Heat Storage and Conductivity Coefficients

Author

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  • Duygu Erten

    (Civil Engineering Department Faculty, Engineering and Natural Sciences, Istanbul Medipol University, Beykoz 34810, Istanbul, Turkey)

  • Zekâi Şen

    (Civil Engineering Department Faculty, Engineering and Natural Sciences, Istanbul Medipol University, Beykoz 34810, Istanbul, Turkey)

Abstract

This paper aims at presenting an innovative methodological approach to identify the heat storage and heat conductivity coefficients of a smart house. For this purpose, an experimental room is selected and heated to a high degree and then left for cooling, during which the reduction in the room temperature is measured with time. The time–temperature record provides the basis for determining the heat storage and heat conductivity coefficients through an objective standard curve matching procedure as the main context. These coefficients help to calculate the heat performance of a single room and, accordingly, the whole building, depending on its surrounding environment, construction material, volume and meteorological conditions. The proposed methodology depends on the one-dimensional heat flow event assuming that the construction material is homogeneous and isotropic and that the heat scatters uniformly in the room. The novelty in the paper is the standard curve for time–temperature decrease record evaluation, which can be used in a smart building planning procedure for decisions on heat storage and transfer.

Suggested Citation

  • Duygu Erten & Zekâi Şen, 2020. "Smart Home Innovative Heat Test Analysis for Heat Storage and Conductivity Coefficients," Sustainability, MDPI, vol. 12(4), pages 1-11, February.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:4:p:1414-:d:320653
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    References listed on IDEAS

    as
    1. Ioan Sarbu & Calin Sebarchievici, 2018. "A Comprehensive Review of Thermal Energy Storage," Sustainability, MDPI, vol. 10(1), pages 1-32, January.
    2. Muratori, Matteo & Roberts, Matthew C. & Sioshansi, Ramteen & Marano, Vincenzo & Rizzoni, Giorgio, 2013. "A highly resolved modeling technique to simulate residential power demand," Applied Energy, Elsevier, vol. 107(C), pages 465-473.
    3. Yu, Zhun (Jerry) & Haghighat, Fariborz & Fung, Benjamin C.M. & Morofsky, Edward & Yoshino, Hiroshi, 2011. "A methodology for identifying and improving occupant behavior in residential buildings," Energy, Elsevier, vol. 36(11), pages 6596-6608.
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