Sensitivity analysis methods for building energy models: Comparing computational costs and extractable information
Sensitivity analysis methods for building energy models: Comparing computational costs and extractable information
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DOI：
10.1016/j.enbuild.2016.10.005
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发表时间：
2016-12-01
影响因子：
6.7
通讯作者：
Choudhary, Ruchi
中科院分区：
文献类型：
--
作者：
Menberg, Kathrin;Heo, Yeonsook;Choudhary, Ruchi
虽然灵敏度分析已被广泛应用于建筑能源模型（BEM）的背景下，有很少的研究，调查不同的灵敏度分析方法的性能，动态，高阶，非线性行为和水平的不确定性，在建筑能源模型。我们仔细研究了三种不同的敏感性分析方法：（a）计算效率高的Morris方法进行参数筛选，（B）线性回归分析（中等计算成本）和（c）Sobol方法（高计算成本）。结果表明，从莫里斯方法采取常用的措施参数的影响，结果可能是不稳定的，而使用中值产生稳健的结果，小样本量的评估。对于主导参数，所有三种敏感性分析方法的结果非常一致。关于参数排序的评价或有影响力和可忽略参数的区分，计算成本高的定量方法为本研究中的模型提供了与使用中值的计算效率高的Morris方法相同的信息。探讨了高阶效应和参数交互作用的不同研究方法，揭示了Morris方法中基元效应与参数值的相关性也可以提供参数交互作用的基本信息。(C)2016年6月，作者。由爱思唯尔公司出版
Though sensitivity analysis has been widely applied in the context of building energy models (BEMs), there are few studies that investigate the performance of different sensitivity analysis methods in relation to dynamic, high-order, non-linear behaviour and the level of uncertainty in building energy models. We scrutinise three distinctive sensitivity analysis methods: (a) the computationally efficient Morris method for parameter screening, (b) linear regression analysis (medium computational costs) and (c) Sobol method (high computational costs). It is revealed that the results from Morris method taking the commonly used measure for parameter influence can be unstable, while using the median value yields robust results for evaluations with small sample sizes. For the dominant parameters the results from all three sensitivity analysis methods are in very good agreement. Regarding the evaluation of parameter ranking or the differentiation of influential and negligible parameters, the computationally costly quantitative methods provide the same information for the model in this study as the computational efficient Morris method using the median value. Exploring different methods to investigate higher-order effects and parameter interactions, reveals that correlation of elementary effects and parameter values in Morris method can also provide basic information about parameter interactions. (C) 2016 The Authors. Published by Elsevier B.V.