In building energy simulation (BES), internal loads are typically defined as hourly schedules based on occupant-related ‘activities’ assigned to each building zone. In this paper, a data-centric bottom-up functional data analysis model is used to examine how activities in a building correlate with energy demand for plug loads and lighting. Functional principal component analysis and hierarchical clustering of the principal component scores have been used to explore the links between the data and zone activity. The results show that plug loads show limited links to activity to the extent that the activity determines the variability of the data. The lighting loads show little correlation with zone activity but instead are determined primarily by the building control system. A novel methodology is proposed for the generation of stochastic load data for input into BES. This methodology has been developed into a tool for stochastic load generation which is available online.

在建筑能耗模拟（BES）中，内部负载通常基于分配给每个建筑区域的与乘员相关的“活动”来定义为每小时计划。在本文中，以数据为中心的自下而上的功能数据分析模型用于检查建筑物中的活动与插头负载和照明的能源需求之间的关系。功能性主成分分析和主成分得分的层次聚类已用于探索数据与区域活动之间的联系。结果表明，在活动确定数据可变性的范围内，插件负载显示了与活动的有限链接。照明负荷与区域活动几乎没有关联，而是主要由建筑物控制系统确定。提出了一种新颖的方法，用于生成随机负载数据以输入到BES中。该方法已开发为可在线生成随机负载的工具。