Modelling “Cognitive Households Digital Twins” in an Energy Community

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Available literature suggests that households consume a considerable amount of energy in contemporary societies. Many techniques expected to help reduce the impact of households’ energy consumption have been suggested in several studies. Cognitive Household Digital Twins (CHDT) is one of such ideas perceived to facilitate rational decision-making regarding energy consumption. A CHDT could be described as a digital replica/model of a household within the cyber-physical space. Such digital twins could possess some attributes such as cognitive capabilities, enabling them to make decisions based on some level of delegated authority from their physical twin. The outcomes of their decisions are expected to increase the sustainable energy consumption of the physical twin. In this study, we demonstrate how CHDTs can exhibit such cognitive and decision-making capabilities using software simulation. In our approach, we modelled a community of CHDTs who collaborate to jointly execute a common task, in this case, jointly minimize consumption, hoping to maximize the opportunity to sell energy to the grid. We adopted a multi-method simulation technique that involves multiple simulation paradigms integrated onto a single simulation platform. The adopted paradigms include System Dynamics, Agent-Based, and Discrete Event simulation techniques. The study's outcome suggests that CHDTs can be a valuable form of autonomous entity that can assist as complimentary decision-making agents in households.
Original languageEnglish
Title of host publication The Proceedings of the International Conference on Electrical Systems & Automation
EditorsMohamed Bendaoud, Borutzky Wolfgang, Khalid Chikh
Place of PublicationSingapore
PublisherSpringer
Pages67-79
Number of pages13
ISBN (Electronic)978-981-19-0039-6
ISBN (Print)978-981-19-0038-9
DOIs
Publication statusPublished - 31 Mar 2022

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