建模区域供暖需求:两个住宅区的合成数据集
Katia Ritosa1, Ina De Jaeger1, Dirk Saelens1,2
1KU Leuven, Department of Civil Engineering, Building Physics and Sustainable Design, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium.
Data in brief
|February 5, 2025
概括
这项研究生成了建筑能源性能的人工数据集,模拟了比利时弗兰德斯的2006年前后住房库存. 这些数据集有助于开发用于传热分析和城市能源规划的工具.
科学领域:
- 建筑科学与能源
- 计算机模拟计算模拟
- 数据科学数据科学数据科学
背景情况:
- 准确的建筑能效数据对于能源效率和城市规划至关重要.
- 现有的监测数据往往缺乏细节或很难获得不同的建筑类型.
- 建筑物的能源性能指令 (EPBD) 影响了建筑标准,创造了不同的性能类别.
研究的目的:
- 创建广泛的人工数据集,模拟现实世界的建筑能源消耗,用于各种住房库.
- 为开发统计工具提供数据,以表征建筑外热传递.
- 为了能够评估模拟组件对建筑能源平衡的影响,并支持城市规模的能源规划.
主要方法:
- 模拟的单户住宅在弗兰德斯使用Dymola和IDEAS包与TEASER.
- 对EPBD前 (低性能) 和EPBD后 (高性能) 建筑物的生成数据集.
- 整合了自然透,占用者的随机行为,以及详细的气体加热系统模型 (包括DHW).
主要成果:
- 创建了两个不同的数据集,代表低性能和高性能建筑库.
- 模拟捕获了详细的能源需求,包括供暖和家庭热水 (DHW).
- 数据集为能源平衡分析提供了全面的,难以衡量的输入.
结论:
- 生成的数据集对于验证用于构建信封表征的统计方法非常有价值.
- 这些数据集有助于研究各种建筑类型和城市能源系统的能源性能.
- 该研究为推进建筑能源建模和规划工具提供了坚实的基础.
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