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Rating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Period

2020Journal article Open access
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dc.contributor.authorSilva, Cátia
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-02-03T16:24:52Z
dc.date.available2021-02-03T16:24:52Z
dc.date.issued2020
dc.description.abstractAggregation of small size consumers and Distributed Generation (DG) units have a considerable impact to catch the full flexibility potential, in the context of Demand Response programs. New incentive mechanisms are needed to remunerate consumers adequately and to recognize the ones that have more reliable participation. The authors propose an innovative approach to be used in the operation phase, to deal with the uncertainty to Demand Response events, where a certain target is requested for an energy community managed by the Aggregator. The innovative content deals with assigning and updating a Reliability Rate to each consumer according to the actual response in a reduction request. Three distinct methods have been implemented and compared. The initial rates assigned according to participation in the Demand Response events after one month of the enrolment period and the ones with higher reliability follow scheduling, performed using linear optimization. The results prove that using the proposed approach, the energy community manager finds the more reliable consumers in each period, and the reduction target achieved in DR events. A clustering algorithm is implemented to determine the final consumer rate for one month considering the centroid valuept_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: UIDB/00760/2020 and CEECIND/02887/2017funded by FEDER Funds through the COMPETE program. This work has also received funding from the European Union’s Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066). Cátia Silva is supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with PhD grant reference SFRH/BD/144200/2019.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/electronics9020349pt_PT
dc.identifier.issn2079-9292
dc.identifier.urihttp://hdl.handle.net/10400.22/16857
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relationEffective DR gathering and deployment for intensive renewable integration using aggregation and machine learning
dc.relation.publisherversionhttps://www.mdpi.com/2079-9292/9/2/349/htmpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/pt_PT
dc.subjectClusteringpt_PT
dc.subjectConsumerspt_PT
dc.subjectDemand responsept_PT
dc.subjectUncertaintypt_PT
dc.titleRating the Participation in Demand Response Programs for a More Accurate Aggregated Schedule of Consumers after Enrolment Periodpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardTitleEffective DR gathering and deployment for intensive renewable integration using aggregation and machine learning
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F144200%2F2019/PT
oaire.citation.issue2pt_PT
oaire.citation.startPage349pt_PT
oaire.citation.titleElectronicspt_PT
oaire.citation.volume9pt_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
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