Abstract

User behaviour can significantly affect indoor thermal comfort conditions, as well as energy consumption, especially in existing buildings with high thermal masses where natural cross ventilation is the main strategy to reduce cooling loads. The aims of this paper were: (i) to compare how behavioural changes evaluated by means of rule-based and stochastic models lead to changes in indoor thermal comfort levels, and (ii) to define the patterns of indoor thermal comfort in historic residential buildings in future scenarios. To this end, a historic building located in Molfetta (Southern Italy) was analysed using a dynamic energy simulation engine in five weather scenarios (Typical Meteorological Year, current extreme weather file 2018, predicted weather files for 2020, 2050, and 2080 generated by morphing method), and stochastic and rule-based models for window openings were adopted and compared. The results showed that the stochastic model was more accurate than the rule-based one, resulting in a reduction of discomfort conditions during the summer period between 30% and 50% in all climate scenarios. However, although the differences between predicted discomfort levels using rule-based and stochastic models tended to increase, discomfort levels still appeared to be not acceptable in the 2050 and 2080 scenarios due to the rising temperature driven by climate change.

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