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Multi-Objective Optimization of Ultra-Low Energy Consumption Buildings in Severely Cold Regions Considering Life Cycle Performance

Author

Listed:
  • Zihan Zhang

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

  • Wanjiang Wang

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

  • Junkang Song

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

  • Zhe Wang

    (Xinjiang Institute of Building Science, Urumqi 830054, China)

  • Weiyi Wang

    (Xinjiang Architectural Design and Research Institute, Urumqi 830002, China)

Abstract

Net-zero energy buildings (NZEB) have received widespread attention for their excellent energy and carbon reduction potential in various countries. However, relatively little research has been conducted on the life performance of its primary form: the ultra-low energy building (ULEB). This paper proposes an optimization method combining meta-models to investigate the carbon reduction potential of ultra-low energy buildings in severely cold regions of China. The XGBoost algorithm is used to construct a meta-model of building performance, and the grid search method is used to obtain a high-precision meta-model with an R 2 of 0.967. Secondly, NSGA-II is used to find passive technical solutions based on the meta-model that minimize the global warming potential (GWP), global cost (GC), and operation energy consumption (OE). Finally, the variables affecting the life-cycle performance of buildings were ranked by sensitivity analysis. The results show that GWP, GC, and OE are reduced by 12.7%, 6.7%, and 7.4% compared with the original building through the optimization process proposed. Sensitivity analysis showed that for GWP, the top four sensitivities are window type (TW) > WWR of south wall (WWRS) > roof insulation thickness (IR) > WWR of north wall (WWRN). For GC, the top four sensitivities are: TW > WWRS > IR > WWR of west wall (WWRW); for OE, the top four sensitivities are: TW > IR > WWRS > WWRN. This paper’s optimization framework and research results can effectively guide the design of the ULEB in severely cold regions.

Suggested Citation

  • Zihan Zhang & Wanjiang Wang & Junkang Song & Zhe Wang & Weiyi Wang, 2022. "Multi-Objective Optimization of Ultra-Low Energy Consumption Buildings in Severely Cold Regions Considering Life Cycle Performance," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16440-:d:997553
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    References listed on IDEAS

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    1. Kimiya Aram & Roohollah Taherkhani & Agnė Šimelytė, 2022. "Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change," Energies, MDPI, vol. 15(3), pages 1-21, January.
    2. Hanze Yu & Wei Yang & Qiyuan Li & Jie Li, 2022. "Optimizing Buildings’ Life Cycle Performance While Allowing Diversity in the Early Design Stage," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    3. Vilppu Eloranta & Aki Grönman & Aleksandra Woszczek, 2021. "Case Study and Feasibility Analysis of Multi-Objective Life Cycle Energy System Optimization in a Nordic Campus Building," Energies, MDPI, vol. 14(22), pages 1-17, November.
    4. Wu, Wei & Skye, Harrison M. & Domanski, Piotr A., 2018. "Selecting HVAC systems to achieve comfortable and cost-effective residential net-zero energy buildings," Applied Energy, Elsevier, vol. 212(C), pages 577-591.
    5. Odey Alshboul & Ali Shehadeh & Ghassan Almasabha & Ali Saeed Almuflih, 2022. "Extreme Gradient Boosting-Based Machine Learning Approach for Green Building Cost Prediction," Sustainability, MDPI, vol. 14(11), pages 1-20, May.
    6. Ganjehkaviri, A. & Mohd Jaafar, M.N. & Hosseini, S.E. & Barzegaravval, H., 2017. "Genetic algorithm for optimization of energy systems: Solution uniqueness, accuracy, Pareto convergence and dimension reduction," Energy, Elsevier, vol. 119(C), pages 167-177.
    7. Feng, Wei & Zhang, Qianning & Ji, Hui & Wang, Ran & Zhou, Nan & Ye, Qing & Hao, Bin & Li, Yutong & Luo, Duo & Lau, Stephen Siu Yu, 2019. "A review of net zero energy buildings in hot and humid climates: Experience learned from 34 case study buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    8. Yibing Xue & Wenhan Liu, 2022. "A Study on Parametric Design Method for Optimization of Daylight in Commercial Building’s Atrium in Cold Regions," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
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