Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data
Building energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the buildi...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/9/2321 |
| _version_ | 1797568672535937024 |
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| author | Yulong Xie Mark Halverson Rosemarie Bartlett Yan Chen Michael Rosenberg Todd Taylor Jeremiah Williams Michael Reiner |
| author_facet | Yulong Xie Mark Halverson Rosemarie Bartlett Yan Chen Michael Rosenberg Todd Taylor Jeremiah Williams Michael Reiner |
| author_sort | Yulong Xie |
| collection | DOAJ |
| description | Building energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the building energy code was conducted in several states of the United States. The study was comprised of three phases: (1) a baseline study to document typical practice and identify opportunities for improvement based on empirical data gathered from the field; (2) an education and training phase targeting the opportunities identified; and (3) a post-study to assess whether a reduction in average state-wide energy use could be achieved following the education and training phase. We proposed a novel methodology based on large-scale building energy simulation inferred by limited field data to assess the performance of a large population of homes. This paper presents the methodology, findings, and results of this study. The state-wide average energy consumption decreased at Phase III from Phase I for five of the seven states involved in the analysis. The measure-level savings potential analysis shows an overall reduction. Overall, the training and education phase plays a recognizable role in improving compliance with building energy codes. |
| first_indexed | 2024-03-10T19:59:18Z |
| format | Article |
| id | doaj.art-554287422cd74020b7e89ec3f420b606 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T19:59:18Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-554287422cd74020b7e89ec3f420b6062023-11-19T23:40:46ZengMDPI AGEnergies1996-10732020-05-01139232110.3390/en13092321Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field DataYulong Xie0Mark Halverson1Rosemarie Bartlett2Yan Chen3Michael Rosenberg4Todd Taylor5Jeremiah Williams6Michael Reiner7Pacific Northwest National Laboratory, Richland, WA 99352, USAPacific Northwest National Laboratory, Richland, WA 99352, USAPacific Northwest National Laboratory, Richland, WA 99352, USAPacific Northwest National Laboratory, Richland, WA 99352, USAPacific Northwest National Laboratory, Richland, WA 99352, USAPacific Northwest National Laboratory, Richland, WA 99352, USAU.S. Department of Energy, Washington, DC 20024, USAU.S. Department of Energy, Washington, DC 20024, USABuilding energy code compliance is the crucial link between the actual energy savings and the efficiency prescribed in energy codes. A research project aiming to identify opportunities to reduce energy consumption in new single-family residential construction by increasing compliance with the building energy code was conducted in several states of the United States. The study was comprised of three phases: (1) a baseline study to document typical practice and identify opportunities for improvement based on empirical data gathered from the field; (2) an education and training phase targeting the opportunities identified; and (3) a post-study to assess whether a reduction in average state-wide energy use could be achieved following the education and training phase. We proposed a novel methodology based on large-scale building energy simulation inferred by limited field data to assess the performance of a large population of homes. This paper presents the methodology, findings, and results of this study. The state-wide average energy consumption decreased at Phase III from Phase I for five of the seven states involved in the analysis. The measure-level savings potential analysis shows an overall reduction. Overall, the training and education phase plays a recognizable role in improving compliance with building energy codes.https://www.mdpi.com/1996-1073/13/9/2321building energy simulationbuilding energy code complianceenergy savings potentialMonte Carlobootstrap sampling |
| spellingShingle | Yulong Xie Mark Halverson Rosemarie Bartlett Yan Chen Michael Rosenberg Todd Taylor Jeremiah Williams Michael Reiner Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data Energies building energy simulation building energy code compliance energy savings potential Monte Carlo bootstrap sampling |
| title | Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data |
| title_full | Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data |
| title_fullStr | Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data |
| title_full_unstemmed | Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data |
| title_short | Evaluating Building Energy Code Compliance and Savings Potential through Large-Scale Simulation with Models Inferred by Field Data |
| title_sort | evaluating building energy code compliance and savings potential through large scale simulation with models inferred by field data |
| topic | building energy simulation building energy code compliance energy savings potential Monte Carlo bootstrap sampling |
| url | https://www.mdpi.com/1996-1073/13/9/2321 |
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