Comprehensive improvement of energy efficiency and indoor environmental quality for university library atriumd—A multi-objective fast optimization framework

Abstract

Low-carbon, energy-saving, and health have become a common trend for the whole of mankind. However, how to balance the relationship between energy-saving and healthy indoor environment is a key issue for sustainable building development. This paper extracted the prototypical form of university library atrium based on 44 library cases in Wuhan. A methodology verified with measured data for evaluating building performance was constructed, and the synergistic influence of spatial morphology parameters on the building energy efficiency (BEE) and indoor environmental quality (IEQ) was analyzed. Finally, a multi-objective fast optimization framework coupled with machine learning algorithms was used to achieve the optimal design of university library atrium. The results showed that the parameters that influence the building energy consumption, indoor thermal comfort, daylighting performance most were the height-to-width ratio, the skylight solar heat gain coefficient, and the sidewall window-to-wall ratio, respectively. The machine learning models predicted performance 400 times faster than traditional performance simulations. And compared with the worst-performance scheme, the maximum optimization rate of building energy consumption, indoor thermal comfort, daylighting performance was 29.46%, 10.46%, and 65.56%, respectively. The multi-objective fast optimization framework could provide guidance for policy makers and architects to performance-based design in the early design stages of university library atrium.

Keywords

University library atrium / Spatial morphology / Building energy efficiency / Indoor environmental quality / Machine learning / Multi-objective optimization

References

[1] Ahmad, M.W. , Mourshed, M. , Rezgui, Y. , 2017. Trees vs Neurons:comparison between random forest and ANN for high-resolution prediction of building energy consumption. Energy Build. 147, 77- 89.

[2] Akkose, G. , Akgul, C.M. , Dino, I.G. , 2021. Educational building retrofit under climate change and urban heat island effect. J. Build. Eng. 40, 102294.

[3] Aldawoud, A. , 2013. The influence of the atrium geometry on the building energy performance. Energy Build. 57, 1- 5.

[4] Asadi, E. , Da Silva, M.G. , Antunes, C.H. , Dias, L. , Glicksman, L. , 2014. Multi-objective optimization for building retrofit: a model using genetic algorithm and artificial neural network and an application. Energy Build. 81, 444- 456.

[5] Asfour, O.S. , 2020. A comparison between the daylighting and energy performance of courtyard and atrium buildings considering the hot climate of Saudi Arabia. J. Build. Eng. 30, 101299.

[6] Bakmohammadi, P. , Noorzai, E. , 2020. Optimization of the design of the primary school classrooms in terms of energy and daylight performance considering occupants' thermal and visual comfort. Energy Rep. 6, 1590- 1607.

[7] Beyraghshamshir, M. , Sarkardehei, E. , 2023. A comparison of the cooling and heating performance of two passive systems of central courtyards and atriums at an elementary school in Yazd City. Sol. Energy 252, 156- 162.

[8] Candanedo, L.M. , Feldheim, V. , Deramaix, D. , 2017. Data driven prediction models of energy use of appliances in a low-energy house. Energy Build. 140, 81- 97.

[9] Carlucci, S. , Causone, F. , De Rosa, F. , Pagliano, L. , 2015. A review of indices for assessing visual comfort with a view to their use in optimization processes to support building integrated design. Renew. Sustain. Energy Rev. 47, 1016- 1033.

[10] Chen, Q. , 2009. Ventilation performance prediction for buildings: a method overview and recent applications. Build. Environ. 44 (4), 848- 858.

[11] Csutora, M. , Zsoka, A. , Harangozo, G. , 2021. The Grounded Surveye—An integrative mixed method for scrutinizing household energy behavior. Ecol. Econ. 182, 106907.

[12] Gagge, A.P. , Fobelets, A.P.R. , Berglund, L. , 1986. A standard predictive index of human response to the thermal environment. Build. Eng. 92, 709- 731.

[13] GB 50736-2016, 2016. Design Code for Heating Ventilation and Air Conditioning of Civil Buildings. Ministry of Housing and UrbanRural Development, PRC.

[14] GB50189-2015, 2015. Design Standard for Energy Efficiency of Public Buildings. Ministry of Housing and Urban-Rural Development, PRC.

