Development of a model predictive control system

Buildings can and must make a significant contribution to the medium-term conversion of energy systems to renewable energies. In the context of smart cities, buildings are not only energy consumers but also energy suppliers and provide energy storage. Certain concepts relating to the thermal storage capacity in buildings (component activation) are suited to these applications. In office buildings, component activation has been used for some time. However this technology is rarely used in residential construction and especially not in densely populated residential buildings, but in these applications it can be applied very effectively with active and passive solar measures and can be implemented with low investment costs when compared with conventional heating systems. Especially in urban areas such a system has high potential. Through widespread use in residential buildings, residential quarters could be created that require almost no additional thermal energy and do not cause any large energy peaks. The overall aim of the research project is therefore to achieve wider use of component activation in combination with renewable energy and predictive control in densely populated residential buildings. The immediate goal is the presentation of the optimal interaction of active and passive solar energy as well as geothermal heat with heat pumps and component activation by modeling and validation on a built object, with the aim to optimize the results for upscaling in a large-volume residential building. The interaction of passive (irradiation in the building) and active (building-integrated photovoltaics) solar energy use as well as geothermal energy use in conjunction with a predictive (weather-data-based) controll system will be analyzed in relation to component activation as a load shifting tool, in order to achieve optimal system behavior. The concept will subsequently be implemented in a built object. Within the scope of the project, the simulated values will be compared with the measured values and thus the model will be validated and adapted accordingly. Through this validation as well as the simultaneous optimization of the lifecycle costs, the energetic and economic potentials of these systems are to be recorded, optimized and displayed (multi-criteria optimization). The broad application of the research results can be achieved on the one hand by upscaling the developed building concept on different building types and on the other by a subsequent implementation project in a densely populated large-volume residential building. It is planned that the research results of the project will be incorporated into the planning of a demo residential building with about 300 residential units in Seestadt Aspern. In addition, a guideline for the planning and execution of the system in different building types will be created in order to enable cost-optimized component activation with solar energy and predictive control.