Conference Paper

Proceedings of BSA Conference 2024: Sixth Conference of IBPSA-Italy

Achieving a Deeper Understanding of User-Related Influences on Artificial Lighting Energy Demand Using High-Performance Computing

Sascha Hammes, Johannes Weninger, Philipp Gschwandtner, Philipp Zech

DOI: https://doi.org/10.13124/9788860462022_46
Abstract: Occupancy behaviour, including presence at the workplace, has a significant influence on a building's energy requirements. However, modelling occupancy behaviour is complex, multidisciplinary, and stochastic rather than deterministic. As little information about the intended use is available during the building planning phase, general assumptions about occupancy behaviour are made during building simulation and system planning, based on empirical and standardised models. However, these are formulated as generally as possible to achieve the broadest possible applicability. For example, despite improved simulation techniques, assumptions about occupant behaviour in the workplace often lead to deviations from the real situation, i.e. energy performance gaps. A better understanding of the factors that influence occupant behaviour, their weighting, and the improved models derived from them are proving to be crucial for eliminating performance gaps. Using advanced statistical methods and High-Performance Computing, representative samples of potential scenarios were created in this study to fully quantify the impact on energy performance. This was based on minuteby-minute occupancy and energy data from a one-year series of measurements in an open-plan office of Bartenbach, Austria. This research, based on High-Performance Computing, presents a breakdown of organisational and individual factors influencing energy-related occupancy behaviour. The results provide a promising basis for future research and pave the way for more targeted and energyefficient building planning.
Pages: 371 - 378
Paper: