Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Morris, Peter, Vine, Desley, & Buys, Laurie (2015) Application of a Bayesian Network complex system model to a successful community electricity demand reduction program. Energy, 84(1), pp. 63-74.

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Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

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6 citations in Scopus
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4 citations in Web of Science®

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ID Code: 83176
Item Type: Journal Article
Refereed: Yes
Keywords: Residential electricity use, Peak demand, Bayesian network, Complex systems model, Multi-disciplinary
DOI: 10.1016/
ISSN: 0360-5442
Divisions: Current > Schools > School of Design
Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Creative Industries Faculty
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Elsevier Ltd.
Copyright Statement: This is the author’s version of a work that was accepted for publication in Energy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Energy, [VOL 84 , 2015] DOI: 10.1016/
Deposited On: 07 Apr 2015 22:23
Last Modified: 12 May 2015 17:30

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