Predicting hourly thermal demand of buildings for digital twin-based energy network modeling using a steady-state model capturing thermal inertia
- 1Corresponding author.; SDU Center for Energy Informatics, Maersk Mc-Kinney Moeller Institute, The Faculty of Engineering, University of Southern Denmark, Campusvej 55, Odense 5230, Denmark
- 2Departament d’Enginyeria Minera, Industrial i TIC, Universitat Politécnica de Catalunya (UPC), Av. de les Bases de Manresa 61-73, Manresa 08240, Spain
- 3SDU Center for Energy Informatics, Maersk Mc-Kinney Moeller Institute, The Faculty of Engineering, University of Southern Denmark, Campusvej 55, Odense 5230, Denmark
Abstract
Quantifying energy consumption is a critical field of study in the planning of buildings. One of the main uses is evaluating the energy performance of the buildings. In addition, it can enable easy investigation of new, efficient methods of operating new generations of energy systems using simulation, with the model input being the energy demand. Dynamic methods for energy quantification often include temporal aspects, such as thermal inertia, resulting in high computational cost and model development. The advantages are higher model accuracy. However, a low computational cost method is preferred to allow for models of a grid of many interconnected buildings. This paper proposes a steady-state methodology for calculating hourly heat and cooling demand for planned or hypothetical buildings. It includes a novel approach to approximating the thermal inertia nature of buildings. The model is validated using real-world heat consumption data. The model has a mean bias error of 8.6 % and a coefficient of variation of root mean square error at 22.3 %, with the peak hourly load being around 1100 kW. These values fall within the ASHRAE guideline 14 specifications, and therefore, the model is deemed calibrated. More in-depth demonstrations of the mimicked dynamic mechanisms are also presented, along with an understanding of the largest contributors to heat losses and gains, for a theoretical building.
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BibTeX
@article{sondergaard2026predicting,
title = {{Predicting hourly thermal demand of buildings for digital twin-based energy network modeling using a steady-state model capturing thermal inertia}},
author = {Henrik Alexander Nissen Søndergaard and Jordi García-Céspedes and Hamid Reza Shaker and José Juan de Felipe and Bo Nørregaard Jørgensen},
journal = {Energy and Built Environment},
year = {2026},
month = oct,
doi = {10.1016/j.enbenv.2025.10.002},
url = {https://doi.org/10.1016/j.enbenv.2025.10.002},
note = {CC BY},
}
RIS
TY - JOUR
TI - Predicting hourly thermal demand of buildings for digital twin-based energy network modeling using a steady-state model capturing thermal inertia
AU - Henrik Alexander Nissen Søndergaard
AU - Jordi García-Céspedes
AU - Hamid Reza Shaker
AU - José Juan de Felipe
AU - Bo Nørregaard Jørgensen
PY - 2026
DA - 2026/10/30
JO - Energy and Built Environment
DO - 10.1016/j.enbenv.2025.10.002
UR - https://doi.org/10.1016/j.enbenv.2025.10.002
AB - Quantifying energy consumption is a critical field of study in the planning of buildings. One of the main uses is evaluating the energy performance of the buildings. In addition, it can enable easy investigation of new, efficient methods of operating new generations of energy systems using simulation, with the model input being the energy demand. Dynamic methods for energy quantification often include temporal aspects, such as thermal inertia, resulting in high computational cost and model development. The advantages are higher model accuracy. However, a low computational cost method is preferred to allow for models of a grid of many interconnected buildings. This paper proposes a steady-state methodology for calculating hourly heat and cooling demand for planned or hypothetical buildings. It includes a novel approach to approximating the thermal inertia nature of buildings. The model is validated using real-world heat consumption data. The model has a mean bias error of 8.6 % and a coefficient of variation of root mean square error at 22.3 %, with the peak hourly load being around 1100 kW. These values fall within the ASHRAE guideline 14 specifications, and therefore, the model is deemed calibrated. More in-depth demonstrations of the mimicked dynamic mechanisms are also presented, along with an understanding of the largest contributors to heat losses and gains, for a theoretical building.
SN - 2666-1233
ER -