关键词: 实时供热量, 辨识模型, 热负荷, 农宅, 寒冷及严寒地区

Abstract: Heating systems in rural residential buildings within cold and severe cold regions face dual challenges of economic and environmental sustainability. This study proposes a real-time heating capacity identification model for rural residences based on energy conservation principles. The model comprehensively considers instantaneous heat gain and transfer through building envelopes, indoor air thermal variations, and air infiltration loads. When applied to three rural residences in North China and Northeast China, physical parameters were calibrated using measured data from non-heating seasons. Post-calibration results showed that the model's prediction errors for instantaneous indoor temperature remained below 6.45% for root mean square error (CVRMSE), 3.31% for mean bias error (MBE), and 8.72% for range-normalized root mean square error (RN_RMSE). Analysis of heating season data using the calibrated model revealed significant differences in peak heat supply between Northeast China and North China, reaching a maximum disparity of 72.2 W/m². Furthermore, a 1℃ reduction in indoor temperature decreased heat supply by 12.45% in Northeast China and 12.85% on average in North China, demonstrating the critical importance of predicting real-time heat demand under varying temperature conditions for effective heating regulation in rural residences.

Key words: real-time heating capacity, identification model, heating load, rural residence, cold and extremely cold regions