Work

Multi-objective optimization approaches for enhancing building energy efficiency through material and equipment selection

Year: 2025

Type: article

Abstract: Improving building energy efficiency is crucial to reducing residential electricity demand and mitigating environmental impacts. Previous studies have largely examined either building envelope or HVAC system parameters independently, without fully quantifying their combined parametric influence on air-conditioning (AC) loads. In particular, the integrated effect of envelope materials (walls, glazing, roof insulation, infiltration) together with equipment-related factors (coil bypass factor and cooling coil supply temperature) has not been systematically investigated using multi-objective optimization frameworks. This study aims to optimize both cooling and heating loads in a typical residential apartment by simultaneously analyzing nine critical design and system parameters. A Taguchi-based L27 orthogonal array was employed, and simulations were conducted in HAP 4.90. Multi-objective optimization was performed using Grey Relational Analysis (GRA) and the Weighted Aggregated Sum Product Assessment (WASPAS) methods. Analysis of Variance (ANOVA) quantified the contribution of each parameter. The optimal configuration was identified as autoclaved aerated concrete (AAC) walls, 10% window-to-wall ratio (WWR), double-shaded glazing (U = 1.6 W/m 2 ·K, SC = 0.4), and 75 mm mineral wool roof insulation. Maintaining 0.5 air changes per hour (ACH) air infiltration, a coil bypass factor (CBF) of 0.1, and a cooling coil supply temperature (CCST) of 14 °C further minimized thermal loads. Wall material emerged as the most dominant factor, contributing 68.51% (GRA) and 71.81% (WASPAS). Annual energy savings of up to 48% were achieved compared with baseline configurations. This study establishes a robust optimization framework integrating envelope and HVAC design variables, offering practical guidelines for architects and engineers. By quantifying both individual and combined parametric effects, the research provides differentiated insights that go beyond existing studies and supports climate-responsive residential building design.

Source: Case Studies in Thermal Engineering

DOI: 10.1016/j.csite.2025.107209