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Title: Lawrence Berkeley National Lab Building 59 (in EN)

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:
;
  1. Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
  2. Lawrence Berkeley National Laboratory
Publication Date:
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:
1762808
DOI:
https://doi.org/10.25584/LBNLBLDG59/1762808

Citation Formats

Luo, Na, and Hong, Tianzhen. Lawrence Berkeley National Lab Building 59. United States: N. p., 2021. Web. doi:10.25584/LBNLBLDG59/1762808.
Luo, Na, & Hong, Tianzhen. Lawrence Berkeley National Lab Building 59. United States. doi:https://doi.org/10.25584/LBNLBLDG59/1762808
Luo, Na, and Hong, Tianzhen. 2021. "Lawrence Berkeley National Lab Building 59". United States. doi:https://doi.org/10.25584/LBNLBLDG59/1762808. https://www.osti.gov/servlets/purl/1762808. Pub date:Tue Jan 26 23:00:00 EST 2021
@article{osti_1762808,
title = {Lawrence Berkeley National Lab Building 59},
author = {Luo, Na and Hong, Tianzhen},
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/LBNLBLDG59/1762808},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 26 23:00:00 EST 2021},
month = {Tue Jan 26 23:00:00 EST 2021}
}