With the advancement of building energy efficiency simulation technology, sensitivity analysis has become increasingly important in optimizing architectural design. This study examines typical rural dwellings in the Beijing–Tianjin–Hebei region, using Regional Sensitivity Analysis (RSA) to assess how design parameters affect energy consumption, carbon emissions, costs, and thermal comfort. Eleven parameters were analyzed through 1,000 simulations, including insulation type, envelope geometry, and photovoltaic configuration. Eave depth showed the highest sensitivity for all metrics, while roof insulation thickness and PV panel angle strongly influenced thermal performance and cost. The study also applies an RSA workflow to mixed continuous and categorical variables, with binning adjustment improving sensitivity results for discrete parameters. Based on sensitivity findings, differentiated optimization strategies were proposed: prioritizing passive shading and roof insulation for comfort optimization, while focusing on PV system scale for carbon emission and cost control. This study provides quantifiable evidence for low-carbon, efficient, and comfortable design in rural buildings.
Wu et al. (Mon,) studied this question.
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