TY - GEN
T1 - Modelling Mutual Influence Towards Sustainable Energy Consumption
AU - Adu-Kankam, Kankam O.
AU - Camarinha-Matos, Luís M.
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT#
Publisher Copyright:
© 2022, IFIP International Federation for Information Processing.
PY - 2022/6
Y1 - 2022/6
N2 - The notions of Collaborative Virtual Power Plant Ecosystem (CVPP-E) and Cognitive Household Digital Twin (CHDT) have been proposed to contribute to the efficient organization and management of households within Renewable Energy Communities (RECs). Both ideas can be represented by digital twins, which complement each other. CHDTs can be modelled as software agents, designed to possess some cognitive capabilities which could enable them to make autonomous decisions, based on the preferences or value system of their owner. Due to their cognitive and decision-making capabilities, these agents could exhibit some behavioural attributes such as engaging in collaborations, mutually influencing one another and the ability to adopt some form of social innovation. These behavioural attributes are expected to promote collaboration which are envisioned to increase the survivability and sustainability of the CVPP-E. This study therefore seeks to demonstrate the capability of CHDTs to mutually influence one another towards a common goal - thus promote sustainable energy consumption. We adopted a multi-method simulation technique that involves the integration of multiple simulation paradigms such as System Dynamics, Agent-Based, and Discrete Event simulation techniques on a single simulation platform. The outcome of the study shows that mutual influence could enhance the sustainable consumption in the ecosystem.
AB - The notions of Collaborative Virtual Power Plant Ecosystem (CVPP-E) and Cognitive Household Digital Twin (CHDT) have been proposed to contribute to the efficient organization and management of households within Renewable Energy Communities (RECs). Both ideas can be represented by digital twins, which complement each other. CHDTs can be modelled as software agents, designed to possess some cognitive capabilities which could enable them to make autonomous decisions, based on the preferences or value system of their owner. Due to their cognitive and decision-making capabilities, these agents could exhibit some behavioural attributes such as engaging in collaborations, mutually influencing one another and the ability to adopt some form of social innovation. These behavioural attributes are expected to promote collaboration which are envisioned to increase the survivability and sustainability of the CVPP-E. This study therefore seeks to demonstrate the capability of CHDTs to mutually influence one another towards a common goal - thus promote sustainable energy consumption. We adopted a multi-method simulation technique that involves the integration of multiple simulation paradigms such as System Dynamics, Agent-Based, and Discrete Event simulation techniques on a single simulation platform. The outcome of the study shows that mutual influence could enhance the sustainable consumption in the ecosystem.
KW - Collaborative networks
KW - Digital twins
KW - Mutual influence
KW - Renewable energy communities
KW - Sustainable consumption
UR - http://www.scopus.com/inward/record.url?scp=85134330425&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-07520-9_1
DO - 10.1007/978-3-031-07520-9_1
M3 - Conference contribution
AN - SCOPUS:85134330425
SN - 978-3-031-07519-3
T3 - IFIP Advances in Information and Communication Technology
SP - 3
EP - 15
BT - Technological Innovation for Digitalization and Virtualization
A2 - Camarinha-Matos, Luís M.
PB - Springer
CY - Cham
T2 - 13th Advanced Doctoral Conference on Computing, Electrical, and Industrial Systems, DoCEIS 2022
Y2 - 29 June 2022 through 1 July 2022
ER -
