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A Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertainties

dc.contributor.authorBorges, Nuno
dc.contributor.authorSoares, João
dc.contributor.authorVale, Zita
dc.date.accessioned2021-03-09T11:25:58Z
dc.date.available2021-03-09T11:25:58Z
dc.date.issued2017
dc.description.abstractThis paper presents a Particle Swarm Optimization (PSO) methodology to solve the problem of day-ahead microgrid (MG) dispatch with high penetration of Distributed Generation (DG) and considering uncertainties. The proposed methodology has the objective to satisfy demand aiming at obtaining the maximum profit, corresponding to the difference between the income and costs of the MG. This methodology considers the uncertainties associated with the production of electricity by the photovoltaic and wind sources. This uncertainty is modeled with the use of a robust approach in PSO. A case study is presented using a 21-bus MG from a real university campus in Portugal, and the projection of distributed energy resources based on the evolution scenario for the year 2050 managed by an aggregator.pt_PT
dc.description.sponsorshipThis work has received funding from the Project NetEffiCity (ANI|P2020 18015), and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.ifacol.2017.08.521pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/17319
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.relationANI|P2020 18015pt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2405896317308893?via%3Dihubpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEnergy Resources Managementpt_PT
dc.subjectMicrogridspt_PT
dc.subjectParticle Swarm Optimizationpt_PT
dc.subjectRobust Optimizationpt_PT
dc.titleA Robust Optimization for Day-ahead Microgrid Dispatch Considering Uncertaintiespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.endPage3355pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage3350pt_PT
oaire.citation.titleIFAC-PapersOnLinept_PT
oaire.citation.volume50pt_PT
oaire.fundingStream5876
person.familyNameSoares
person.familyNameVale
person.givenNameJoão
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
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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