%0 Journal Article
%A Jessica Granderson
%A Guanjing Lin
%A Yimin Chen
%A Armando Casillas
%A Jin Wen
%A Zhelun Chen
%A Piljae Im
%A Sen Huang
%A Jiazhen Ling
%B Scientific Data
%D 2023
%G eng
%R https://doi.org/10.1038/s41597-023-02197-w
%T A labeled dataset for building HVAC systems operating in faulted and fault-free states
%V 10
%8 06/2023
%X <p>Open data is fueling innovation across many fields. In the domain of building science, datasets that can<br />be used to inform the development of operational applications - for example new control algorithms<br />and performance analysis methods - are extremely difficult to come by. This article summarizes the<br />development and content of the largest known public dataset of building system operations in faulted<br />and fault free states. It covers the most common HVAC systems and configurations in commercial<br />buildings, across a range of climates, fault types, and fault severities. The time series points that are<br />contained in the dataset include measurements that are commonly encountered in existing buildings as<br />well as some that are less typical. Simulation tools, experimental test facilities, and in-situ field<br />operation were used to generate the data. To inform more data-hungry algorithms, most of the<br />simulated data cover a year of operation for each fault-severity combination. The data set is a significant<br />expansion of that first published by the lead authors in 2020.</p>