Application of a Bayesian Network complex system model to a successful community electricity demand reduction program. Morris, P., Vine, D., & Buys, L. Energy, 3, 2015. ![Application of a Bayesian Network complex system model to a successful community electricity demand reduction program [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex 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.
@article{
title = {Application of a Bayesian Network complex system model to a successful community electricity demand reduction program},
type = {article},
year = {2015},
keywords = {Bayesian network,Complex systems model,Multi-disciplinary,Peak demand,Residential electricity use},
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abstract = {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.},
bibtype = {article},
author = {Morris, Peter and Vine, Desley and Buys, Laurie},
doi = {10.1016/j.energy.2015.02.019},
journal = {Energy}
}
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