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

Dataset
Other Related Research

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

Lawrence Berkeley National Laboratory

Publication Date:: Mon Feb 25 23:00:00 EST 2019

Other Number(s):: 910

Research Org.:: DOE Open Energy Data Initiative (OEDI); Lawrence Berkeley National Laboratory

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

Collaborations:: Lawrence Berkeley National Laboratory

Subject:: AHU; Array; Commercial Buildings; EnergyPlus; Fault Detection and Diagnostics; HVAC; VAV; air conditioning; air handling unit; building; building energy; building performance; cooling; energy; heating; model; raw data; rooftop units; simulation

OSTI Identifier:: 1824861

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

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:Mon Feb 25 23:00:00 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         = {Mon Feb 25 23:00:00 EST 2019},

  month        = {Mon Feb 25 23:00:00 EST 2019}

}

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

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