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Clustering-based negotiation profiles definition for local energy transactions

2018Conference object Open access
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dc.contributor.authorPinto, Angelo
dc.contributor.authorPinto, Tiago
dc.contributor.authorPraça, Isabel
dc.contributor.authorVale, Zita
dc.contributor.authorFaria, Pedro
dc.date.accessioned2022-03-17T10:52:10Z
dc.date.available2022-03-17T10:52:10Z
dc.date.issued2018
dc.description.abstractElectricity markets are complex and dynamic environments, mostly due to the large scale integration of renewable energy sources in the system. Negotiation in these markets is a significant challenge, especially when considering negotiations at the local level (e.g., between buildings and distributed energy resources). It is essential for a negotiator to be able to identify the negotiation profile of the players with whom he is negotiating. If a negotiator knows these profiles, it is possible to adapt the negotiation strategy and get better results in a negotiation. In order to identify and define such negotiation profiles, a clustering process is proposed in this paper. The clustering process is performed using the kml-k-means algorithm, in which several negotiation approaches are evaluated in order to identify and define players' negotiation profiles. A case study is presented, using as input data, information from proposals made during a set of negotiations. Results show that the proposed approach is able to identify players' negotiation profiles used in bilateral negotiations in electricity markets.pt_PT
dc.description.sponsorshipThis work has been developed under the CONTEST project - SAICTPOL/23575/2016 and has received funding from 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/SmartGridComm.2018.8587572pt_PT
dc.identifier.isbn978-1-5386-7954-8
dc.identifier.urihttp://hdl.handle.net/10400.22/20275
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8587572pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectClusteringpt_PT
dc.subjectLocal energy marketspt_PT
dc.subjectProfile modellingpt_PT
dc.subjectk-means algorithmpt_PT
dc.subjectClustering algorithmspt_PT
dc.subjectBuildingspt_PT
dc.titleClustering-based negotiation profiles definition for local energy transactionspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.conferencePlaceAalborg , Denmarkpt_PT
oaire.citation.endPage5pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)pt_PT
oaire.fundingStream5876
person.familyNamePinto
person.familyNamePraça
person.familyNameVale
person.familyNameFaria
person.givenNameTiago
person.givenNameIsabel
person.givenNameZita
person.givenNamePedro
person.identifierR-000-T7J
person.identifier299522
person.identifier632184
person.identifier.ciencia-id2414-9B03-C4BB
person.identifier.ciencia-idC710-4218-1BFF
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.orcid0000-0001-8248-080X
person.identifier.orcid0000-0002-2519-9859
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0002-5982-8342
person.identifier.ridT-2245-2018
person.identifier.ridK-8430-2014
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35219107600
person.identifier.scopus-author-id22734900800
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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