Associated Use of Design of Experiments in Numerical Energy Simulation for Energy Use Optimization in Residential Buildings

This article investigates the optimization of energy consumption in residential buildings. The research begins by modelling a representative building configuration (F3) aligned with the Technical Regulatory Document (DTR C3.2/4) standards for heating and cooling. Dynamic thermal simulations assess its performance; while key input factors and their variation ranges are identified. A Design of Experiments (DOE) matrix streamlines simulations, and Analysis of Variance (ANOVA) identifies critical parameters. These parameters inform polynomial models to predict energy demands under various conditions. The findings reveal that in Algeria’s hot-summer Mediterranean climate, roof and wall U-values and operative temperature significantly influence heating loads, while operative temperature, wall U-value, and Solar Heat Gain Coefficient (SHGC) are the dominant factors affecting cooling loads. Optimal solutions could reduce heating demand by 37–59.6% and cooling demand by 10–26%. These results suggest that the proposed methodology could be effectively integrated into the 2025–2030 national housing program to enhance energy performance and support CO2 emissions reduction in alignment with the country’s Nationally Determined Contributions (NDCs).