Publication
Smart Grid Ecosystem Modeling Using a Novel Framework for Heterogenous Agent Communities
| dc.contributor.author | Pereira, Helder | |
| dc.contributor.author | Ribeiro, Bruno | |
| dc.contributor.author | Gomes, Luis | |
| dc.contributor.author | Vale, Zita | |
| dc.date.accessioned | 2023-02-02T10:46:15Z | |
| dc.date.available | 2023-02-02T10:46:15Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | The modeling of smart grids using multi-agent systems is a common approach due to the ability to model complex and distributed systems using an agent-based solution. However, the use of a multi-agent system framework can limit the integration of new operation and management models, especially artificial intelligence algorithms. Therefore, this paper presents a study of available open-source multi-agent systems frameworks developed in Python, as it is a growing programming language and is largely used for data analytics and artificial intelligence models. As a consequence of the presented study, the authors proposed a novel open-source multi-agent system framework built for smart grid modeling, entitled Python-based framework for heterogeneous agent communities (PEAK). This framework enables the use of simulation environments but also allows real integration at pilot sites using a real-time clock. To demonstrate the capabilities of the PEAK framework, a novel agent ecosystem based on agent communities is shown and tested. This novel ecosystem, entitled Agent-based ecosystem for Smart Grid modeling (A4SG), takes full advantage of the PEAK framework and enables agent mobility, agent branching, and dynamic agent communities. An energy community of 20 prosumers, of which six have energy storage systems, that can share energy among them, using a peer-to-peer market, is used to test and validate the PEAK and A4SG solutions. | pt_PT |
| dc.description.sponsorship | The authors acknowledge the work facilities and equipment provided by the GECAD research center (UIDB/00760/2020) to the project team. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.3390/su142315983 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/22101 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| dc.relation.publisherversion | https://www.mdpi.com/2071-1050/14/23/15983 | pt_PT |
| dc.subject | Multi-agent systems | pt_PT |
| dc.subject | Smart grid modeling | pt_PT |
| dc.subject | Agent mobility | pt_PT |
| dc.subject | Agent branching | pt_PT |
| dc.title | Smart Grid Ecosystem Modeling Using a Novel Framework for Heterogenous Agent Communities | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | |
| oaire.citation.issue | 23 | pt_PT |
| oaire.citation.startPage | 15983 | pt_PT |
| oaire.citation.title | Sustainability | pt_PT |
| oaire.citation.volume | 14 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Vale | |
| person.givenName | Zita | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | 6F19-CB63-C8A8 | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.orcid | 0000-0002-8597-3383 | |
| person.identifier.orcid | 0000-0002-4560-9544 | |
| person.identifier.rid | A-5824-2012 | |
| person.identifier.scopus-author-id | 7004115775 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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