Incorporating Occupant cooling behaviors into novel thermal comfort models for residential demand response

During periods of electricity demand response (DR) in residential buildings, inhabitants frequently engage in supplementary cooling behaviors, extending beyond the utilization of air conditioning (AC). However, the prevalent thermal comfort models, namely the Predicted Mean Vote (PMV) and Temperature Range Method (TRM), which are typically employed during DR periods, are designed for stable environments and do not consider the impact of these additional cooling behaviors. This study aims to develop novel thermal comfort models that more accurately reflect these behaviors during residential DR periods. The initial stage of the study involved a questionnaire survey conducted among residents in Zhengzhou, China, to investigate the AC usage patterns and additional cooling behaviors. Subsequently, typical AC DR strategies, which include increasing indoor temperature set points and turning off AC, along with the three most comment additional cooling behaviors, namely utilizing an electric fan, reducing clothing and consuming cold beverages, were examined through multi-scenario experiments. The findings from these experiments facilitated the development of two novel models: the PMV-DR model, indicative of the thermal comfort level, and the TRM-DR model, representative of the thermal comfort acceptance rate (AR) during the DR period. When compared with the traditional PMV and TRM models, these newly proposed models demonstrated greater consistency with the experimental results. As a result, these models could serve as the basis for thermal comfort evaluations during residential DR periods in the Zhengzhou region. Furthermore, they could provide a methodological benchmark for other geographical locales.