Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms
This documentation and dataset can be used to test the performance of automated fault detection and diagnostics algorithms for buildings. The dataset was created by LBNL, PNNL, NREL, ORNL and ASHRAE RP-1312 (Drexel University). It includes data for air-handling units and rooftop units simulated with PNNL's large office building model.
Citation Formats
TY - DATA
AB - This documentation and dataset can be used to test the performance of automated fault detection and diagnostics algorithms for buildings. The dataset was created by LBNL, PNNL, NREL, ORNL and ASHRAE RP-1312 (Drexel University). It includes data for air-handling units and rooftop units simulated with PNNL's large office building model.
AU - Lin, Guanjing
A2 - Mitchell, Robin
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.25984/1824861
KW - Commercial Buildings
KW - Fault Detection and Diagnostics
KW - building energy
KW - HVAC
KW - VAV
KW - EnergyPlus
KW - building performance
KW - energy
KW - raw data
KW - AHU
KW - air handling unit
KW - rooftop units
KW - heating
KW - cooling
KW - air conditioning
KW - model
KW - building
KW - simulation
LA - English
DA - 2019/02/26
PY - 2019
PB - Lawrence Berkeley National Laboratory
T1 - Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms
UR - https://doi.org/10.25984/1824861
ER -
Lin, Guanjing, and Robin Mitchell. Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms. Lawrence Berkeley National Laboratory, 26 February, 2019, Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1824861.
Lin, G., & Mitchell, R. (2019). Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms. [Data set]. Open Energy Data Initiative (OEDI). Lawrence Berkeley National Laboratory. https://doi.org/10.25984/1824861
Lin, Guanjing and Robin Mitchell. Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms. Lawrence Berkeley National Laboratory, February, 26, 2019. Distributed by Open Energy Data Initiative (OEDI). https://doi.org/10.25984/1824861
@misc{OEDI_Dataset_910,
title = {Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms},
author = {Lin, Guanjing and Mitchell, Robin},
abstractNote = {This documentation and dataset can be used to test the performance of automated fault detection and diagnostics algorithms for buildings. The dataset was created by LBNL, PNNL, NREL, ORNL and ASHRAE RP-1312 (Drexel University). It includes data for air-handling units and rooftop units simulated with PNNL's large office building model. },
url = {https://data.openei.org/submissions/910},
year = {2019},
howpublished = {Open Energy Data Initiative (OEDI), Lawrence Berkeley National Laboratory, https://doi.org/10.25984/1824861},
note = {Accessed: 2025-05-25},
doi = {10.25984/1824861}
}
https://dx.doi.org/10.25984/1824861
Details
Data from Feb 26, 2019
Last updated Oct 15, 2021
Submitted Feb 26, 2019
Organization
Lawrence Berkeley National Laboratory
Contact
Guanjing Lin
Authors
Research Areas
Keywords
Commercial Buildings, Fault Detection and Diagnostics, building energy, HVAC, VAV, EnergyPlus, building performance, energy, raw data, AHU, air handling unit, rooftop units, heating, cooling, air conditioning, model, building, simulationDOE Project Details
Project Name Automated Fault Detection and Diagnostics Data Curation and Benchmarking
Project Number FY17 AOP 3.2.6.1
