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Evaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Response

2022Journal article Open access
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dc.contributor.authorBarreto, Rúben
dc.contributor.authorGoncalves, Calvin
dc.contributor.authorGomes, Luis
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2023-02-01T11:00:56Z
dc.date.available2023-02-01T11:00:56Z
dc.date.issued2022
dc.description.abstractIn the energy sector, prosumers are becoming relevant entities for energy management systems since they can share energy with their citizen energy community (CEC). Thus, this paper proposes a novel methodology based on demand response (DR) participation in a CEC context, where unsupervised learning algorithms such as convolutional neural networks and k-means are used. This novel methodology can analyze future events on the grid and balance the consumption and generation using end-user flexibility. The end-users’ invitations to the DR event were according to their ranking obtained through three metrics. These metrics were energy flexibility, participation ratio, and flexibility history of the end-users. During the DR event, a continuous balancing assessment is performed to allow the invitation of additional end-users. Real data from a CEC with 50 buildings were used, where the results demonstrated that the end-users’ participation in two DR events allows reduction of energy costs by EUR 1.31, balancing the CEC energy resources.pt_PT
dc.description.sponsorshipThis article is a result of the project RETINA (NORTE-01-0145-FEDER-000062), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). The authors acknowledge the support of the GECAD research center (UIDB/ 00760/2020) for providing to the project team the needed work facilities and equipment.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/en15072380pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/22058
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationNORTE-01-0145-FEDER-000062pt_PT
dc.relationUIDB/ 00760/2020pt_PT
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/15/7/2380pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectCitizen energy communitypt_PT
dc.subjectDemand responsept_PT
dc.subjectEnd-user participationpt_PT
dc.subjectEnergy flexibilitypt_PT
dc.subjectUnsupervised learningpt_PT
dc.titleEvaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Responsept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue7pt_PT
oaire.citation.startPage2380pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume15pt_PT
person.familyNameBarreto
person.familyNameGoncalves
person.familyNameFaria
person.familyNameVale
person.givenNameRúben
person.givenNameCalvin
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-idC71C-A2AB-534A
person.identifier.ciencia-id6F19-CB63-C8A8
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-5574-6972
person.identifier.orcid0000-0003-2214-3814
person.identifier.orcid0000-0002-8597-3383
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id57211286931
person.identifier.scopus-author-id7004115775
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication.latestForDiscovery35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6

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