Energy efficiency analysis has been presented recently to minimize the energy consumption of buildings by designing the optimal structural parameters. Because of uncertain parameters incorporated in the energy analysis of a building, computationally effective methods are needed to model the uncertainties in the analysis. In this paper, a probabilistic multi-objective optimization method is proposed based on the statistical methods, i.e., the empirical rule method and two-point estimate method, for analyzing the energy efficiency in buildings. The energy consumption density and thermal discomfort function of residents are considered as the objective functions of the optimization problem. The model of a 12-story commercial building is used to examine the proposed method. Probabilistic methods are compared with the deterministic one to show the effect of considering uncertainties on the results. According to the results, there is a substantial difference between the optimal values of the building’s parameters by applying probabilistic and deterministic methods.

中文翻译：

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使用统计方法对建筑物进行概率能源效率分析

最近提出了能源效率分析，以通过设计最佳结构参数来最小化建筑物的能源消耗。由于建筑物能量分析中包含的不确定参数，需要计算有效的方法来模拟分析中的不确定性。本文提出了一种基于统计方法的概率多目标优化方法，即经验规则法和两点估计法，用于分析建筑物的能源效率。将居民的能源消耗密度和热不适函数作为优化问题的目标函数。使用 12 层商业建筑的模型来检验所提出的方法。将概率方法与确定性方法进行比较，以显示考虑不确定性对结果的影响。根据结果​​，通过应用概率和确定性方法，建筑物参数的最佳值之间存在显着差异。