The increasing world population has led to a significant increase of energy consumption in the building sector in recent years. Reasons are manifold. They mainly include increased thermal comfort requirements for the building occupants. Higher thermal comfort implies higher needs for the buildings' heating, ventilation and air-conditioning (HVAC) systems at their peak levels. This operation eventually entails the risk of load peaks, which increases risks for electric black-outs. Demand side management (DSM) is an established concept for buildings, which includes the optimal shifting of potential loads to time periods such that peak loads can be prevented effectively. The concept thus provides that electric and thermal storage potentials are exploited adequately. Further development should enforce the use of renewable energy sources, which offers another possibility to efficiently reduce the risks of potential load peaks. Mathematical modeling of HVAC systems is an established approach to understand the system behavior and to trigger plans and strategies on how to tackle the HVAC system controls in order to recognize potentials and consequently perform efficient load shifting in an automated way. Model based control concepts endorse the systematic and transparent approach towards automated load shifting. This paper presents the methodology for the design of a model based predictive control concept for load shifting in the non-residential building sector. The methodology includes the mathematical modeling of the HVAC systems and the loads of a passive house standard non-residential building. The concept for the model based predictive controller is developed upon a simplification of the plant model.
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