02 May 2022
The Information Gap in Occupant-Centric Building Operations: Lessons Learned from Interviews with Building Operators in Germany
Differences in building operator strategies can significantly affect building energy use and occupant comfort. However, it seems that the daily work of building operators and facility managers is still largely based on heuristics and individual experiences. In this work, we have investigated the current data collection methods during the operation and its daily use in buildings as well as the handling of occupant behavior, comfort, and user complaints based on interviews with ten building operators in Germany. These interviews were conducted as part of an international study of building operator OCC (Occupant-Centric Control) strategies, under the auspices of the IEA EBC Annex 79. The results of the interviews clearly reflect, that until now, communication between building operators and building occupants plays a more important role in optimizing or adjusting building operations to meet occupant needs than the data collected by BAS, which is mainly used to detect faults and check the system status of key HVAC components when faults occur. In some cases, the real-time data are applied for the adjustment of set points and schedules depending on measured conditions; however, customization of set points considering the user’s preferred temperature or ventilation rate or building operation based on occupancy detection has not yet been implemented in the considered buildings. The overall objective of this contribution to building operation research is to highlight best practices and identify white spaces that fulfill occupant requirements and achieve a high level of energy-efficiency. The presented findings identify current gaps between science and practice in the field of sustainable optimization of building operation, but also point out real-world starting points for future research and development.
Munich University of Applied Sciences, CENERGIE—Center for Energy Efficient Buildings and Districts, Munich, Germany
Kane, Michael B.
Northeastern University, Department of Civil and Environmental Engineering, Boston, MA, United States
EnOB: DataFEE - Data mining, machine learning, feedback, and feedforward - Energieeffizienz durch nutzungszentrierte Gebäudesysteme
EnOB: NuData Campus - Nutzungsdaten basierte Optimierung von Gebäuden und Anlagen am Beispiel der Hochschule München
Fraunhofer-Verbund Werkstoffe, Bauteile – Materials