Advanced modeling and simulation methods for assessment and optimization of indoor climate

The present study aims at illustrating the possibilities arising from zonal models for detailed assessment of indoor climate in co-simulation setups. By subdividing a room into several volumes, zonal models are able to provide increased accuracy compared to single node models. At the Fraunhofer Institute for Building Physics (IBP) a model with these characteristics was developed that allows for proper representation of air movement due to forced and free convection as well as computation of detailed radiation heat transfer based on view factor calculation. While the zonal model allows for detailed investigation of the indoor thermodynamics, external influences like systems for window shading cannot be considered yet. To investigate their impact, the integration of corresponding simulation models can be realized based on the Functional Mock-Up Interface (FMI). FMI is a tool independent standard for model exchange and co-simulation. In this work, the master platform to orchestrate the zonal model and further FMUs is developed in Python. The coupling allows for quantifying the consequences of external influences on the indoor climate. The modular nature of the proposed simulation framework enables seamless exchange of FMUs to automatically optimize not only continuous parameters but also structural alternatives by means of system components. To exemplify the procedure, a monitored building serves as a reference for the generation of a detailed indoor climate simulation. Data from extensive monitoring was used to validate the physical model. A proposed simulation framework is the basis for the investigation of various window and shading systems co-simulated in Energy Plus using the FMI.