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Demand Response Shifting Management Applied to Distributed Generation and Pumping

dc.contributor.authorBoldt, Diogo
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-03-09T14:46:08Z
dc.date.available2021-03-09T14:46:08Z
dc.date.issued2015
dc.description.abstractRecent energy policies in countries around the world, including in Europe, point to the need to integrate growing amounts of distributed generation in electric power systems. This situation led to several changes in the operation and planning of power systems. This paper presents a methodology focusing on demand response programs, distributed generation and pumping, which is aimed to be used by a Virtual Power Player, who is able to manage the available resources minimizing the operation costs. The influence of demand response shifting management, in which was possible to shift load from a critical period to other more benefic, was also taken into account. In this paper it was used Artificial Intelligence, Artificial Neural Networks (ANN), to predict the power the VPP would have to pump to reservoirs to fulfill the reservoir operator demands along the day. The case study includes 2223 consumers and 47 distributed generators units. The implemented scenario corresponds to a real day in Portuguese power system, 9th March 2014.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: EUREKA - ITEA2 Project SEAS with project number 12004; H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); 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.2015.217pt_PT
dc.identifier.isbn978-1-4799-7560-0
dc.identifier.urihttp://hdl.handle.net/10400.22/17336
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/7376793pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectDemand responsept_PT
dc.subjectDistributed generationpt_PT
dc.subjectEnergy policiespt_PT
dc.subjectPortuguese power systempt_PT
dc.titleDemand Response Shifting Management Applied to Distributed Generation and Pumpingpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleEnabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/641794/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.conferencePlaceCape Town, South Africapt_PT
oaire.citation.endPage1544pt_PT
oaire.citation.startPage1537pt_PT
oaire.citation.title2015 IEEE Symposium Series on Computational Intelligencept_PT
oaire.fundingStreamH2020
oaire.fundingStream5876
person.familyNameFaria
person.familyNameVale
person.givenNamePedro
person.givenNameZita
person.identifier632184
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
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/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
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