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Influence of two dynamic predictive clothing insulation models on building energy performance

Creative Commons 'BY' version 4.0 license
Abstract

In the HVAC system energy simulation, indoor thermal comfort condition is typically calculated based on the assumption that the clothing insulation is equal to a constant value of 0.5 clo during the cooling season and 1.0 clo during heating season. In reality, occupants frequently adjust their clothing depending on the thermal conditions, as opposed to the assumption of constant clothing insulation, indicating that the clothing variation should be captured during the building simulation to realistically model HVAC systems. In this study, the impact of the two newly developed predictive clothing insulation models on the HVAC system operation and energy consumption is quantitatively assessed using the detailed whole-building energy simulation program, EnergyPlus. The first model varies the clothing insulation as a function of outdoor air temperature measured at 6 am and the second model takes into account both 6 am outdoor air temperature and indoor operative temperature when adjusting the clothing insulation. The results of the typical assumption of the constant clothing insulation values were compared to those of the two predictive clothing models. It turned out that more accurate prediction of variations in clothing lead to an increase in the heating energy consumption. This is due to the fact that occupants took less clothing compared to the typical assumption of constant clothing value of 1.0 during the heating season. 

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