A Model Integrating Theory and Simulation to Establish the Link Between Outdoor Microclimate and Building Heating Load in High-Altitude Cold Regions

The heating load of residential buildings is closely related to the local microclimate. However, there is a lack of quantitative indicators for assessing the impact of the outdoor microclimate on building heating loads in Lhasa residential buildings. This study established an analytical relationship between surface temperature and building heating load through theoretical derivation. Simulations of the outdoor microclimate and building surface temperatures were conducted using Phoenics2019 and Ladybug1.8.0 tools. Statistical models were developed to correlate outdoor microclimate parameters with the surface temperatures of both transparent and opaque building envelopes. Ultimately, these individual models were integrated to form a comprehensive framework for directly calculating heating loads from microclimate data. The model validation results indicate that the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) is 12.87%, which meets the ASHRAE Guideline 14 international standard requirement of ≤30% for hourly data. The Normalized Mean Bias Error (NMBE) is –9.76%, also satisfying the ASHRAE Guideline 14 criterion of ±10% for hourly data. These results suggest that the model exhibits a minor underestimation, which is acceptable from an engineering perspective. The proposed model can provide a quantitative reference to a certain extent for the comprehensive evaluation of outdoor microclimate environmental performance in residential buildings in Lhasa.