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作 者:张浩杰 郝小礼[1,2] 殷维 胡锦华 ZHONG Haojie;HAO Xiaoli;YIN Wei;HU Jinhua(College of Civil Engineering,Hunan University of Science and Technology;Hunan Engineering Research Center for Intelligently Prefabricated Passive House,Hunan University of Science and Technology)
机构地区:[1]湖南科技大学土木工程学院 [2]湖南省智慧建造装配式被动房工程研究中心
出 处:《建筑热能通风空调》2022年第3期17-23,共7页Building Energy & Environment
基 金:湖南省教育厅重点项目(19A180)。
摘 要:为获得被动房外墙保温层厚度的最优解,建立了建筑全生命周期能耗、全生命周期碳排放、全生命周期总成本3个目标函数的数学模型。提出非支配排序遗传算法(NSGA-Ⅱ)与上述多个目标组合的分层优化方法,量化保温层厚度对目标结果的影响。利用上述方法,以夏热冬冷地区某被动式建筑为研究背景,进行建筑运行能耗仿真计算,得出单目标下的建筑最佳保温层厚度。随后利用NSGA-Ⅱ算法,优化生命周期能耗、生命周期碳排放这2个目标得到Pareto前端,在这一组非劣解集(Pareto解)中,对全生命周期总成本进行优化,得到多目标下的最佳保温层厚度为121 mm。研究结果为该地区被动房外墙保温层最佳厚度选择提供了分析方法和参考依据。In order to find the optimal solution for the thickness of the insulation layer of the external envelope of the passive house,The mathematical model of the three objective functions,that is the building’s life cycle energy consumption,life cycle carbon emissions and life cycle total cost,is established.A hierarchical optimization method combining the non-dominated sorting genetic algorithm(NSGA-Ⅱ)and the above multiple objectives is proposed to quantify the influence of the thickness of the insulation layer on the objective values.Using the above-mentioned method,with a passive house in a hot summer and cold winter area as a example,the building operation energy consumption simulation calculation is carried out,and the optimal insulation thickness of the building under a single objective is obtained.Then use the NSGA-Ⅱalgorithm to optimize the two objectives of life cycle energy consumption and life cycle carbon emissions to obtain the Pareto front.In this set of non-inferior solutions(Pareto solutions),another objective-the life cycle cost is optimized,and the optimal insulation layer thickness of multi-objective is 121mm.The research results provide an analysis method and reference for the selection of the optimal thickness of the external wall insulation layer of the passive house in this area.
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