A Labeled Dataset for Building HVAC Systems Operating in Faulted and Fault-Free States: Article No. 342

Jessica Granderson, Guanjing Lin, Yimin Chen, Armando Casillas, Jin Wen, Zhelun Chen, Piljae Im, Sen Huang, Jiazhen Ling

Research output: Contribution to journalArticlepeer-review

Abstract

Open data is fueling innovation across many fields. In the domain of building science, datasets that can be used to inform the development of operational applications - for example new control algorithms and performance analysis methods - are extremely difficult to come by. This article summarizes the development and content of the largest known public dataset of building system operations in faulted and fault free states. It covers the most common HVAC systems and configurations in commercial buildings, across a range of climates, fault types, and fault severities. The time series points that are contained in the dataset include measurements that are commonly encountered in existing buildings as well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field operation were used to generate the data. To inform more data-hungry algorithms, most of the simulated data cover a year of operation for each fault-severity combination. The data set is a significant expansion of that first published by the lead authors in 2020.
Original languageAmerican English
Number of pages13
JournalScientific Data
Volume10
DOIs
StatePublished - 2023

NREL Publication Number

  • NREL/JA-5500-86627

Keywords

  • building system operations
  • commercial buildings
  • HVAC
  • open data

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