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dc.contributor.authorCanals Casals, Lluc
dc.contributor.authorCorchero García, Cristina
dc.contributor.authorOrtiz, Joana
dc.contributor.authorSalom, Jaume
dc.contributor.authorCardoner, David
dc.contributor.authorIgualada González, Lucía
dc.contributor.authorCarrillo, Rafael E.
dc.contributor.authorStauffer, Yves
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció
dc.contributor.otherFacultat d'Informàtica de Barcelona
dc.contributor.otherInstitut de Recerca en Energía de Catalunya
dc.date.accessioned2020-07-13T08:20:26Z
dc.date.available2020-07-13T08:20:26Z
dc.date.issued2019
dc.identifier.citationCanals Casals, L. [et al.]. How building and district algorithms enhance renewable energy integration in energy markets. A: International Conference on the European Energy Market. "Electricity Market (EEM), International Conference on European". 2019, p. 1-5.
dc.identifier.isbn978-1-7281-1257-2
dc.identifier.urihttp://hdl.handle.net/2117/192881
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
dc.description.abstractThis study shows the results of the SABINA H2020 project, which analyzes the effect of two level optimization algorithms to increase the consumption of renewable power sources and reduce greenhouse gas emissions. First, at building level, a building algorithm maximizes the self-consumption of generated energy by its own renewable power sources. Second, at district level, a market integrated district algorithm takes into account aspects related to the electricity grid, such as the electricity generation mix and the prices of electricity and ancillary services, and aggregates the energy flexibility forecast of buildings to minimize the overall CO 2 emissions while ensuring a cost reduction to prosumers
dc.format.extent5 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Energies
dc.subject.lcshEnergy industries
dc.subject.lcshRenewable energy sources
dc.titleHow building and district algorithms enhance renewable energy integration in energy markets
dc.typeConference report
dc.subject.lemacIndústries energètiques
dc.subject.lemacEnergies renovables
dc.contributor.groupUniversitat Politècnica de Catalunya. GIIP - Grup de Recerca en Enginyeria de Projectes: Disseny, Sostenibilitat i Comunicació
dc.contributor.groupUniversitat Politècnica de Catalunya. GNOM - Grup d'Optimització Numèrica i Modelització
dc.identifier.doi10.1109/EEM.2019.8916457
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8916457
dc.rights.accessOpen Access
local.identifier.drac28497576
dc.description.versionPostprint (published version)
local.citation.authorCanals Casals, L.; Corchero, C.; Ortiz, J.; Salom, J.; Cardoner, D.; Igualada , L.; Carrillo, R. E.; Stauffer, Y.
local.citation.contributorInternational Conference on the European Energy Market
local.citation.publicationNameElectricity Market (EEM), International Conference on European
local.citation.startingPage1
local.citation.endingPage5


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