Repository logo
 
Publication

Rating the participation in Demand Response events with a contextual approach to improve accuracy of aggregated schedule

2022Journal article Open access
Simple item page
dc.contributor.authorSilva, Cátia
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.contributor.authorTerras, José M.
dc.contributor.authorAlbuquerque, Susete
dc.date.accessioned2023-02-02T10:25:46Z
dc.date.available2023-02-02T10:25:46Z
dc.date.issued2022
dc.description.abstractThe flexibility provided by the demand side will be crucial to take a step forward to increase the penetration of renewable energy resources in the system. The proposed methodology provides the aggregator with information about the most reliable consumers, attributing a trustworthy rate that characterizes their performance on Demand Response (DR) events. The innovation relies on applying rates and evaluating the context in which the event is triggered and the factors that influence such rates. The authors find that context is essential to understand which participants are available for the event and achieve the reduction target successfully. Also, the proposed methodology focuses on the performance and the proper motivation for continuous participation, reducing the uncertainty of the response in DR events by giving higher economic compensation to the active consumers with better results. Distributed generation is also optimally managed by the aggregator. Findings prove the feasibility of the proposed methodology supporting the Aggregator in communities and smart cities management.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). Cátia Silva is supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with PhD grant reference SFRH/BD/144200/2019. Pedro Faria is supported by FCT with grant CEECIND/01423/2021. The authors acknowledge the work facilities and equipment provided by GECAD research center (UIDB/00760/2020) to the project team.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.egyr.2022.06.060pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/22096
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationNORTE-01- 0145-FEDER-000062pt_PT
dc.relationEffective DR gathering and deployment for intensive renewable integration using aggregation and machine learning
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2352484722012008?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectDemand Responsept_PT
dc.subjectUncertaintypt_PT
dc.subjectTrustworthy consumerspt_PT
dc.titleRating the participation in Demand Response events with a contextual approach to improve accuracy of aggregated schedulept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleEffective DR gathering and deployment for intensive renewable integration using aggregation and machine learning
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F144200%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.citation.endPage8300pt_PT
oaire.citation.startPage8282pt_PT
oaire.citation.titleEnergy Reportspt_PT
oaire.citation.volume8pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSilva
person.familyNameFaria
person.familyNameVale
person.givenNameCátia
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-id5318-DCFD-218D
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8306-4568
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication5eebf2bb-32f6-4593-a536-6db611d531e8
relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isProjectOfPublication251e8359-504b-430d-b43d-84097b01ccfe
relation.isProjectOfPublicationdb3e2edb-b8af-487a-b76a-f6790ac2d86e
relation.isProjectOfPublication.latestForDiscoverydb3e2edb-b8af-487a-b76a-f6790ac2d86e

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ART26_GECAD_ZAV_2022.pdf
Size:
4.18 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ISEP – GECAD – Artigos