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Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance

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  • Piselli, Cristina
  • Pisello, Anna Laura

Abstract

Given the massive scientific progress on near zero-energy targets, occupant behavior has become a key variable affecting building energy performance. In this view, the paper builds upon previous contributions to analyze real occupancy of an office building with peer occupants monitored for 2 years. After assessing that peers do not behave the same and do not control equivalently the indoors, acknowledged occupancy models and field-collected data are compared through dynamic simulation on daily and annual bases. To this aim data-driven occupancy models are developed based on the collected data. Moreover, neural response tests are performed on selected occupants to study their emotional status. The estimation of annual energy need highlights the influence of building occupancy. In fact, the simulated building energy consumption can vary by up to 20% by only selecting the occupancy simulation scheme. Moreover, non-negligible discrepancies in terms of value gap and time schedule daily profiles are still found between predicted and measured variables when considering the data-driven models, since they do not take into account multi-physical and non-physical (personal) stimuli. The first results of neural experiment show the role of personal non-physical factors in the inconsistent reaction to thermal stimuli, as key driver for the associated behavior.

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  • Piselli, Cristina & Pisello, Anna Laura, 2019. "Occupant behavior long-term continuous monitoring integrated to prediction models: Impact on office building energy performance," Energy, Elsevier, vol. 176(C), pages 667-681.
    • Handle: RePEc:eee:energy:v:176:y:2019:i:c:p:667-681
    DOI: 10.1016/j.energy.2019.04.005
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