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Modeling Collaborative Behaviors in Energy Ecosystems

2023-02-13Artigo científico Acesso aberto
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dc.contributor.authorAdu-Kankam, Kankam Okatakyie
dc.contributor.authorCamarinha-Matos, Luís Manuel
dc.contributor.institutionDEE - Departamento de Engenharia Electrotécnica e de Computadores
dc.contributor.institutionUNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
dc.contributor.institutionCTS - Centro de Tecnologia e Sistemas
dc.contributor.institutionDEE2010-C2 Robótica e Manufactura Integrada por Computador
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2023-04-03T22:14:49Z
dc.date.available2023-04-03T22:14:49Z
dc.date.issued2023-02-13
dc.description© 2023 by the authors. Licensee MDPI, Basel, Switzerland
dc.description.abstractThe notions of a collaborative virtual power plant ecosystem (CVPP-E) and a cognitive household digital twin (CHDT) have been proposed as contributions to the efficient organization and management of households within renewable energy communities (RECs). CHDTs can be modeled as software agents that are designed to possess some cognitive capabilities, enabling them to make autonomous decisions on behalf of their human owners based on the value system of their physical twin. Due to their cognitive and decision-making capabilities, these agents can exhibit some behavioral attributes, such as engaging in diverse collaborative actions aimed at achieving some common goals. These behavioral attributes can be directed to the promotion of sustainable energy consumption in the ecosystem. Along this line, this work demonstrates various collaborative practices that include: (1) collaborative roles played by the CVPP manager such as (a) opportunity seeking and goal formulation, (b) goal proposition/invitation to form a coalition or virtual organization, and (c) formation and dissolution of coalitions; and (2) collaborative roles played by CHDTs which include (a) acceptance or decline of an invitation based on (i) delegation/non-delegation and (ii) value system compatibility/non-compatibility, and (b) the sharing of common resources. This study adopts a simulation technique that involves the integration of multiple simulation methods such as system dynamics, agent-based, and discrete event simulation techniques in a single simulation environment. The outcome of this study confirms the potential of adding cognitive capabilities to CHDTs and further shows that these agents could exhibit certain collaborative attributes, enabling them to become suitable as rational decision-making agents in households.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent38
dc.format.extent10182796
dc.identifier.doi10.3390/computers12020039
dc.identifier.issn2073-431X
dc.identifier.otherPURE: 57157390
dc.identifier.otherPURE UUID: 7ebc9a9a-a22b-425e-841f-59fda185947a
dc.identifier.otherWOS: 000938895200001
dc.identifier.otherWOS: 85148758962
dc.identifier.otherScopus: 85148758962
dc.identifier.urihttp://hdl.handle.net/10362/151542
dc.language.isoeng
dc.peerreviewedyes
dc.relationFunding: info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT
dc.subjectSDG 7 - Affordable and Clean Energy
dc.subjectSDG 11 - Sustainable Cities and Communities
dc.subjectSDG 16 - Peace, Justice and Strong Institutions
dc.subjectSDG 17 - Partnerships for the Goals
dc.titleModeling Collaborative Behaviors in Energy Ecosystemsen
dc.typejournal article
degois.publication.issue2
degois.publication.titleComputers
degois.publication.volume12
dspace.entity.typePublication
rcaap.rightsopenAccess

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