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

Liang Zhao (), Wei Zhang and Wenshun Wang ()
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Liang Zhao: School of Telecommunications Engineering, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221000, China
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

Sustainability, 2022, vol. 14, issue 20, 1-17

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.

Keywords: low-carbon; BIM; NSGA-II; building performance; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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