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).

Keywords: Design of experiment (DOE), U-value, Heating, Cooling, National Determined Contributions (NDCs).

[1] International Energy Agency IEA, Buildings - Energy System, https://www.iea.org/energy-system/buildings, (accessed 1 Dec. 2024).
[2] Ministère de l’énergie, https://energy.gov.dz, (accessed 31 Oct. 2024).
[3] Programme De Développement Des Nations Unies, Elaboration de la Troisième Communication Nationale et du Premier Rapport Biennal de l’Algérie auprès de la CCNUCC, https://www.undp.org/fr/algeria/projets/elaboration-de-la-troisieme-communication-nationale-et-du-premier-rapport-biennal-de-lalgerie-aupres-de-la-ccnucc, (accessed 20 May 2024).
[4] J.K. Telford, A brief introduction to design of experiments, Johns Hopkins APL Tech. Dig. 27 (2007) 224–232.
[5] Z. Romani, Développement d’une méthode d’aide à la décision multicritère pour la conception des bâtiments neufs et la réhabilitation des bâtiments existants à haute efficacité énergétique, PhD Thesis, Université de La Rochelle, Université Abdelmalek Essaâdi, 2015.
[6] A.N. Sadeghifam, S.M. Zahraee, M.M. Meynagh, I. Kiani, Combined use of design of experiment and dynamic building simulation in assessment of energy efficiency in tropical residential buildings, Energy Build. 86 (2015) 525–533.
[7] J. Xu, J.H. Kim, H. Hong, J. Koo, A systematic approach for energy efficient building design factors optimization, Energy Build. 89 (2015) 87–96.
[8] H. Belahya, A. Boubekri, A. Kriker, A fast evaluation method for energy building consumption based on the design of experiments, IOP Conf. Ser.: Earth Environ. Sci., IOP Publishing, 2017.
[9] L. Bentoumi, T. Bouacida, R. Bessaih, A. Bouttout, Impact of thermal insulation on energy consumption in buildings, J. Therm. Eng. 10 (2024) 924–935.
[10] The Algerian Regulatory Technical Document C3.2/4.
[11] N. Meftah, Z.L. Mahri, Analysis of Algerian energy efficiency measures in buildings for achieving sustainable development goals, J. Renew. Energ. (2021) 37–44.
[12] S. Semahi, M.A. Benbouras, W.A. Mahar, N. Zemmouri, S. Attia, Development of spatial distribution maps for energy demand and thermal comfort estimation in Algeria, Sustainability 12 (2020) 6066.
[13] S. Rahmouni, R. Smail, A design approach towards sustainable buildings in Algeria, Smart Sustain. Built Environ. 9 (2020) 229–245.
[14] K.E.B. Djebbar, S. Salem, A. Mokhtari, A multi-objective optimization approach of housing in Algeria. A step towards sustainability, Urban. Arhit. Constr. 9 (2018) 131.