1. 天津大学 建筑学院,天津,300072
2. 农业部都市农业重点实验室,上海,200240
3. 华中农业大学 园艺林学学院,[KH-*8/9]武汉,430070
4. 天津科技大学 机械工程学院,天津,300222
纸质出版:2018
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何成, 朱丽, 田玮. 城市建筑布局的能耗敏感性分析[J]. 哈尔滨工业大学学报, 2018,50(4):2018-4.
HE Cheng, ZHU Li, TIAN Wei. Sensitivity analysis of urban building layout on energy consumption[J]. 2018, 50(4): 2018-4.
何成, 朱丽, 田玮. 城市建筑布局的能耗敏感性分析[J]. 哈尔滨工业大学学报, 2018,50(4):2018-4. DOI: 10.11918/j.issn.0367-6234.201703101.
HE Cheng, ZHU Li, TIAN Wei. Sensitivity analysis of urban building layout on energy consumption[J]. 2018, 50(4): 2018-4. DOI: 10.11918/j.issn.0367-6234.201703101.
为研究城市建筑布局对能耗的影响规律及关键性布局参数,采用仿真试验结合敏感性分析的方法,从遮挡太阳辐射减少建筑得热的角度,对武汉地区200种布局进行仿真研究.首先,通过拉丁超立方抽样(LHS)确定布局参数组合;然后,利用R语言和EnergyPlus能耗模拟软件建立200种能耗模型并计算;最后,应用标准回归系数(SRC)和树状高斯过程模型(TGP)两种全局敏感性分析方法,量化分析水平和垂直方向9个布局参数对目标建筑能耗的影响.结果表明:建筑布局对能耗有显著影响,9个布局参数的总变化,分别引起制冷、供暖和总能耗15.8%、26.8%、4.4%的波动;两种敏感性分析结果类似,对制冷和总能耗影响最大的参数是西侧建筑高度,其主效应都在0.3左右,影响最小的参数是南侧建筑面宽,其主效应都在0.1以下;影响供暖能耗最大的参数是南侧建筑的高度,其主效应在0.3以上,影响最小的参数是东侧建筑面宽.当参数取值远大于目标建筑尺寸时,各参数对能耗的影响力降低,采用TGP敏感性分析更合理.从节能减排的角度,为城市规划及建筑布局提供理论依据.
To study the effect of urban building layout on energy consumption and to identify the key layout parameters
the simulation experiment and the sensitivity analysis method are used to simulate 200 kinds of layout in Wuhan from the perspective of reducing the solar radiation and heat gain. Firstly
the parameter combinations are created by Latin hypercube sampling (LHS). Then
200 energy consumption models are established and calculated by R language and EnergyPlus energy consumption simulation software. Finally
the standard regression coefficient (SRC) and treed Gaussian process (TGP) global sensitivity analysis methods are implemented in order to explore the influence of the nine layout parameters of both horizontal and vertical direction on the target building energy consumption. The results show that the building layout has a significant effect on the energy consumption
the changes of 9 layout parameters would cause fluctuations in cooling
heating and total energy consumption of 15.8%
26.8%
and 4.4%
respectively. The two sensitivity analysis results are similar. The parameter that has the greatest influence on the cooling and total energy consumption is the height of building in the western part
whose main effects are around 0.3. The least influential parameter is the width of the south
whose main effects are bellow 0.1. The dominant parameter of heating energy is the height of the south building
which can account for more than 30% of the variations of the output
and the smallest is the east building width. When the parameter value is much larger than the target building size
the influence of each parameter on energy consumption is reduced
and using the TGP sensitivity analysis is more reasonable. From the perspective of energy-saving and emissions reduction
this paper can provide theoretical basis for the urban planning and building layout.
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