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Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods

2019Conference object Open access
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dc.contributor.authorSilva, Cátia
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2023-02-23T15:56:01Z
dc.date.available2023-02-23T15:56:01Z
dc.date.issued2019
dc.description.abstractNowadays, the data can be considered an asset when properly managed. An entity with the right tool to analyse the amount of data existent and withdraw crucial information will have the power to obliterate the competition. In the Energy sector, with Smart Grid introduction, small resources have more influence in the market through Demand Response and bidirectional communication. However, none of the actual business models is prepared to deal with the uncertainty related to these resources. The authors, in order to find a solution for this complex problem, proposed a methodology which the goal is to minimize operation costs and give fair compensation for resources who participate in the management of local markets. With this fair payment, it is expected continuous participation. Through clustering methods, remuneration groups are created. In the present paper, a study about the optimal number of clusters is performed. The information gives the Aggregator control in results of the following phases, understanding the impact in the remuneration of the resources.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: COLORS Project, CEECIND/02887/2017, and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT. Cátia Silva is supported by Fundação para a Ciência e a Tecnologia (FCT), grant SFRH/BD/144200/2019.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationC. Silva, P. Faria and Z. Vale, "Defining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methods," 2019 20th International Conference on Intelligent System Application to Power Systems (ISAP), 2019, pp. 1-6, doi: 10.1109/ISAP48318.2019.9065957.pt_PT
dc.identifier.doi10.1109/ISAP48318.2019.9065957pt_PT
dc.identifier.isbn978-1-72813-192-4
dc.identifier.urihttp://hdl.handle.net/10400.22/22383
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationCEECIND/02887/2017pt_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://ieeexplore.ieee.org/document/9065957pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/pt_PT
dc.subjectClusteringpt_PT
dc.subjectAggregationpt_PT
dc.subjectConsumerspt_PT
dc.subjectRemunerationpt_PT
dc.subjectEnergy Marketpt_PT
dc.titleDefining the Optimal Number of Demand Response Programs and Tariffs Using Clustering Methodspt_PT
dc.typeconference object
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/UID%2FEEA%2F00760%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F144200%2F2019/PT
oaire.citation.conferencePlaceNew Delhi, Indiapt_PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)pt_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.typeconferenceObjectpt_PT
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