From static metrics to multi-objective parametric optimization: enhancing the performance of semi-arid residential buildings through the Hourly Thermal Comfort Index

Energy consumption and thermal comfort remain pivotal global challenges that directly impact the quality of residential life and habitat sustainability. This research develops a numerical model to predict the thermal behavior of residential buildings through a comprehensive parametric analysis, focusing on windows as critical elements in energy exchange. A wide range of variables was evaluated, including insulation deficiencies, material properties, glazing types, window-to-wall ratio (WWR), solar shading devices, floor levels, and operational factors such as family size and lighting loads. The study was conducted on a residential facade in Batna, Algeria – a warm, semi-arid climate. Thermal comfort was assessed by monitoring ambient temperatures and correlating them with the Hourly Thermal Comfort Index (HTCI) in accordance with ASHRAE 55 standards. To ensure objective accuracy, the study focused on a field-based sample of five residents living in southwest-oriented units. The findings, which maximize thermal performance using the "Galapagos" evolutionary algorithm, show that single glazing significantly degrades comfort levels. In contrast, advanced configurations – combining double or triple low-E glazing with horizontal shading – increased the comfort index from a baseline of 55.54% to over 77% for the southwest orientation. By providing a precise hourly analysis (HTCI) that captures instantaneous thermal fluctuations, this study addresses the limitations of traditional static assessments. These findings establish a framework for future research that integrates in situ measurements with occupant surveys, effectively bridging the gap between objective performance and subjective experience to achieve a holistic understanding of thermal challenges in real-world residential environments.