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Targeted selection of participants for energy efficiency programs using genetic agent-based (GAB) framework

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Abstract

Many studies show that the human energy-related behaviors have a significant impact on the return of Energy Efficiency Programs (EEPs). However, studies that aimed at increasing the energy savings from the EEPs are still limited. In this paper, a Genetic Agent-Based (GAB) framework has been proposed to enhance the return of a typical EEP by simulating social network and energy behavior attributes and finding the best participants among a target community. Several attributes are considered for creating the agent-based model of households and numerically representing their interactions with the EEP or within their social network. The improvement of the EEP using the GAB framework is tested on a social network consisting of 56 households. The simulation results show that by accurately selecting participants using the presented framework, the amount of energy saving could increase up to ten times. This ultimately indicates the considerable impact of the social network on the EEP performance. In other words, to have an efficient EEP in the long term, the social network attributes such as network degree and strength of connections should be also considered in decision-making along with the energy-related attributes.

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Authors and Affiliations

  1. Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

    Mohammad Zarei & Mojtaba Maghrebi

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  1. Mohammad Zarei
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  2. Mojtaba Maghrebi
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Correspondence to Mojtaba Maghrebi.

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Zarei, M., Maghrebi, M. Targeted selection of participants for energy efficiency programs using genetic agent-based (GAB) framework. Energy Efficiency 13, 823–833 (2020). https://doi.org/10.1007/s12053-020-09841-z

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