Simulation of energy performance in buildings featuring green walls and green roofs in arid climates

Abstract

Global warming, caused by greenhouse gas emissions created by human activities and urban heat island (UHI) effect, is a major issue, especially in arid regions. The study explores the energy efficiency of green-walled and green-roofed buildings in arid climates, through simulations. The study seeks to examine the effects of these greening technologies on thermal performance, heat transfer and energy consumption. The force consuming structures using green roofing and walls forecasted using deep neural network (DNN) model, which is optimised using the Deer Hunting Optimization Algorithm (DHOA). The simulation outcomes show the capacity of these greening technologies to enhance thermal comfort and mitigate UHI problems. Furthermore, these solutions contribute significantly to increased energy savings and internal air pollution. Proposed DNN–DHOA model achieved R² 0.971, RMSE 0.0181, and MAE 0.0119 demonstrating superior predictive performance in energy consumption estimation task. The findings provide valuable insights to urban designers and policymakers in arid regions, promoting the integration of green technologies to enhance the sustainability and energy efficiency of urban environments.

Keywords

Green roofs / Green walls / Arid climates / Deep neural network / Deer hunting optimization algorithm

References

[1] Nasr Y, Zakhem HE, Hamami AEA, Bachawati ME, Belarbi R. Comprehensive assessment of the Impact of green roofs and walls on building energy performance: a scientific review. Energies, 2024, 17(20): 5160

[2] Andric I, Kamal A, Al-Ghamdi SG. Efficiency of green roofs and green walls as climate change mitigation measures in extremely hot and dry climate: case study of Qatar. Energy Rep, 2020, 6: 2476-2489

[3] Djedjig R, Bozonnet E, Belarbi R. Analysis of thermal effects of vegetated envelopes: integration of a validated model in a building energy simulation program. Energ Build, 2015, 86: 93-103

[4] Synnefa A, Dandou A, Santamouris M, Tombrou M, Soulakellis N. On the use of Cool materials as a heat island mitigation Strategy. J Appl Meteorol Clim, 2008, 47(11): 2846-2856

[5] Djedjig R, Bozonnet E, Belarbi R. Experimental study of the urban microclimate mitigation potential of green roofs and green walls in street canyons. Int J Low-Carbon Technol, 2015, 10(1): 34-44

[6] Zinzi M, Agnoli S. Cool and green roofs. An energy and comfort comparison between passive cooling and mitigation urban heat island techniques for residential buildings in the Mediterranean region. Energ Build, 2012, 55: 66-76

[7] Feng H, Hewage K. Energy saving performance of green vegetation on LEED certified buildings. Energ Build, 2014, 75: 281-289

[8] Jamei E, Thirunavukkarasu G, Abuseif M, Seyedmahmoudian M, Mekhilef S, Stojcevski A, Chau H-W. Simulation-based study on the effect of green roofs on Summer energy performance in Melbourne. Land, 2023, 12(12): 2105

[9] Schweitzer O, Erell E. Evaluation of the energy performance and irrigation requirements of extensive green roofs in a water-scarce Mediterranean climate. Energ Build, 2014, 68: 25-32

[10] Khan H, Asif M. Impact of green roof and orientation on the energy performance of buildings: a Case study from Saudi Arabia. Sustainability, 2017, 9(4): 640

[11] Pragati S, Priya RS, Pradeepa C, Senthil R. Simulation of the energy performance of a building with green roofs and green walls in a tropical climate. Sustainability, 2023, 15(3): 2006

[12] Herath HMPIK, Halwatura RU, Jayasinghe GY. Modeling a tropical urban context with green walls and green roofs as an urban heat island adaptation Strategy. Procedia Eng, 2018, 212: 691-698

[13] Huang Y-Y, Chen C-T, Liu W-T. Thermal performance of extensive green roofs in a subtropical metropolitan area. Energ Build, 2018, 159: 39-53

[14] Battista G, Vollaro EDL, Vollaro RDL. How Cool pavements and green roof affect building energy performances. Heat Transf Eng, 2022, 43(3–5): 326-336

[15] Ragab A, Abdelrady A. Impact of green roofs on energy demand for cooling in Egyptian buildings. Sustainability, 2020, 12(14): 5729

[16] Mousavi S, Gheibi M, Wacławek S, Behzadian K. A novel smart framework for optimal design of green roofs in buildings conforming with energy conservation and thermal comfort. Energ Build, 2023, 291: 113111

[17] Teotónio I, Cruz CO, Silva CM, Morais J. Investing in sustainable built environments: the willingness to pay for green roofs and green walls. Sustainability, 2020, 12(8): 3210

[18] Mahmoud A, Asif M, Hassanain M, Babsail M, Sanni-Anibire M. Energy and economic Evaluation of green roofs for residential buildings in hot-Humid climates. Buildings, 2017, 7(2): 30

[19] Alrashed F, Asif M. Trends in residential energy consumption in Saudi Arabia with particular Reference to the eastern Province. J. Sustain. Dev. Energy Water Environ. Syst, 2014, 2(4): 376-387

[20] Alrashed F, Asif M. Analysis of critical climate related factors for the application of zero-energy homes in Saudi Arabia. Renewable Sustain Energy Rev, 2015, 41: 1395-1403

[21] Brammya G, Praveena S, Preetha NSN, Ramya R, Rajakumar BR, Binu D (2019) Deer Hunting optimization algorithm: a New Nature-inspired meta-heuristic paradigm. Comput J bxy133. https://doi.org/10.1093/comjnl/bxy133

[22] Shaban WM, Elbaz K, Zhou A, Shen SL. Physics-informed deep neural network for modeling the chloride diffusion in concrete. Eng Appl Artif Intel, 2023, 125: 106691

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