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Unit commitment based on risk assessment to systems with variable power sources

dc.contributor.authorFonte, Pedro M
dc.contributor.authorMonteiro, Cláudio
dc.contributor.authorBarbosa, Fernando Maciel
dc.date.accessioned2018-07-09T09:22:50Z
dc.date.available2018-07-09T09:22:50Z
dc.date.issued2016-12
dc.description.abstractThis paper presents the development of a complete methodology for power systems scheduling with highly variable sources based on a risk assessment model. The methodology is tested in a real case study, namely an island with high penetration of renewable energy production. The uncertainty of renewable power production forecasts and load demand are defined by the probability distribution function, which can be a good alternative to the scenarios approach. The production mix chosen for each hour results from the costs associated to the operation risks, such as load shed and renewable production curtailment. The results to a seven days case study allow concluding about the difficulty to achieve a complete robust solution.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFONTE, Pedro Miguel; MONTEIRO, Cláudio; BARBOSA, Fernando Maciel – Unit commitment based on risk assessment to systems with variable power sources. In IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society. Florence, Italy: IEEE, 2016. ISBN 978-1-5090-3474-1. Pp. 3924-3929pt_PT
dc.identifier.doi10.1109/IECON.2016.7793533pt_PT
dc.identifier.isbn978-1-5090-3474-1
dc.identifier.isbn978-1-5090-3475-8
dc.identifier.urihttp://hdl.handle.net/10400.21/8675
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7793533pt_PT
dc.subjectPower generation schedulingpt_PT
dc.subjectRisk assessmentpt_PT
dc.subjectUncertaintypt_PT
dc.titleUnit commitment based on risk assessment to systems with variable power sourcespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlace23-26 Oct. 2016 - Florence, Italypt_PT
oaire.citation.endPage3929pt_PT
oaire.citation.startPage3924pt_PT
oaire.citation.titleIECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Societypt_PT
person.familyNameFonte
person.givenNamePedro M
person.identifier.ciencia-id4D17-2B29-38BB
person.identifier.orcid0000-0001-5858-203X
person.identifier.scopus-author-id8507639300
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication7da87fed-6d70-4191-b26a-d0fd64965d29
relation.isAuthorOfPublication.latestForDiscovery7da87fed-6d70-4191-b26a-d0fd64965d29

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