Data-driven transfer function modelling of building dynamics using a frequency domain approach

Sophie Bernard; Bert Belmans; Filip Descamps; Arjen Mentens; Valéry Ann Jacobs; John Lataire

doi:10.26868/25222708.2021.30613

Data-driven transfer function modelling of building dynamics using a frequency domain approach

Sophie Bernard, Bert Belmans, Filip Descamps, Arjen Mentens, Valéry Ann Jacobs, John Lataire

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Abstract

In this research, a modelling tool is presented to de- rive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms. A data-driven approach is used to identify a model that is able to predict the indoor temperature in a case-study building when an electric heater is turned on. The approach is demon- strated on data obtained from EnergyPlus simula- tions, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimisation criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.

Original language	English
Pages (from-to)	1810-1817
Number of pages	8
Journal	Building Simulation Conference proceedings
DOIs	https://doi.org/10.26868/25222708.2021.30613
Publication status	Published - 2022
Event	17th Conference of IBPSA - Bruges, Belgium Duration: 1 Sept 2021 → 3 Sept 2021 http://www.ibpsa.org/

Bibliographical note

Funding Information:
1This work was financially supported in part by the Flemish Government (Methusalem Fund METH1), and in part by the Fund for Scientific Research (FWO).

Funding Information:
For this study, EnergyPlus (an open-source software developed and funded by the U.S. Department of Energy (DOE)) is used to generate realistic data sets. The model estimation approach proposed in this paper is developed such as to be useable on actual measurements as well, to be implemented in future work.

Publisher Copyright:
© International Building Performance Simulation Association, 2022

Copyright:
Copyright 2023 Elsevier B.V., All rights reserved.

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bs2021_30613Accepted author manuscript, 3.98 MB

http://www.ibpsa.org/?page_id=292

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title = "Data-driven transfer function modelling of building dynamics using a frequency domain approach",

abstract = "In this research, a modelling tool is presented to de- rive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms. A data-driven approach is used to identify a model that is able to predict the indoor temperature in a case-study building when an electric heater is turned on. The approach is demon- strated on data obtained from EnergyPlus simula- tions, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimisation criterion. The model inputs were limited to the heater{\textquoteright}s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.",

author = "Sophie Bernard and Bert Belmans and Filip Descamps and Arjen Mentens and Jacobs, {Val{\'e}ry Ann} and John Lataire",

note = "Funding Information: 1This work was financially supported in part by the Flemish Government (Methusalem Fund METH1), and in part by the Fund for Scientific Research (FWO). Funding Information: For this study, EnergyPlus (an open-source software developed and funded by the U.S. Department of Energy (DOE)) is used to generate realistic data sets. The model estimation approach proposed in this paper is developed such as to be useable on actual measurements as well, to be implemented in future work. Publisher Copyright: {\textcopyright} International Building Performance Simulation Association, 2022 Copyright: Copyright 2023 Elsevier B.V., All rights reserved.; 17th Conference of IBPSA ; Conference date: 01-09-2021 Through 03-09-2021",

year = "2022",

doi = "10.26868/25222708.2021.30613",

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AU - Bernard, Sophie

AU - Belmans, Bert

AU - Descamps, Filip

AU - Mentens, Arjen

AU - Jacobs, Valéry Ann

AU - Lataire, John

N1 - Funding Information: 1This work was financially supported in part by the Flemish Government (Methusalem Fund METH1), and in part by the Fund for Scientific Research (FWO). Funding Information: For this study, EnergyPlus (an open-source software developed and funded by the U.S. Department of Energy (DOE)) is used to generate realistic data sets. The model estimation approach proposed in this paper is developed such as to be useable on actual measurements as well, to be implemented in future work. Publisher Copyright: © International Building Performance Simulation Association, 2022 Copyright: Copyright 2023 Elsevier B.V., All rights reserved.

PY - 2022

Y1 - 2022

N2 - In this research, a modelling tool is presented to de- rive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms. A data-driven approach is used to identify a model that is able to predict the indoor temperature in a case-study building when an electric heater is turned on. The approach is demon- strated on data obtained from EnergyPlus simula- tions, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimisation criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.

AB - In this research, a modelling tool is presented to de- rive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms. A data-driven approach is used to identify a model that is able to predict the indoor temperature in a case-study building when an electric heater is turned on. The approach is demon- strated on data obtained from EnergyPlus simula- tions, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimisation criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.

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DO - 10.26868/25222708.2021.30613

M3 - Conference paper

SN - 2522-2708

SP - 1810

EP - 1817

JO - Building Simulation Conference proceedings

JF - Building Simulation Conference proceedings

T2 - 17th Conference of IBPSA

Y2 - 1 September 2021 through 3 September 2021

ER -

Data-driven transfer function modelling of building dynamics using a frequency domain approach

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