一个标记的数据集用于在故障和无故障状态下运行的建筑HVAC系统
Jessica Granderson1, Guanjing Lin2, Yimin Chen3
1Lawrence Berkeley National Laboratory, Berkeley, USA. JGranderson@lbl.gov.
Scientific data
|June 1, 2023
概括
本研究介绍了建筑系统操作的最大的公共数据集,包括HVAC系统的故障和无故障状态. 这种开放的数据资源旨在推动科学应用和控制算法的创新.
科学领域:
- 建筑科学 建筑科学
- 数据科学数据科学数据科学
- 暖通空调系统工程 HVAC系统工程
背景情况:
- 建筑科学方面的创新往往受到操作数据集的稀缺性所阻碍.
- 现有的公共数据集缺乏建筑系统的全面操作数据,特别是在故障条件下.
- 开发高级应用程序,如控制算法和性能分析方法,需要大量高质量的数据.
研究的目的:
- 引入建筑系统运行的最大的公开可用的数据集.
- 为普通商业建筑HVAC系统提供包括无故障和各种故障状态的数据.
- 支持开发数据密集的算法,用于建筑性能分析和控制.
主要方法:
- 使用模拟工具,实验测试设施和现场实地操作的组合生成数据.
- 包括来自建筑系统的常见和不太典型的时间序列数据点.
- 对每个故障严重程度组合的运行一年的模拟,以支持数据密集型算法.
主要成果:
- 开发最广泛的公共数据集,详细说明建筑系统操作.
- 数据集涵盖了各种HVAC系统,气候,故障类型和严重程度.
- 2020年首席作者最初发布的数据集的显著扩展.
结论:
- 本文所介绍的数据集是推动建筑科学和运营应用的重要资源.
- 这种全面数据的可用性将加速新型控制策略和分析方法的开发.
- 这种资源使得建立操作数据的访问获得民主化,促进了更广泛的创新.
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