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Occupant behavior and thermal comfort in buildings: monitroing the end user

Author: Visser, L. · Kingma, B.R.M. · Willems, E. · Loomans, M. · Schellen, H. · Broers, W. · Veld, P. op 't · Marken Lichtenbelt, W. van
Type:article
Date:2019
Source:Tanabe, S.I.Zhang, H.Kurnitski, J.Gameiro da Silva, M.C.Nastase, I.Wargocki, P.Cao, G.Mazzarela, L.Inard, C., E3S Web of Conferences, 13th REHVA World Congress, CLIMA 2019, 26 May 2019 through 29 May 2019, 111
Identifier: 868636
doi: doi:10.1051/e3sconf/201911104056
Article number: 04056
Keywords: Thermal comfort · Ambient conditions · Biophysical model · Energy performance · Monitoring periods · Occupant behaviour · Operative temperature · Skin temperatures · Thermoregulatory · Behavioral research

Abstract

Studies indicate that the energy performance gap between real and calculated energy use can be explained for 80% by occupant behaviour. This human factor may be composed of routine and thermoregulatory behaviour. When occupants do not feel comfortable due to high or low operative temperatures and resulting high or low skin temperatures, they are likely to exhibit thermoregulatory behaviour. The aim of this study is to monitor and understand this thermoregulatory behaviour of the occupant. This is a detailed study of two females living in a rowhouse in the city of Heerlen (Netherlands). During a monitoring period of three weeks over a time span of three months the following parameters were monitored: activity level, clothing, micro climate, skin temperatures and thermal comfort and sensation. Their micro climate was measured at five positions on the body to assess exposed near body conditions and skin temperature. Every two hours they filled in a questionnaire regarding their thermal comfort and sensation level (7-point scale), clothing, activities and thermoregulatory behaviour. The most comfortable (optimal) temperature was calculated for each person by adopting a biophysical model, a thermoneutral zone model. This study shows unique indivual comfort patterns in relation to ambient conditions. An example is given how this information can be used to calculate the buildings energy comsumption.