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Title: Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center

Abstract

Over the several past years, Lawrence Berkeley National Laboratory (LBNL) has conducted field tests for different pre-cooling strategies in different commercial buildings within California. The test results indicated that pre-cooling strategies were effective in reducing electric demand in these buildings during peak periods. This project studied how to optimize pre-cooling strategies for eleven buildings in the Tri-City Corporate Center, San Bernardino, California with the assistance of a building energy simulation tool -- the Demand Response Quick Assessment Tool (DRQAT) developed by LBNL's Demand Response Research Center funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. From the simulation results of these eleven buildings, optimal pre-cooling and temperature reset strategies were developed. The study shows that after refining and calibrating initial models with measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response (Auto-DR) events. This study summarizes the optimization experience of the procedure to develop and calibrate building models in DRQAT. In order to confirm the actual effect of demand response strategies, the simulation results were compared to the field test data. The results indicated that the optimal demand response strategies workedmore » well for all buildings in the Tri-City Corporate Center. This study also compares DRQAT with other building energy simulation tools (eQUEST and BEST). The comparison indicate that eQUEST and BEST underestimate the actual demand shed of the pre-cooling strategies due to a flaw in DOE2's simulation engine for treating wall thermal mass. DRQAT is a more accurate tool in predicting thermal mass effects of DR events.« less

Authors:
; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Environmental Energy Technologies Division
OSTI Identifier:
983201
Report Number(s):
LBNL-3348E
TRN: US201014%%588
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
32; ACCURACY; CALIFORNIA; COMMERCIAL BUILDINGS; DEFECTS; ENGINES; FIELD TESTS; OPTIMIZATION; REFINING; SIMULATION; THERMAL MASS; Pre-cooling, Demand response, Thermal mass, Auto-DR, Building energy simulation tool

Citation Formats

Yin, Rongxin, Xu, Peng, and Kiliccote, Sila. Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center. United States: N. p., 2008. Web. doi:10.2172/983201.
Yin, Rongxin, Xu, Peng, & Kiliccote, Sila. Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center. United States. https://doi.org/10.2172/983201
Yin, Rongxin, Xu, Peng, and Kiliccote, Sila. 2008. "Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center". United States. https://doi.org/10.2172/983201. https://www.osti.gov/servlets/purl/983201.
@article{osti_983201,
title = {Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center},
author = {Yin, Rongxin and Xu, Peng and Kiliccote, Sila},
abstractNote = {Over the several past years, Lawrence Berkeley National Laboratory (LBNL) has conducted field tests for different pre-cooling strategies in different commercial buildings within California. The test results indicated that pre-cooling strategies were effective in reducing electric demand in these buildings during peak periods. This project studied how to optimize pre-cooling strategies for eleven buildings in the Tri-City Corporate Center, San Bernardino, California with the assistance of a building energy simulation tool -- the Demand Response Quick Assessment Tool (DRQAT) developed by LBNL's Demand Response Research Center funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. From the simulation results of these eleven buildings, optimal pre-cooling and temperature reset strategies were developed. The study shows that after refining and calibrating initial models with measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response (Auto-DR) events. This study summarizes the optimization experience of the procedure to develop and calibrate building models in DRQAT. In order to confirm the actual effect of demand response strategies, the simulation results were compared to the field test data. The results indicated that the optimal demand response strategies worked well for all buildings in the Tri-City Corporate Center. This study also compares DRQAT with other building energy simulation tools (eQUEST and BEST). The comparison indicate that eQUEST and BEST underestimate the actual demand shed of the pre-cooling strategies due to a flaw in DOE2's simulation engine for treating wall thermal mass. DRQAT is a more accurate tool in predicting thermal mass effects of DR events.},
doi = {10.2172/983201},
url = {https://www.osti.gov/biblio/983201}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Nov 01 00:00:00 EDT 2008},
month = {Sat Nov 01 00:00:00 EDT 2008}
}