Platform-independent modeling of control and regulation logic for detailed study of building automation systems involving construction and building technology.
The result enables the analysis of energy saving potentials through building automation before construction.
Plus-plus-energy buildings have already been implemented in practice in various forms, but many projects have shown that their actual energy consumption is higher than the originally planned consumption.
Since every kilowatt-hour of energy not consumed contributes to achieving the goal of “climate neutrality”, buildings with well-designed and perfectly operating building automation systems are needed to ensure optimal building performance. Otherwise highly efficient buildings can result in unnecessary additional energy consumption of up to 54%. In order to be able to design the building automation - in particular the control and regulation logic - for optimal operation in advance, it is necessary that it is developed on the basis of a digital, simulation-capable representation (digital twin). All relevant aspects of the building (control logic, utilization information, geometry, structural engineering and building services engineering) should be mapped in various degrees of detail - from simplified to very detailed - in order to ensure target-oriented planning.
In the project, a method for platform-independent modeling of the control and regulation logic will be created and integrated into an open data model. This allows the control logic to be linked to the components and parameters of building models already in the planning phase and over the entire building life cycle. For a proof-of-concept, the IT ecosystem SIMULTAN is used, which provides a platform for existing open data models such as IFC (ISO 16739) and BACNET (ISO 16484).
Based on this, interfaces are methodically developed to transfer the platform-independent modeled control logic into platform-specific solutions (e.g. simulation tools, engineering tools). The practical suitability of the methodology is demonstrated by application in a laboratory scenario.