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Daily Operation Optimization for Grid-Connected Hybrid System Considering Short-Term Electricity Price Forecast Scheme

2018-06-12Journal article Restricted access
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dc.contributor.authorBento, P.M.R.
dc.contributor.authorNunes, H.G.G.
dc.contributor.authorÁlvaro Nunes Pombo, José
dc.contributor.authorMariano, S.
dc.contributor.authorCalado, M. do Rosário
dc.date.accessioned2020-01-10T16:22:43Z
dc.date.available2020-01-10T16:22:43Z
dc.date.issued2018-06-12
dc.description.abstractWith an increasing public and governmental awareness regarding environment protection and sustainable resources, hand-in-hand with an escalating electricity demand, the exponential growth of renewable energy generation capacity has been the “answer”. Mitigating the environmental harms associated with the more conventional energy sources such as: coal, oil, gas and nuclear. Nonetheless, some challenges remain, particularly concerning the integration of these technologies into the conventional generation mix. Hybrid energy systems allow a paradigm shift from a concentrated conventional generation to a more distributed one. This paper discusses the optimized PVwind with hydro and battery storage capabilities for a gridconnected application considering the Short-Term Price Forecast information. The proposed technique has been tested in different scenarios, and results demonstrate the effectiveness of the proposed approach.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/EEEIC.2018.8493695pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/8213
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.subjectHybrid energy systemspt_PT
dc.subjectOptimized dispatch strategypt_PT
dc.subjectPhotovoltaic powerpt_PT
dc.subjectPumped-storage hydropowerpt_PT
dc.subjectShort-term price forecastingpt_PT
dc.subjectWind powerpt_PT
dc.subjectOptimized control strategypt_PT
dc.titleDaily Operation Optimization for Grid-Connected Hybrid System Considering Short-Term Electricity Price Forecast Schemept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlacePalermo, Italypt_PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2018 IEEE Int. Conf. on Environment and Electrical Engineering (EEEIC 2018)pt_PT
person.familyNameRocha Bento
person.familyNameGarcia Nunes
person.familyNamePombo
person.familyNamePinto Simões Mariano
person.familyNameCalado
person.givenNamePedro Miguel
person.givenNameHugo Gabriel
person.givenNameJose
person.givenNameSílvio José
person.givenNameM. do Rosário
person.identifier.ciencia-id7615-8E00-8084
person.identifier.ciencia-id541F-E2B4-D66D
person.identifier.ciencia-id9115-032B-370B
person.identifier.orcid0000-0002-9102-7086
person.identifier.orcid0000-0002-6029-7032
person.identifier.orcid0000-0002-8727-0067
person.identifier.orcid0000-0002-6102-5872
person.identifier.orcid0000-0002-5206-487X
person.identifier.ridV-4684-2018
person.identifier.ridN-6834-2013
person.identifier.ridN-6809-2013
person.identifier.scopus-author-id57196424786
person.identifier.scopus-author-id57195107686
person.identifier.scopus-author-id34977533800
person.identifier.scopus-author-id35612517200
person.identifier.scopus-author-id9338016700
rcaap.embargofctCopyright cedido à editora no momento da publicaçãopt_PT
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication40ed2120-90cf-41fa-84fc-d1c85cf8d848
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relation.isAuthorOfPublication.latestForDiscoverycce2060a-24b8-441b-8896-cb4d0b3d3e83

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