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Building electricity consumption: Data analytics of building operations with classical time series decomposition and case based subsetting

Pickering, Ethan M. and Hossain, Mohammad A. and French, Roger H. and Abramson, Alexis R. (2018) Building electricity consumption: Data analytics of building operations with classical time series decomposition and case based subsetting. Energy and Buildings, 177 . pp. 184-196. ISSN 0378-7788. https://resolver.caltech.edu/CaltechAUTHORS:20181101-073924640

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Abstract

The commercial building sector consumes approximately one-fifth of U.S. total energy and exhibits significant operational inefficiencies, leaving a great opportunity to implement various energy-efficiency measures. However, conventional energy audit techniques are expensive, time-consuming, and frequently inaccurate. Conversely, classical time series decomposition of smart meter (i.e. 15 min interval) building electricity consumption provides quick, inexpensive, and useful insights to building operation and characteristics. Paired with complementary time series datasets such as outdoor temperature and solar irradiation, specific insights into HVAC scheduling, daily operational variation, and the relative impact of temperature and solar radiation were quantitatively assessed. This work analyzes six commercial buildings and identifies various building characteristics, including the potential for savings of over 700 MWh valued at $92,000 per year from building rescheduling alone. With access to only whole building smart meter data, these results are obtained virtually and instantaneously, making the case for a rigorous data analytics approach to unlock the potential of building energy efficiency.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.enbuild.2018.07.056DOIArticle
ORCID:
AuthorORCID
Pickering, Ethan M.0000-0002-4485-6359
French, Roger H.0000-0002-6162-0532
Additional Information:© 2018 Elsevier B.V. Received 22 February 2018, Revised 13 June 2018, Accepted 25 July 2018, Available online 9 August 2018.
Subject Keywords:Building energy efficiency; Classical time series decomposition; Data analytics; Commercial buildings; Virtual energy audit
Record Number:CaltechAUTHORS:20181101-073924640
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20181101-073924640
Official Citation:Ethan M. Pickering, Mohammad A. Hossain, Roger H. French, Alexis R. Abramson, Building electricity consumption: Data analytics of building operations with classical time series decomposition and case based subsetting, Energy and Buildings, Volume 177, 2018, Pages 184-196, ISSN 0378-7788, https://doi.org/10.1016/j.enbuild.2018.07.056. (http://www.sciencedirect.com/science/article/pii/S0378778818306029)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90552
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:01 Nov 2018 17:31
Last Modified:03 Oct 2019 20:26

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