This article describes the Buildings library, a free open-source library that is implemented in Modelica, an equation-based object-oriented modelling language. The library supports rapid prototyping, as well as design and operation of building energy and control systems. First, we describe the scope of the library, which covers heating, ventilation and air-conditioning systems, multi-zone heat transfer and multi-zone airflow and contaminant transport. Next, we describe differentiability requirements and address how we implemented them. We describe the class hierarchy that allows implementing component models by extending partial implementations of base models of heat and mass exchangers, and by instantiating basic models for conservation equations and flow resistances. We also describe associated tools for pre- and post-processing, regression tests, co-simulation and real-time data exchange with building automation systems. The article closes with an example of a chilled water plant, with and without water-side economizer, in which we analysed the system-level efficiency for different control setpoints.

Real-time flow simulation is crucial for emergency management in buildings, such as fire and accidental or intentional release of chemical/biological agents (contaminants). The simulation results can then be used to impose proper measures to minimize casualties. Computational fluid dynamics (CFD) is accurate, but too time-consuming. Nodal models are fast, but not informative. To obtain a quick and informative solution, this study proposes an intermediate approach between nodal models and CFD by introducing a fast fluid dynamics (FFD) method. This investigation used the FFD methods with and without turbulence treatments to study systematically four basic flows in buildings, and compared the numerical results with the corresponding CFD results and the data from the literature. The results show that, on one hand, the FFD can offer much richer flow information than nodal models, but less accurate results than CFD. On the other hand, the FFD is 50 times faster than the CFD. The results also show that the FFD with the laminar assumption has the best overall performance as regards both accuracy and speed. It is possible to conduct faster-than-real-time flow simulations with detailed flow information by using the FFD method. The paper introduces a fast fluid dynamics (FFD) method, which can simulate airflow and contaminant dispersion in buildings with real-time or faster-than-real-time speed and provide informative solutions. As an intermediate approach between nodal models and the computational fluid dynamics (CFD), the FFD can be a very useful tool for emergency management in case of fire and accidental or intentional release of chemical or biological agents in a building or around the buildings. The FFD can also be used as a preliminary test tool for quick assessment of indoor airflows before a detailed CFD analysis.

This article describes the development and implementation of the functional mock-up unit (FMU) for co-simulation import interface in EnergyPlus. This new capability allows EnergyPlus to conduct co-simulation with various simulation programs that are packaged as FMUs. For example, one can model an innovative Heating, Ventilation, and Air Conditioning (HVAC) system and its controls in Modelica, export the HVAC system and the control algorithm as an FMU, and link it to a model of the building envelope in EnergyPlus for run-time data exchange. The formal of FMUs is specified in the functional mock-up interface (FMI) standard, an open standard designed to enable links between disparate simulation programs. An FMU may contain models, model description, source code, and executable programs for multiple platforms. A master simulator – in this case, EnergyPlus – imports and simulates the FMUs, controlling simulation time and coordinating the exchange of data between the different FMUs. This article describes the mathematical basis of the FMI standard, discusses its application to EnergyPlus, and describes the architecture of the EnergyPlus implementation. It then presents a typical workflow, including pre-processing and co-simulation. The article concludes by presenting two use cases in which models of a ventilation system and a shading controller are imported in EnergyPlus as an FMU.