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Title: Assessing overall building energy performance of a large population of residential single-family homes using limited field data

Abstract

Building energy simulation play a significant role in building design and retrofit. Most applications deal with one or few individual buildings which enables the specification of detailed model inputs. However, building energy simulation can also be a powerful tool for assessing energy performance even when detailed building characteristics are not available. In this study, field data were collected on a limited randomly selected new residential homes in 8 US states aiming to evaluate energy code compliance and saving potential. The limited data prohibits deriving model inputs for the homes visited let alone for the entire unknown new home stock. We use prototype building to construct a large number of building models and utilize bootstrap sampling to draw model inputs from the limited data. We demonstrate that overall energy performance of a large population of new homes can be assessed by the novel framework through EnergyPlus simulation using limited field data.

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [2];  [1];  [1];  [1];  [1]
  1. Pacific Northwest National Laboratory, Richland, WA, USA
  2. Mathematics Department, Brigham Young University-Idaho, Rexburg, ID, USA
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind Energy Technologies Office (EE-4WE)
OSTI Identifier:
1504447
Report Number(s):
PNNL-SA-131346
Journal ID: ISSN 1940-1493
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Journal of Building Performance Simulation
Additional Journal Information:
Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1940-1493
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
EnergyPlus simulation, building energy code compliance, Saving potential, bootstrap sampling

Citation Formats

Xie, Yulong, Mendon, Vrushali, Halverson, Mark, Bartlett, Rosemarie, Hathaway, John, Chen, Yan, Rosenberg, Michael, Taylor, Todd, and Liu, Bing. Assessing overall building energy performance of a large population of residential single-family homes using limited field data. United States: N. p., 2018. Web. doi:10.1080/19401493.2018.1477833.
Xie, Yulong, Mendon, Vrushali, Halverson, Mark, Bartlett, Rosemarie, Hathaway, John, Chen, Yan, Rosenberg, Michael, Taylor, Todd, & Liu, Bing. Assessing overall building energy performance of a large population of residential single-family homes using limited field data. United States. doi:10.1080/19401493.2018.1477833.
Xie, Yulong, Mendon, Vrushali, Halverson, Mark, Bartlett, Rosemarie, Hathaway, John, Chen, Yan, Rosenberg, Michael, Taylor, Todd, and Liu, Bing. Wed . "Assessing overall building energy performance of a large population of residential single-family homes using limited field data". United States. doi:10.1080/19401493.2018.1477833.
@article{osti_1504447,
title = {Assessing overall building energy performance of a large population of residential single-family homes using limited field data},
author = {Xie, Yulong and Mendon, Vrushali and Halverson, Mark and Bartlett, Rosemarie and Hathaway, John and Chen, Yan and Rosenberg, Michael and Taylor, Todd and Liu, Bing},
abstractNote = {Building energy simulation play a significant role in building design and retrofit. Most applications deal with one or few individual buildings which enables the specification of detailed model inputs. However, building energy simulation can also be a powerful tool for assessing energy performance even when detailed building characteristics are not available. In this study, field data were collected on a limited randomly selected new residential homes in 8 US states aiming to evaluate energy code compliance and saving potential. The limited data prohibits deriving model inputs for the homes visited let alone for the entire unknown new home stock. We use prototype building to construct a large number of building models and utilize bootstrap sampling to draw model inputs from the limited data. We demonstrate that overall energy performance of a large population of new homes can be assessed by the novel framework through EnergyPlus simulation using limited field data.},
doi = {10.1080/19401493.2018.1477833},
journal = {Journal of Building Performance Simulation},
issn = {1940-1493},
number = 4,
volume = 12,
place = {United States},
year = {2018},
month = {5}
}

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