A measure to manage approach to characterizing the energy impact of residential building stocks

Afamia Elnakat; Juan D. Gomez; Martha Wright; Afamia Elnakat; Juan D. Gomez; Martha Wright

doi:10.3934/energy.2016.4.574

AIMS Energy

2016, Volume 4, Issue 4: 574-588. doi: 10.3934/energy.2016.4.574

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A measure to manage approach to characterizing the energy impact of residential building stocks

Texas Sustainable Energy Research Institute, University of Texas, San Antonio, TX 78249, USA

Received: 31 March 2016 Accepted: 20 May 2016 Published: 26 May 2016

The city of San Antonio is the seventh largest in the United States by population and the second in the state of Texas, with a population of over 1.3 million people. As one of the fastest growing cities, the San Antonio residential real estate market has expanded to meet the demands of the growing population. Managing the energy footprint of single-family houses can be enhanced by big data analysis of combined metered energy consumption and building infrastructure characteristics. This study analyzes the energy intensity of 389,160 single family detached homes and identifies energy utilization trends across various residential building stock size and vintage categories. Supported by the “measure to manage” premise, this study highlights the value of this characterization as a forecasting and planning tool for sustainable growth and a more engaged consumer.
- Energy efficiency,
- energy intensity,
- residential energy consumption,
- measure to manage,
- residential building characterization,
- forecasting energy demand
Citation: Afamia Elnakat, Juan D. Gomez, Martha Wright. A measure to manage approach to characterizing the energy impact of residential building stocks[J]. AIMS Energy, 2016, 4(4): 574-588. doi: 10.3934/energy.2016.4.574

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Abstract

The city of San Antonio is the seventh largest in the United States by population and the second in the state of Texas, with a population of over 1.3 million people. As one of the fastest growing cities, the San Antonio residential real estate market has expanded to meet the demands of the growing population. Managing the energy footprint of single-family houses can be enhanced by big data analysis of combined metered energy consumption and building infrastructure characteristics. This study analyzes the energy intensity of 389,160 single family detached homes and identifies energy utilization trends across various residential building stock size and vintage categories. Supported by the “measure to manage” premise, this study highlights the value of this characterization as a forecasting and planning tool for sustainable growth and a more engaged consumer.

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