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Control-Oriented, Data-Driven Models of Thermal Dynamics

Author

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  • Ljuboslav Boskic

    (Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA
    Nevada National Security Site, Special Technologies Laboratory, Santa Barbara, CA 93117, USA)

  • Igor Mezic

    (Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106, USA)

Abstract

We investigate data-driven, simple-to-implement residential environmental models that can serve as the basis for energy saving algorithms in both retrofits and new designs of residential buildings. Despite the nonlinearity of the underlying dynamics, using Koopman operator theory framework in this study we show that a linear second order model embedding, that captures the physics that occur inside a single or multi zone space does well when compared with data simulated using EnergyPlus. This class of models has low complexity. We show that their parameters have physical significance for the large-scale dynamics of a building and are correlated to concepts such as the thermal mass. We investigate consequences of changing the thermal mass on the energy behavior of a building system and provide best practice design suggestions.

Suggested Citation

  • Ljuboslav Boskic & Igor Mezic, 2021. "Control-Oriented, Data-Driven Models of Thermal Dynamics," Energies, MDPI, vol. 14(5), pages 1-14, March.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1453-:d:512165
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    References listed on IDEAS

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    1. Antar, Mohamed A., 2010. "Thermal radiation role in conjugate heat transfer across a multiple-cavity building block," Energy, Elsevier, vol. 35(8), pages 3508-3516.
    2. Kuczyński, T. & Staszczuk, A., 2020. "Experimental study of the influence of thermal mass on thermal comfort and cooling energy demand in residential buildings," Energy, Elsevier, vol. 195(C).
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