The integration of renewable electrical energy sources and the increase of these sources in the future pose a major challenge to the stabilisation of the electricity grid. For example, in the absence of sun or wind, there will be a greater fluctuation of the power on the grid ('duck curve'). Technical installations in all types of buildings that consume electricity may be able to shift their use in time and thus contribute to the stabilisation (the balance between supply and demand) of the grid. This flexibility could be offered on demand to the Balance Responsible Parties, the responsible party for balance on each access point on the energy network, which is known as Demand Response. In order to minimize the inconvenience to the user of the building due to the time shift in energy consumption on the one hand and to maximize flexibility on the other hand, a building can be made smart. The data generated here (e.g. occupancy, future occupancy, comfort ...) can be included in the optimisation feature that calculates the flexibility of the technical installation and takes into account the current and future use of the building given the known and expected use.
The research will focus on the possibility to determine the flexibility of the technical installations in buildings and then use them in demand response programs. For this purpose, data sent over the KNX bus will be used. The KNX bus data in combination with the knowledge of the current and future use of the building will define a Model Predictive Control scheme. This constraint driven controller mechanism will adjust the setting points of the installation in function of a cost function to be determined in the study, that will maximize the marketable flexibility and minimize the energy cost of the building.