Lawrence Berkley National Laboratory Building 59

Luo, Na

doi:10.25584/1763763

Title: Lawrence Berkley National Laboratory Building 59 (in EN)

Dataset
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Abstract

The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.

Authors:

Luo, Na

Lawrence Berkeley National Laboratory; LBNL

Publication Date:: Mon Feb 01 04:00:00 UTC 2021

Other Number(s):: 69035

DOE Contract Number:: AC02-05CH11231

Research Org.:: Pacific Northwest National Laboratory 2; LBNL

Sponsoring Org.:: EE-5B

Subject:: 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; Indoor environmental; Occupant; Outdoor environmental; Systems and equipment operational

OSTI Identifier:: 1763763

DOI:: https://doi.org/10.25584/1763763

Citation Formats


                    Luo, Na. Lawrence Berkley National Laboratory Building 59.  United States: N. p., 2021. 
        Web.  doi:10.25584/1763763.

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                    Luo, Na. Lawrence Berkley National Laboratory Building 59.  United States.  doi:https://doi.org/10.25584/1763763

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                    Luo, Na. 2021.  
"Lawrence Berkley National Laboratory Building 59".  United States.  doi:https://doi.org/10.25584/1763763.  https://www.osti.gov/servlets/purl/1763763. Pub date:Mon Feb 01 04:00:00 UTC 2021

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@article{osti_1763763,

  title        = {Lawrence Berkley National Laboratory Building 59},

  author       = {Luo, Na},

  abstractNote = {The building management system in Building 59 is monitoring and archiving building-level electricity usage, HVAC and lighting system states (e.g., setpoint, temperature, flow rate, pressure), indoor environmental conditions (air temperature, relative humidity, CO2), on-site weather (air temperature, relative humidity), and especially occupant counts as well as other metrics such as Wi-Fi signal. This dataset could support multiple use cases, such as model predictive control and occupant related demand management.},

  doi          = {10.25584/1763763},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon Feb 01 04:00:00 UTC 2021},

  month        = {Mon Feb 01 04:00:00 UTC 2021}

}

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DOI: https://doi.org/10.25584/1763763

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