An Innovative Fault Impact Analysis Framework for Enhancing Building Operations

doi:10.1016/j.enbuild.2019.07.011

This content will become publicly available on September 15, 2020

Title: An Innovative Fault Impact Analysis Framework for Enhancing Building Operations

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Abstract

The main goal of this paper is to rank building faults based on their impacts on the building energy penalty and occupant thermal comfort penalty considering multiple faults and fault occurrence rates. A fault impact analysis framework is created by incorporating the fault model library with the whole building energy performance simulation (e.g., EnergyPlus used in this study). The fault occurrence rate is introduced as a 'meta' parameter in the simulation. This framework involves three essential aspects of conducting a fault impact analysis: fault constructing, fault simulation, and fault impact analysis. A parametric sensitivity analysis was used to determine and rank the criticality of the faults considering the fault concurrence frequency, by using the deep-learning based response surface model (i.e., the multi-layer perceptron regression). The proposed fault analysis framework with ranking was tested and demonstrated for the DOE's prototype medium-sized office in four different climate zones (i.e., Atlanta, Chicago, Miami, and San Francisco) with 12,000 EnergyPlus fault simulations. A total of 129 fault modes from 41 groups of fault models were simulated for the medium-sized office case. The results demonstrate the proposed framework is robust and scalable for the fault impact analysis. The top critical fault for the medium-sized officemore »« less

Authors:

Li, Yanfei ^[1]; O'Neill, Zheng ^[2]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
Univ. of Alabama, Tuscaloosa, AL (United States). Dept. of Mechanical Engineering

Publication Date:: 2019-09-15

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

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE)

OSTI Identifier:: 1545255

Report Number(s):: NREL/JA-5500-74403
Journal ID: ISSN 0378-7788

Grant/Contract Number:: AC36-08GO28308

Resource Type:: Accepted Manuscript

Journal Name:: Energy and Buildings

Additional Journal Information:: Journal Volume: 199; Journal Issue: C; Journal ID: ISSN 0378-7788

Publisher:: Elsevier

Country of Publication:: United States

Language:: English

Subject:: 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; fault simulation; fault impact analysis; EnergyPlus; parametric sensitivity analysis

Citation Formats


                    Li, Yanfei, and O'Neill, Zheng. An Innovative Fault Impact Analysis Framework for Enhancing Building Operations.  United States: N. p., 2019. 
        Web.  doi:10.1016/j.enbuild.2019.07.011.

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                    Li, Yanfei, & O'Neill, Zheng. An Innovative Fault Impact Analysis Framework for Enhancing Building Operations.  United States.  doi:10.1016/j.enbuild.2019.07.011.

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                    Li, Yanfei, and O'Neill, Zheng. Sun .  
        "An Innovative Fault Impact Analysis Framework for Enhancing Building Operations".  United States.  doi:10.1016/j.enbuild.2019.07.011.

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@article{osti_1545255,

  title        = {An Innovative Fault Impact Analysis Framework for Enhancing Building Operations},

  author       = {Li, Yanfei and O'Neill, Zheng},

  abstractNote = {The main goal of this paper is to rank building faults based on their impacts on the building energy penalty and occupant thermal comfort penalty considering multiple faults and fault occurrence rates. A fault impact analysis framework is created by incorporating the fault model library with the whole building energy performance simulation (e.g., EnergyPlus used in this study). The fault occurrence rate is introduced as a 'meta' parameter in the simulation. This framework involves three essential aspects of conducting a fault impact analysis: fault constructing, fault simulation, and fault impact analysis. A parametric sensitivity analysis was used to determine and rank the criticality of the faults considering the fault concurrence frequency, by using the deep-learning based response surface model (i.e., the multi-layer perceptron regression). The proposed fault analysis framework with ranking was tested and demonstrated for the DOE's prototype medium-sized office in four different climate zones (i.e., Atlanta, Chicago, Miami, and San Francisco) with 12,000 EnergyPlus fault simulations. A total of 129 fault modes from 41 groups of fault models were simulated for the medium-sized office case. The results demonstrate the proposed framework is robust and scalable for the fault impact analysis. The top critical fault for the medium-sized office is the fault of HVAC-Left-ON for the packaged rooftop unit, regarding the site energy, source energy, and HVAC energy. Excluding the fault of HVAC-Left-ON, the top critical faults vary significantly among the four climate zones.},

  doi          = {10.1016/j.enbuild.2019.07.011},

  journal      = {Energy and Buildings},

  number       = C,

  volume       = 199,

  place        = {United States},

  year         = {2019},

  month        = {9}

}

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