Abstract

Household room air conditioners (RACs) are widely used in residential buildings to maintain an indoor thermal climate in China’s hot summer and cold winter (HSCW) zone. The aggregate utilization of RACs in a region has a great impact on regional energy demand in both the heating and cooling seasons. Classifying household RAC users and identifying their RAC usage demands will contribute to better balanced regional energy management for building energy flexibility. In this study, a data-driven method was proposed to classify the household RAC user groups at the regional level, using running time as an indicator. The results showed that RAC users could be classified into four groups with different RAC usage demands. The Lower Class was determined by the absolute poverty line with the Gini coefficient. In addition, the Upper Class was distinguished through the determination of the scaling region in power-law distribution. At the same time, the similarities and differences between different classes in monthly and hourly periods and the flexibility potential were discussed. The rigid demand was observed in the monthly periods of June, July and August and during the hourly periods of 21:00–22:00 in both the bedroom and living-room.

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