An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics

Title: An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics

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Abstract

Small commercial buildings in the U.S. waste an estimated 300 Trillion BTU (approximately $6 billion in energy costs) annually due to faults, but lack cost-effective automated fault detection and diagnosis (AFDD) tools. NREL and GE Global Research are partnering to develop hybrid AFDD algorithms tailored to the unique needs of small commercial buildings (

Authors:

^[1]; Nichols, Jason ^[2]

National Renewable Energy Laboratory (NREL), Golden, CO (United States)
GE Global Research Center

Publication Date:: 2018-10-04

Research Org.:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)

OSTI Identifier:: 1476981

Report Number(s):: NREL/PR-5500-71860

DOE Contract Number:: AC36-08GO28308

Resource Type:: Conference

Resource Relation:: Conference: Presented at the 2018 Intelligent Building Operations Workshop, 7 July 2018, West Lafayette, Indiana

Country of Publication:: United States

Language:: English

Subject:: 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 47 OTHER INSTRUMENTATION; automated fault detection; diagnosis; machine learning; energy modeling; buildings; EnergyPlus; OpenStudio

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                    Frank, Stephen M, and Nichols, Jason. An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics.  United States: N. p., 2018. 
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                    Frank, Stephen M, & Nichols, Jason. An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics.  United States.

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                    Frank, Stephen M, and Nichols, Jason. Thu .  
        "An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics".  United States.  https://www.osti.gov/servlets/purl/1476981.

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@article{osti_1476981,

  title        = {An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics},

  author       = {Frank, Stephen M and Nichols, Jason},

  abstractNote = {Small commercial buildings in the U.S. waste an estimated 300 Trillion BTU (approximately $6 billion in energy costs) annually due to faults, but lack cost-effective automated fault detection and diagnosis (AFDD) tools. NREL and GE Global Research are partnering to develop hybrid AFDD algorithms tailored to the unique needs of small commercial buildings (},

  doi          = {},

  url          = {https://www.osti.gov/biblio/1476981},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {2018},

  month        = {10}

}

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