Open-source framework for automated generation of building energy performance simulation models and beyond from BIM Data

Automation in Construction, vol. 179, pp. 106427

Abstract

The manual creation of Building Energy Performance Simulation (BEPS) models is time-consuming and error-prone, hindering the implementation of energy-efficient building designs. This paper explores how to automate the generation of BEPS models from Building Information Modeling (BIM) data while addressing challenges of data imperfection and tool compatibility. bim2sim is presented as an open-source Python framework with a modular plugin architecture that processes Industry Foundation Classes (IFC) files to generate simulation models for various tools, including Modelica/TEASER and EnergyPlusWe present bim2sim , an open-source Python framework with a modular plugin architecture that processes Industry Foundation Classes (IFC) files to generate simulation models for various tools including Modelica/TEASER and EnergyPlus. The application to a non-residential building case study demonstrates the framework’s capability to produce functional simulation models at different levels of detail with significant time savings, reducing the time for generating simulation results from a BIM model to less than one hour. The framework benefits architects, building services engineers, and simulation engineers by streamlining the simulation workflow while maintaining OpenBIM compatibility. Future research should address remaining limitations in geometry processing and material mapping to further facilitate seamless information exchange between building design and simulation domains. • bim2sim framework converts BIM to simulation-ready building energy models, reducing manual processing and errors. • bim2sim is built as open-source Python framework with modular plugins supporting multiple simulation tools and domains. • Demonstration with two plugins: TEASER (Modelica) for annual energy demands and EnergyPlus for thermal/comfort analysis. • Efficient model conversion (<1hr), robust to imperfect IFC data while maintaining OpenBIM compatibility.

Authors 6

1. David Jansen corresponding Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Mathieustraße 10, Aachen, 52074, Germany

2. Veronika Richter Aachen Institute of Energy Efficiency and Sustainable Building (E3D)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Institute of Energy Efficiency and Sustainable Building, Mathieustr. 30, Aachen, 52074, Germany

3. Laura Maier Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Mathieustraße 10, Aachen, 52074, Germany

4. Jérôme Frisch Aachen Institute of Energy Efficiency and Sustainable Building (E3D)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Institute of Energy Efficiency and Sustainable Building, Mathieustr. 30, Aachen, 52074, Germany

5. Christoph van Treeck Aachen Institute of Energy Efficiency and Sustainable Building (E3D)

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, Institute of Energy Efficiency and Sustainable Building, Mathieustr. 30, Aachen, 52074, Germany

6. Dirk Müller Aachen E.ON Energy Research Center Institute for Energy Efficient Buildings and Indoor Climate

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University, E.ON Energy Research Center, Institute for Energy Efficient Buildings and Indoor Climate, Mathieustraße 10, Aachen, 52074, Germany