There is currently no established methodology for the generation of synthetic stochastic internal load profiles for input into building energy simulation. In this paper, a Functional Data Analysis approach is used to propose a new data-centric bottom-up model of plug loads based on hourly data monitored at a high spatial resolution and by space-use type for a case-study building. The model comprises a set of fundamental Principal Components (PCs) that describe the structure of all data samples in terms of amplitude and phase. Scores (or weightings) for each daily demand profile express the contribution of each PC to the demand. Together the principal components and the scores constitute a structure-based model potentially applicable beyond the building considered. The results show good agreement between samples generated using the model and monitored data for key parameters of interest including the timing of the daily peak demand.

当前，尚无用于生成合成随机内部负荷曲线以输入建筑能耗模拟的成熟方法。在本文中，功能数据分析方法用于基于以高空间分辨率监视的每小时数据并按空间使用类型为案例研究建筑，以插头为基础，提出一种以数据为中心的新的自下而上模型。该模型包含一组基本主成分（PC），这些基本主成分以幅度和相位来描述所有数据样本的结构。每个每日需求概况的分数（或权重）表示每个PC对需求的贡献。主成分和分数共同构成了一个基于结构的模型，该模型可能在所考虑的建筑物之外可能适用。