The overall project EEBF utilizes methods from the fields of data analytics and non-linear model predictive control (NMPC) for a holistic supervisory control of residential buildings. This supervisory control monitors the energy flows in the building and predictively optimizes them in real-time with regard to user comfort, energy consumption and costs. The expected benefits for the occupant are the increase in comfort, significant savings in CO2 and energy costs as well as improved possibilities for tenant electricity models. Load prediction and real-time supervisory control also enable energy suppliers to flexibilize primary energy use and to harmonize grid load.
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