The article “Hybrid Physics-Data Modeling of Building Thermal Dynamics” has been published in the Artificial Intelligence in HVAC issue of the REHVA Journal.
Authored by Mattia Bergagio, Massimo Amerio and Francesco Gallo (EURIX), together with Paola Fasiello (REHVA), the paper presents key results from Task 4.1 of the ENTRANCE project, focusing on the development of data-driven dynamic models to improve building energy flexibility.
The study introduces a hybrid, physics-informed and interpretable modelling framework, which combines physical knowledge with data-driven techniques to more accurately capture building thermal dynamics. The approach is demonstrated through its application to one of the ENTRANCE pilot buildings, highlighting its potential to support advanced energy management strategies in buildings.
The publication contributes to ENTRANCE’s objectives by advancing AI-based methods for understanding and controlling building energy behaviour, with implications for flexibility, efficiency and sustainability in HVAC systems.
Read the article here: https://entrance-project.com/results/
