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Title: Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings

Abstract

The paper introduces a hybrid modelling approach that enhances the accuracy and usability of physics-based energy simulation for existing buildings. The approach leverages measured zone air temperature data streams -- increasingly available from smart thermostats -- to derive difficult-to-obtain input parameters for internal thermal mass and infiltration airflow rates. It does so using a reformulated inverse heat balance algorithm. We implemented the inverse algorithms in EnergyPlus and used LBNL's Facility for Low Energy eXperiments (FLEXLAB) for demonstration and validation

Authors:
 [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Building Technologies Office (EE-5B)
OSTI Identifier:
1482546
DOE Contract Number:  
AC02-05CH11231
Resource Type:
Conference
Resource Relation:
Conference: 15. IBPSA Conference (Building Simulation 2017), San Francisco, CA (United States), 7-9 Aug 2017
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION

Citation Formats

Lee, San Hoon, and Hong, Tianzhen. Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings. United States: N. p., 2018. Web.
Lee, San Hoon, & Hong, Tianzhen. Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings. United States.
Lee, San Hoon, and Hong, Tianzhen. Thu . "Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings". United States. doi:. https://www.osti.gov/servlets/purl/1482546.
@article{osti_1482546,
title = {Leveraging Zone Air Temperature Data to Improve Physics-Based Energy Simulation of Existing Buildings},
author = {Lee, San Hoon and Hong, Tianzhen},
abstractNote = {The paper introduces a hybrid modelling approach that enhances the accuracy and usability of physics-based energy simulation for existing buildings. The approach leverages measured zone air temperature data streams -- increasingly available from smart thermostats -- to derive difficult-to-obtain input parameters for internal thermal mass and infiltration airflow rates. It does so using a reformulated inverse heat balance algorithm. We implemented the inverse algorithms in EnergyPlus and used LBNL's Facility for Low Energy eXperiments (FLEXLAB) for demonstration and validation},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Nov 15 00:00:00 EST 2018},
month = {Thu Nov 15 00:00:00 EST 2018}
}

Conference:
Other availability
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