Abstract
Residential buildings consume a significant portion of energy and electricity in the US. The residential housing stock in rural areas of the US specifically is more likely to be older and less energy-efficient than those homes built in more urban areas. Improving the energy efficiency of such residential buildings includes benefits such as overall reduction in emissions resulting from building operations, and reduction in costs to the building occupants. In order to accomplish these goals, understanding the energy performance characteristics of buildings in these rural areas is important. This can help to better define which buildings are in greatest need of energy efficiency retrofits, and establish a framework by which to target such buildings for performance improvements through efforts such as utility-supported rebate programs. However, to date, the study of rural residential buildings has been limited, in part, due to the lack of available data and detailed information on buildings. In this research, through collaboration with the communities of Ames, Bloomfield, and Cedar Falls, Iowa, US, building energy use data and building characteristic data were used to assess the overall characteristics and energy performance of rural residential buildings. Using statistical analysis and data mining techniques, this study investigates the differential changes in energy use intensity (EUI) relative to the average built area, the building age, among others. Such evaluations can be used to design retrofit and rebate policies and programs that benefit both individual building occupants, and also address absolute levels of consumption now and moving forward.
Original language | English (US) |
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Title of host publication | Construction Research Congress 2022 |
Subtitle of host publication | Computer Applications, Automation, and Data Analytics - Selected Papers from Construction Research Congress 2022 |
Editors | Farrokh Jazizadeh, Tripp Shealy, Michael J. Garvin |
Publisher | American Society of Civil Engineers (ASCE) |
Pages | 164-173 |
Number of pages | 10 |
ISBN (Electronic) | 9780784483961 |
DOIs | |
State | Published - 2022 |
Externally published | Yes |
Event | Construction Research Congress 2022: Computer Applications, Automation, and Data Analytics, CRC 2022 - Arlington, United States Duration: Mar 9 2022 → Mar 12 2022 |
Publication series
Name | Construction Research Congress 2022: Computer Applications, Automation, and Data Analytics - Selected Papers from Construction Research Congress 2022 |
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Volume | 2-B |
Conference
Conference | Construction Research Congress 2022: Computer Applications, Automation, and Data Analytics, CRC 2022 |
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Country/Territory | United States |
City | Arlington |
Period | 3/9/22 → 3/12/22 |
Bibliographical note
Publisher Copyright:© 2022 Construction Research Congress 2022: Computer Applications, Automation, and Data Analytics - Selected Papers from Construction Research Congress 2022. All rights reserved.