Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms

Lin, Guanjing; Mitchell, Robin

doi:10.25984/1824861

Title: Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms

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Abstract

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.

Authors:: Lin, Guanjing; Mitchell, Robin

Publication Date:: 2019-02-26

Other Number(s):: 910

DOE Contract Number:: FY17 AOP 3.2.6.1

Research Org.:: DOE Open Energy Data Initiative (OEDI); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)

Collaborations:: Lawrence Berkeley National Laboratory

Subject:: Array

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

Geolocation:: 49.2637,-66.5318|24.5873,-66.5318|24.5873,-125.4514|49.2637,-125.4514|49.2637,-66.5318

OSTI Identifier:: 1824861

DOI:: https://doi.org/10.25984/1824861

Project Location:

Citation Formats


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

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

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                    Lin, Guanjing, and Mitchell, Robin. 2019.  
"Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms".  United States.  doi:https://doi.org/10.25984/1824861.  https://www.osti.gov/servlets/purl/1824861. Pub date:Tue Feb 26 00:00:00 EST 2019

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@article{osti_1824861,

  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.},

  doi          = {10.25984/1824861},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2019},

  month        = {2}

}

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DOI: https://doi.org/10.25984/1824861

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