[15] GB55015-2021, 2021. General Code for Energy Efficiency and Renewable Energy Application in Buildings. Ministry of Housing and Urban-Rural Development, PRC.

[16] Geng, G. , Geng, J. , Yin, H. , Wang, C. , Zhu, N. , 2020. Parametric design of atrium space energy efficiency for office building in severe cold region. J. Xi'an Univ. Archit. Technol. 6 (52), 895- 904.

[17] Hu, P. , Liu, W. , Jiang, Z. , 2006. Study on indoor thermal sensation of young college students in the area which is hot in summer and cold in winter. Int. J. Archit. Sci. 7.

[18] Guan, Z. , Xu, X. , Xue, Y. , Wang, C. , 2023. Multi-objective optimization design of geometric parameters of atrium in nZEB based on energy consumption, carbon emission and cost. Sustainability 15 (1), 147.

[19] Hu, S. Jiang, Y. Yan, D. , 2021. China Building Energy Use and Carbon Emission Yearbook 2021. China Architecture & Building Press, Beijing.

[20] IEA , 2023. Energy End-Uses and Efficiency Indicators Data Explorer.

[21] Jenssen, R. , Eltoft, T. , 2008. A new information theoretic analysis of sum-of-squared-error kernel clustering. Neurocomputing 72 (1), 23- 31.

[22] Kuang, W. , Liu, J. , Dong, J. , Chi, W. , Zhang, C. , 2016. The rapid and massive urban and industrial land expansions in China between 1990 and 2010: a CLUD-based analysis of their trajectories, patterns, and drivers. Landsc. Urban Plann. 145, 21- 33.

[23] Laouadi, A. , Atif, M.R. , Galasiu, A. , 2002. Towards developing skylight design tools for thermal and energy performance of atriums in cold climates. Build. Environ. 37 (12), 1289- 1316.

[24] Liu, G. , Ren, L. , Qu, G. , Zhang, Y. , Zang, X. , 2022. Fast prediction model of three-dimensional temperature field of commercial complex for entrance-atrium temperature regulation. Energy Build. 273, 112380.

[25] Liu, L. , Zhai, R. , Xu, Y. , Hu, Y. , Liu, S. , Yang, L. , 2024. Comprehensive sustainability assessment and multi-objective optimization of a novel renewable energy driven multi-energy supply system. Appl. Therm. Eng. 236, 121461.

[26] Lu, S. , Luo, Y. , Gao, W. , Lin, B. , 2024. Supporting early-stage design decisions with building performance optimisation: findings from a design experiment. J. Build. Eng. 82, 108298.

[27] Maamari, F. , Andersen, M. , de Boer, J. , Carroll, W.L. , Dumortier, D. , Greenup, P. , 2006. Experimental validation of simulation methods for bi-directional transmission properties at the daylighting performance level. Energy Build. 38 (7), 878- 889.

[28] Mohapatra, S.K. , Mishra, S. , Tripathy, H.K. , Alkhayyat, A. , 2022. A sustainable data-driven energy consumption assessment model for building infrastructures in resource constraint environment. Sustain. Energy Technol. Assessments 53, 102697.

[29] Nerurkar, P. , Shirke, A. , Chandane, M. , Bhirud, S. , 2018. Empirical analysis of data clustering algorithms. Procedia Comput. Sci. 125, 770- 779.

[30] Pan, J. , Li, N. , Zhang, W. , He, Y. , Hu, X. , 2022. Investigation based on physiological parameters of human thermal sensation and comfort zone on indoor solar radiation conditions in summer. Build. Environ. 226, 109780.

[31] Pang, J. , Fan, Z. , Yang, M. , Liu, J. , Zhang, R. , Wang, W. , Sun, L. , 2023. Effects of complex spatial atrium geometric parameters on the energy performance of hotels in a cold climate zone in China. J. Build. Eng. 72, 106698.

[32] Pérez-Lombard, L. , Ortiz, J. , Pout, C. , 2008. A review on buildings energy consumption information. Energy Build. 40 (3), 394- 398.

