Urban Building Energy Stock Datasets

This dataset comprises over 1 million records of residential urban building stock, including types such as terraced houses, detached houses, semi-detached houses, and bungalows. It utilizes jEPlus as a parametric tool for physics-based simulations, combined with EnergyPlus for thermal simulation, and integrates DesignBuilder construction templates for generation. The dataset encompasses various building features, such as HVAC systems and building fabric properties (including U-values for walls, roofs, floors, doors, and windows). It also contains parameters related to heating, lighting, equipment, photovoltaic systems, and hot water energy demand. For citation: Usman Ali, Sobia Bano, Mohammad Haris Shamsi, Divyanshu Sood, Cathal Hoare, Wangda Zuo, Neil Hewitt, James O'Donnell. “Urban building energy performance prediction and retrofit analysis using data-driven machine learning approach”. Energy and Buildings, Volume 303, https://doi.org/10.1016/j.enbuild.2023.113768本数据集包含超100万条城市住宅建筑存量记录，涵盖联排住宅、独栋住宅、双拼住宅及单层平房等建筑类型。本数据集以jEPlus作为参数化物理仿真工具，结合EnergyPlus开展热仿真，并集成DesignBuilder的建筑构造模板完成数据集构建。数据集涵盖多类建筑特征参数，包括暖通空调（Heating, Ventilation and Air Conditioning，简称HVAC）系统、建筑围护结构性能（含墙体、屋面、楼板、门窗的U值）；同时包含与采暖、照明、用电设备、光伏系统及生活热水能耗需求相关的各类参数。引用格式：Usman Ali、Sobia Bano、Mohammad Haris Shamsi、Divyanshu Sood、Cathal Hoare、Wangda Zuo、Neil Hewitt、James O'Donnell. 《基于数据驱动机器学习方法的城市建筑能耗性能预测与改造分析》. 能源与建筑（Energy and Buildings），第303卷，https://doi.org/10.1016/j.enbuild.2023.113768