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DOE OSTI · 2497362

Automated model generation and parameter estimation of building energy models using an ontology-based framework

Bjørnskov, Jakob [Univ. of Southern Denmark, Odense (Denmark)] (ORCID:0000000347932967)·Jradi, Muhyiddine [Univ. of Southern Denmark, Odense (Denmark)] (ORCID:0000000230391845)·Wetter, Michael [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000270430802)
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Abstract

This study presents a methodology for automated model generation and parameter estimation of building energy models using semantic modeling and Bayesian estimation. Semantic modeling techniques are used to represent the system components and their interactions, facilitating the automatic generation of a simulation model from dynamic component models. The proposed approach is applied to a case study of a ventilation system where a simulation model is generated, calibrated, and assessed through different performance metrics. These metrics demonstrate the accuracy and reliability of both model point estimates and probabilistic prediction intervals across all model outputs. Overall, the proposed methodology offers a systematic and automated approach to model development and calibration in building energy systems, with potential applications in building performance analysis, monitoring, and optimization.

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATIONBuilding energy modelBuilding performance simulationData-drivenDigital twinOntology

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Bjørnskov, Jakob [Univ. of Southern Denmark, Odense (Denmark)] (ORCID:0000000347932967), Jradi, Muhyiddine [Univ. of Southern Denmark, Odense (Denmark)] (ORCID:0000000230391845), Wetter, Michael [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000270430802). 2025-01-02. Automated model generation and parameter estimation of building energy models using an ontology-based framework. https://doi.org/10.1016/j.enbuild.2024.115228

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