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Understanding the effects of environmental factors on building energy efficiency designs and credits: Case studies using data mining and real-time data

Jonghoon Kim (Arizona State University, Tempe, Arizona, USA)
Jin-Young Hyun (University of Louisville, Louisville, Kentucky, USA)
Wai K. Chong (School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA)
Samuel Ariaratnam (School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, Arizona, USA)

Journal of Engineering, Design and Technology

ISSN: 1726-0531

Article publication date: 5 June 2017

Abstract

Purpose

The purpose of this study was to explore the relationship between environmental factors and building energy consumption of three Leadership in Energy and Environmental Design (LEED)-certified buildings at the Arizona State University, by establishing the relationships of the outside atmospheric temperature and the energy consumed in the building using real-time data generated from different sources.

Design/methodology/approach

K-means clustering analysis is used to calibrate and eliminate unwanted influences or factors from a set of building consumption real-time data. For further statistical analysis, the chi-square is used to verify if the results are ample to prove the findings.

Findings

Few studies have addressed building energy consumption real-time data versus LEED Energy and Atmosphere (EA) credits with the data mining technique (k-means clustering) on most of building performance analyses. This study highlighted that the calibrating energy data are a better approach to analyze energy use in buildings and that there is a relationship between LEED credits’ (EA) Optimize Energy Performance scores and building energy efficiency. However, the energy consumption data alone do not yield useful results to establish the cause and effect relationships.

Originality/value

Although there are several previous research studies regarding LEED building energy performance, this research study focused on the LEED building energy performance versus LEED EA credits versus environmental factors using real-time building energy data and various statistical methods (e.g. K-means clustering and chi-square). The findings provide researchers, engineers and architects with valuable references for building energy analysis methods and supplements in LEED standards.

Keywords

Acknowledgements

The research team is not disputing the importance of these energy efficiency credits, but wish to highlight the importance of external factors in influencing energy consumption in buildings. The authors express appreciation to Patricia Olson (Senior Architect) and Robert Vandling (Technology Support Analyst) at the ASU for graciously making the data available for this study.

Citation

Kim, J., Hyun, J.-Y., Chong, W.K. and Ariaratnam, S. (2017), "Understanding the effects of environmental factors on building energy efficiency designs and credits: Case studies using data mining and real-time data", Journal of Engineering, Design and Technology, Vol. 15 No. 03, pp. 270-285. https://doi.org/10.1108/JEDT-12-2015-0082

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited