Estimation of outdoor design dataset based on interdependency of multiple meteorological elements by using vine copulas
Estimation of outdoor design dataset based on interdependency of multiple meteorological elements by using vine copulas
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基于多气象要素相互依赖的Vine copula室外设计数据集估计
DOI：
10.1016/j.enbuild.2022.112724
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发表时间：
2023
影响因子：
6.7
通讯作者：
K. Emura
中科院分区：
文献类型：
--
作者：
Z. Jiao;K. Emura
在建筑设计中，ASHRAE推荐的常用室外天气条件是通过年累积出现频率法生成的。这可能导致空调设备容量被高估。这是因为对室内峰值冷负荷影响最大的空气温度、湿度和太阳辐射是独立选择的。这意味着这三个天气参数同时出现的概率非常小。本文提出了一种基于这三个气象参数同时发生概率的精确联合分布来选择设计气象数据的方法。为此，一种新的统计方法vine copula被应用于构建这三个天气参数的理论多元联合分布的24小时数据，并结合设计参数的每一个小时与一个特定的同时发生的概率到一个设计日。室外设计条件是根据东京10年来的逐时气象记录生成的。结果表明，藤蔓copula方法能够建立有效的理论模型，同时发生概率选取的所有设计参数均显著低于相同常规超越概率选取的设计参数。当同时发生概率为0.4%、1%和2%时，相应的室内热风险水平分别为0.46%、0.52%和0.84%。因此，该方法可供设计人员参考，以确定更合理的空调系统容量。
In building design, the commonly used outdoor weather conditions recommended by ASHRAE are generated by the annual cumulative frequency of occurrence method. This may result in air-conditioning equipment capacity being overestimated. This is because the air temperature, humidity and solar radiation that have the greatest impact on indoor peak cooling loads are selected independently. It means that the probability of these three weather parameters occurring at the same time is extremely small. This paper proposes an approach for selecting the design weather data on the basis of the exact joint distribution with specific simultaneous occurrence probabilities of these three weather parameters. For this purpose, a novel statistical method vine copula is applied to construct the theoretical multivariate joint distributions of these three weather parameters for 24-hour data and combined the design parameters of each hour with a specific simultaneous occurrence probability into a design day. The hourly meteorological records over 10 years in Tokyo are used to generate the outdoor design conditions. The results indicate that the vine copula method can create an effective theoretical model and all the design parameters selected by the simultaneous occurrence probability are significantly below that of the same conventional exceeding probability. For simultaneous occurrence probabilities of 0.4 %, 1 % and 2 %, the corresponding indoor thermal risk levels are 0.46 %, 0.52 % and 0.84 %, respectively. Therefore, the proposed method can be used as a reference for designers to determine a more reasonable capacity of air-conditioning systems.