4.6 Article

Influence of Complex Occupant Behavior Models on Cooling Energy Usage Analysis

Journal

SUSTAINABILITY
Volume 13, Issue 3, Pages -

Publisher

MDPI
DOI: 10.3390/su13031243

Keywords

complex occupant behavior; co-simulation; behavior sequence; cooling energy; residential building

Funding

  1. National Research Foundation of Korea (NRF) - Korea government (Ministry of Science and ICT) [2019R1C1C1010956]
  2. National Research Foundation of Korea [2019R1C1C1010956] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study analyzed the effects of applying single and complex behavior models on simulation results of residential buildings, focusing on two interconnected occupant behaviors - window opening and closing, and air conditioner usage. The results highlighted the importance of complex behavior models in predicting actual energy consumption, helping identify gaps between reality and existing simulation methods for energy consumption analysis. The study aims to guide future researchers studying occupant behavior.
The behavior of building occupants has been studied by researchers for building control as well as for predicting energy use. In this study, we analyzed the effect of the application of single and complex behavior models on the simulation results of residential buildings. Two occupant behaviors-window opening and closing and air conditioner (AC) usage-were simulated, which are known to be interconnected. This study had two purposes: The first was to integrate data analysis tools (R in this study) and building simulation tools (EnergyPlus in this study) so that two behaviors with interconnectivity could be reflected in building simulation analysis. The second purpose was to apply the behavior models in residential buildings to an integrated simulation environment in stages to analyze their relative influence on the building energy and indoor environment. The results of the study prove that the application of complex behavior is important for research regarding the prediction of actual energy consumption. The results help identify the gap between reality and the existing simulation methods; thereby, they can help improve methods related to energy consumption analysis. We hope that this study and its results will serve as a guide for researchers looking to study occupants' behavior in the future.

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