[33] Qin, R. , Yan, D. , Zhou, X. , Jiang, Y. , 2012. Research on a dynamic simulation method of atrium thermal environment based on neural network. Build. Environ. 50, 214- 220.

[34] Ratajczak, K. , Bandurski, K. , Płóciennik, A. , 2022. Incorporating an atrium as a HAVC element for energy consumption reduction and thermal comfort improvement in a Polish climate. Energy Build. 277, 112592.

[35] Reeves, T. , Olbina, S. , Issa, R. , 2012. Validation of building energy modeling tools: ecotect^TM, green building studio^TM and IES<VE&gt. In: Proceedings of the 2012 Winter Simulation Conference (WSC). IEEE, pp. 1-12.

[36] Stafford, T.M. , 2015. Indoor air quality and academic performance. J. Environ. Econ. Manag. 70, 34- 50.

[37] Šujanová, P. , Rychtáriková, M. , Sotto Mayor, T. , Hyder, A. , 2019. A healthy, energy-efficient and comfortable indoor environment, a review. Energies 12 (8), 1414.

[38] Tabadkani, A. , Valinejad, Shoubi M. , Soflaei, F. , Banihashemi, S. , 2019. Integrated parametric design of adaptive facades for user's visual comfort. Autom. ConStruct. 106, 102857.

[39] Taleghani, M. , Tenpierik, M. , van den Dobbelsteen, A. , 2014. Energy performance and thermal comfort of courtyard/atrium dwellings in The Netherlands in the light of climate change. Renew. Energy 63, 486- 497.

[40] Tan, D. , Dong, R. , Zhang, Z. , Zhang, B. , Jiang, F. , Ye, Y. , et al., 2024. Multi-objective impact mechanism on the performance characteristic for a diesel particulate filter by RF-NSGA III-TOPSIS during soot loading. Energy 286, 129582.

[41] Wang, L. , Huang, Q. , Zhang, Q. , Xu, H. , Yuen, R.K. , 2017. Role of atrium geometry in building energy consumption: the case of a fully air-conditioned enclosed atrium in cold climates, China. Energy Build. 151, 228- 241.

[42] Ward, G. , Mistrick, R. , Lee, E.S. , McNeil, A. , Jonsson, J. , 2011. Simulating the daylight performance of complex fenestration systems using bidirectional scattering distribution functions within radiance. Leukos 7 (4), 241- 261.

[43] WHO , 2023. WHO Unveils Framework for Climate Resilient and Low Carbon Health Systems.

[44] Wu, P. , Zhou, J. , Li, N. , 2021. Influences of atrium geometry on the lighting and thermal environments in summer: CFD simulation based on-site measurements for validation. Build. Environ. 197, 107853.

[45] Wu, Y. , Jiang, A. , Liu, H. , Li, B. , Kosonen, R. , 2024. Climate chamber investigation of the effect of indoor thermal histories on thermal adaptation in different seasons. Energy and Built Environment 5 (3), 455- 463.

[46] Xiao, W. , Zhong, W. , Wu, H. , Zhang, T. , 2023. Multiobjective optimization of daylighting, energy, and thermal performance for form variables in atrium buildings in China's hot summer and cold winter climate. Energy Build. 297, 113476.

[47] Xie, M. , Wang, M. , Zhong, H. , Li, X. , Li, B. , Mendis, T. , Xu, S. , 2023. The impact of urban morphology on the building energy consumption and solar energy generation potential of university dormitory blocks. Sustain. Cities Soc. 96, 104644.

[48] Xu, S. , Li, G. , Zhang, H. , Xie, M. , Mendis, T. , Du, H. , 2023. Effect of block morphology on building energy consumption of office blocks: a case of wuhan, China. Buildings 13 (3), 768.

[49] Yan, H. , Yan, K. , Ji, G. , 2022. Optimization and prediction in the early design stage of office buildings using genetic and XGBoost algorithms. Build. Environ. 218, 109081.

[50] Zhang, S. , Lin, Z. , 2020. Standard effective temperature based adaptive-rational thermal comfort model. Appl. Energy 264, 114723.

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2024 The Author(s). Publishing services by Elsevier B.V. on behalf of Higher Education Press and KeAi.

审图号：GS京（2025）0467号