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Discussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generation

2018Conference object Open access
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dc.contributor.authorSilva, Cátia
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-02-18T11:51:24Z
dc.date.available2021-02-18T11:51:24Z
dc.date.issued2018
dc.description.abstractWith the introduction of the Smart Grid context in the current network, it will be necessary to improve business models to include the use of distributed generation and demand response programs regarding the remuneration of participants as a form of incentive. Throughout this article a methodology is presented which will aggregate generation units and consumers participating in DR programs. A comparison of clustering methods will be carried out in order to understand which one of them will be the most appropriate for the scenario studied. After grouping all the resources, the remuneration of the groups are made considering the maximum rate in each group. The hierarchical clustering proved to be the most appropriate because it grouped the resources so that the total cost for the aggregator was the minimum.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: CONTEST Project (P2020-23575), and UID/EEA/00760/2013 funded by FEDER Funds through, COMPETE program and by National Funds through FCT.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/SSCI.2018.8628781pt_PT
dc.identifier.isbn978-1-5386-9276-9
dc.identifier.urihttp://hdl.handle.net/10400.22/17038
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8628781pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectAggregationpt_PT
dc.subjectDemand responsept_PT
dc.subjectDistributed generationpt_PT
dc.subjectClustering Methodspt_PT
dc.subjectComputational intelligencept_PT
dc.subjectDemand side managementpt_PT
dc.subjectPower engineering computingpt_PT
dc.subjectAggregation costpt_PT
dc.titleDiscussing Different Clustering Methods for the Aggregation of Demand Response and Distributed Generationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.conferencePlaceBangalore, Indiapt_PT
oaire.citation.endPage1650pt_PT
oaire.citation.startPage1645pt_PT
oaire.citation.title2018 IEEE Symposium Series on Computational Intelligence (SSCI)pt_PT
oaire.fundingStream5876
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.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
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