The proposed energy concept of HiLo targets zero emissions in operation, high efficiency and full integration of system components into structural elements, leveraging their specific attributes.
All the systems for interior climatization as well as energy harvesting are controlled by a building automation system to optimally balance the system performance and user preferences. Novel user-centred approaches are applied that use methods of machine learning and adaptation under real-life operational conditions (SuAT).
In one of the previous projects on lighting comfort, we demonstrated the necessity of dynamically-adapted lighting levels in order to achieve both comfort and energy savings.
We estimated the individual occupancy information from passive infrared (PIR) motion sensors and detected the light levels. Using this information we set an automatic lighting control system which dynamically adapts lighting levels in order to achieve both comfort and energy savings.
Figure 1. The HPZ building (SUAT Offices) at the ETH Hönggerberg campus was the study location.
Figure 2. The floorplan of the HPZ building. Red dots indicate sensor locations.
Figure 3. Adaptive light level and time delay thresholds in each office. The time delays are the periods between the last time motion was detected and the lights were turned off by the control system and they are given as a function of the probability that nobody is in the room and that the system has taken the appropriate action.