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BIM-Based Multi-Objective Optimization of Low-Carbon and Energy-Saving Buildings

Author

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  • Liang Zhao

    (School of Telecommunications Engineering, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221000, China
    Jiangsu Province Engineering Research Center of Intelligent Visual Recognition and Data Mining, Xuzhou 221000, China
    Xuzhou Intelligent Machine and Visual Application Technology Engineering Research Center, Xuzhou 221000, China
    These authors contributed equally to this work.)

  • Wei Zhang

    (Jiangsu Collaborative Innovation Center for Building Energy Saving and Construct Technology, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221116, China)

  • Wenshun Wang

    (School of Mechanics & Civil Engineering, China University of Mining and Technology, Xuzhou 221000, China
    These authors contributed equally to this work.)

Abstract

Global warming and other environmental problems are increasing the demand for green and low-carbon buildings. The development of high-performance computers and building information models has a significant impact on low-carbon buildings. Low-carbon building design needs to comprehensively consider geography, climate, material, cost and other factors, a highly complex multidisciplinary research problem. Therefore, it is urgent to use advanced modeling and simulation technology, involving BIM, parametric design, cloud platform and evolutionary algorithm. This paper proposes a BIM based low-carbon building design optimization framework, which realizes the comprehensive trade-off function of building low-carbon energy saving and daylighting performance through an improved genetic algorithm. The framework drives BIM through parameterization and integrates building environment information, geometric information and operation information, including six parts: BIM model establishment, parameter-driven development, building performance simulation, multi-objective optimization design, Pareto frontier analysis, and energy-saving decision-making and evaluation. The case study shows that the simulation results obtained through the framework can effectively achieve building energy conservation while maximizing the lighting performance of the building, providing a scientific basis and reference for construction professionals to design low-carbon buildings. Finally, the application advantages and limitations of the framework in low-carbon building design and its application prospects in low-carbon energy-saving building design are discussed. This research has made contributions to the multi-disciplinary low-carbon energy conservation research field, realized the multi-objective optimization strategy of building performance based on BIM, genetic algorithm and simulation, and is an important supplement to existing building energy conservation and emission reduction optimization design.

Suggested Citation

  • Liang Zhao & Wei Zhang & Wenshun Wang, 2022. "BIM-Based Multi-Objective Optimization of Low-Carbon and Energy-Saving Buildings," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13064-:d:940081
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    References listed on IDEAS

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    3. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    4. Nili, Maryam & Seyedhosseini, Seyed Mohammad & Jabalameli, Mohammad Saeed & Dehghani, Ehsan, 2021. "A multi-objective optimization model to sustainable closed-loop solar photovoltaic supply chain network design: A case study in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
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