Related Datasets

Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms

DOI 10.25984/1824861

Publicly accessible License

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.

Download All Resources 7.85 MB — 2 files

Data Sets for AFDD Evauluation of Building FDD Algorithms.zip

This is a zip file of the CSV files that accompany the documentation for the automated fault detection and diagnostics (AFDD) testing data sets created by LBNL, PNNL, N... more

682

Download 6.69 MB

Inventory of Data Sets for AFDD Evaluation.pdf

This document provides an inventory and associated documentation of automated fault detection and diagnostics (AFDD) testing data sets created by LBNL, PNNL, NREL/ORNL,... more

1,202

Download 1.17 MB

Citation Formats

Lawrence Berkeley National Laboratory. (2019). Data Sets for  Evaluation of Building Fault Detection and Diagnostics Algorithms [data set].  Retrieved from https://dx.doi.org/10.25984/1824861.

Export Citation to RIS

Lin, Guanjing, Mitchell, Robin. Data Sets for  Evaluation of Building Fault Detection and Diagnostics Algorithms. United States: N.p., 26 Feb, 2019. Web. doi: 10.25984/1824861.

Lin, Guanjing, Mitchell, Robin. Data Sets for  Evaluation of Building Fault Detection and Diagnostics Algorithms. United States. https://dx.doi.org/10.25984/1824861

Lin, Guanjing, Mitchell, Robin. 2019. "Data Sets for  Evaluation of Building Fault Detection and Diagnostics Algorithms". United States. https://dx.doi.org/10.25984/1824861. https://data.openei.org/submissions/910.

@div{oedi_910, title = {Data Sets for  Evaluation of Building Fault Detection and Diagnostics Algorithms}, author = {Lin, Guanjing, 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. }, doi = {10.25984/1824861}, url = {https://data.openei.org/submissions/910}, journal = {}, number = , volume = , place = {United States}, year = {2019}, month = {02}}

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

Guanjing Lin

Lawrence Berkeley National Lab

Robin Mitchell

Lawrence Berkeley National Lab

Research Areas

Buildings Efficiency Energy Analysis

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, simulation

DOE Project Details

Project Name Automated Fault Detection and Diagnostics Data Curation and Benchmarking

Project Number FY17 AOP 3.2.6.1