KICk-StARtER-G
(AI-based controller for comfort-based control of thermal systems and control loops to increase the energy and resource efficiency of buildings)
In the BMBF-funded research project an AI-based controller for comfort-based control of thermal systems and control loops to increase the energy and resource efficiency of buildings (acronym KICk-StARtER-G) is being developed.
The project’s main innovation lies in the multidimensional optimization through the combination of hardware and software components with new intelligent and predictive methods for building control using machine learning (ML). Telemetry data from the Energy Efficiency Center (EEC, headquarter of the CAE), additional sensor data, a digital twin model of the building and weather forecasts are used to determine set-points for controlling heating and cooling, sun shading devices and artificial lighting and fed back into the EEC's existing building automation system. By correlating data and input commands with feedback from the building's users, the control and forecasting algorithms can be continuously improved to ensure that the building is highly energy efficient and comfortable at the same time.
By providing immediate energy saving potentials in building operation, the envisioned software-as-a-service & hardware solution can be transferred to other buildings, contributing to a sustainable energy transition.
Funding body: BMBF, funding code: 01|S23003A
Duration from 01.03.2023 to 28.02.2026
