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Data-Driven Estimation of Time-Varying Stochastic Effects on Building Heat Consumption Related to Human Interactions

Author

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  • Christoffer Rasmussen

    (Department of Applied Mathematics and Computer Science, The Technical University of Denmark, 2800 Kongens Lyngby, Denmark
    Department of Research and Development, Watts, 4600 Køge, Denmark)

  • Niels Lassen

    (Skanska Technology, Skanska Norway, 0187 Oslo, Norway)

  • Peder Bacher

    (Department of Applied Mathematics and Computer Science, The Technical University of Denmark, 2800 Kongens Lyngby, Denmark)

  • Tor Helge Dokka

    (Skanska Technology, Skanska Norway, 0187 Oslo, Norway)

  • Henrik Madsen

    (Department of Applied Mathematics and Computer Science, The Technical University of Denmark, 2800 Kongens Lyngby, Denmark)

Abstract

Within the field of statistical modelling and data-driven characterisation of buildings’ energy performance, the focus is typically on parameter estimation of the building envelope and the energy systems. Less focus has been put on the stochastic human effect on energy consumption. We propose a new method for estimating the thermal building properties while, in parallel, estimating time-varying effects caused by the humans’ interactions with the building. We do that by combining a smooth, non-linear formulation of the energy signature method known from the literature with a hidden state formulated as a random walk to describe the human interactions with the building. The method is demonstrated on data obtained from autumn 2019 to late spring 2021 from a 900 m 2 newly built school building located south of Oslo, Norway. The demonstration case has shown that the model accuracy increases and the model bias decrease when cross-validated. The estimated hidden state has also been shown to resemble the estimated combined mechanical and natural ventilation pattern controlled by the building users and operational staff. These human interactions have increased the total heat loss expressed in kilowatts per kelvin by around 50% over the course of one year from before the COVID-19 pandemic to after its outbreak.

Suggested Citation

  • Christoffer Rasmussen & Niels Lassen & Peder Bacher & Tor Helge Dokka & Henrik Madsen, 2023. "Data-Driven Estimation of Time-Varying Stochastic Effects on Building Heat Consumption Related to Human Interactions," Energies, MDPI, vol. 16(16), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:16:p:5991-:d:1217909
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    References listed on IDEAS

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    1. Schweiker, Marcel & Shukuya, Masanori, 2010. "Comparative effects of building envelope improvements and occupant behavioural changes on the exergy consumption for heating and cooling," Energy Policy, Elsevier, vol. 38(6), pages 2976-2986, June.
    2. Christoffer Rasmussen & Peder Bacher & Davide Calì & Henrik Aalborg Nielsen & Henrik Madsen, 2020. "Method for Scalable and Automatised Thermal Building Performance Documentation and Screening," Energies, MDPI, vol. 13(15), pages 1-23, July.
    3. Hammarsten, Stig, 1987. "A critical appraisal of energy-signature models," Applied Energy, Elsevier, vol. 26(2), pages 97-110.
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