Indoor Overheating and Comfort-Oriented Heating Demand Reduction in Residential Buildings Across China’s Severe Cold Regions

High indoor temperatures during the heating season increase the indoor–outdoor temperature difference and lead to additional heating demand in residential buildings in severe cold regions. However, the quantitative relationship between measured overheating and the potential for optimizing heating temperatures remains unclear. This study investigated case study dwellings in Ulanhot, Xilinhot, and Hailar using field measurements and EnergyPlus simulations to characterize indoor thermal conditions during the heating season and estimated the reduction in heating demand under comfort-oriented temperature adjustments. The results show that all primary occupied spaces exhibited elevated temperatures to varying degrees. The mean bedroom temperature in Xilinhot was 28.03 °C, and the temperature exceeded 28 °C for 63.89% of the monitored time. In Hailar, the mean temperatures in the living room and bedroom were 27.35 °C and 27.78 °C, respectively, and the corresponding time fractions above 26 °C were 90.21% and 95.57%. Under standardized prototype dwelling conditions, heating demand increased continuously with the setpoint temperature. Increasing the setpoint from 18 °C to 26 °C raised seasonal area-normalized heating demand from 64.14–98.18 to 103.39–143.50 kWh m−2 across the three cities. Reducing an overheating setpoint of 26 °C to 20 °C lowered seasonal heating demand by 23.94–28.94%; adjusting the measured temperature reference scenarios to 20 °C produced reductions of 24.49–33.60%. The district heating emission factor scenarios further showed that, when 20 °C temperature optimization was combined with the low-coal emission parameters, seasonal area-normalized operational carbon emissions decreased by 57.22–60.03% relative to the 2020 26 °C baseline. These findings indicate that comfort-oriented heating temperature adjustment can effectively reduce residential heating demand in severe cold regions and provide quantitative support for temperature optimization, refined control, and low-carbon operation in district-heated dwellings.