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

Christoffer Rasmussen (), Niels Lassen, Peder Bacher, Tor Helge Dokka and Henrik Madsen
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Christoffer Rasmussen: Department of Applied Mathematics and Computer Science, The Technical University of Denmark, 2800 Kongens Lyngby, 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

Energies, 2023, vol. 16, issue 16, 1-22

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.

Keywords: data-driven modelling; building physics; hidden state estimation; time-varying estimation; interpretablilty; occupants’ behaviour; building operation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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