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Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2

dc.contributor.authorCouto, António
dc.date.accessioned2022-01-25T18:22:05Z
dc.date.available2022-01-25T18:22:05Z
dc.date.issued2021-09
dc.descriptionProject OPTIGRID - Methodology for Analysis of Dynamic Line Capacity and Optimized Management of Electric Grids: https://optigrid.lneg.pt/
dc.description.abstractABSTRACT: The work presented in this deliverable was developed by LNEG and R&D NESTER as part of the R&D activities of the project OPTIGRID - Methodology for the dynamic line rating analysis and optimal management of power networks. According to the plan activities of Tasks 2.1 and 2.4, the main objective of this deliverable is to present the methods applied to obtain the meteorological forecast data need to feed the models developed in this project and it merges all the datasets to be used in each case study. According to the work plan, and as reported in the deliverables from Task 4, three case studies were defined for: A) a region with large distributed wind capacity; B) a region with large photovoltaic (PV) potential and limited grid capacity; and C) market splitting occurrence in MIBEL due to congestion in the interconnections. For these regions the meteorological forecast data, used during this project, were obtained using a numerical weather prediction model and computational fluid dynamic model coupling approach. The numerical weather prediction (NWP) model is used to forecast the hourly spatial meteorological data (e.g., wind speed and direction, temperature) during 2018 with a maximum spatial resolution of 3 km. This model is calibrated regarding its physical parametrizations and initial/boundary conditions, among others.pt_PT
dc.description.versionN/Apt_PT
dc.identifier.citationCouto, António - Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2. Project report of OPTIGRID - Methodology for Analysis of Dynamic Line Capacity and Optimized Management of Electric Grids, Deliverable nº D2.2, LNEG, 2021, 42pp.pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.9/3726
dc.language.isoengpt_PT
dc.relationMETHODOLOGY FOR THE DYNAMIC LINE RATING ANALYSIS AND OPTIMAL MANAGEMENT OF POWER NETWORKS
dc.relation.publisherversionhttps://optigrid.lneg.pt/pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectRenewable energy sourcespt_PT
dc.subjectElectrical networkspt_PT
dc.subjectIntegrationpt_PT
dc.subjectElectricity marketspt_PT
dc.subjectMIBELpt_PT
dc.titleMeteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2pt_PT
dc.typereport
dspace.entity.typePublication
oaire.awardTitleMETHODOLOGY FOR THE DYNAMIC LINE RATING ANALYSIS AND OPTIMAL MANAGEMENT OF POWER NETWORKS
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEEI-EEE%2F31711%2F2017/PT
oaire.citation.titleMeteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2pt_PT
oaire.fundingStream3599-PPCDT
person.familyNameCouto
person.givenNameAntónio
person.identifier.ciencia-id2619-80A1-A8AC
person.identifier.orcid0000-0002-7368-8817
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typereportpt_PT
relation.isAuthorOfPublicationa0c5b011-98c5-49d3-9ac6-ddfb6027f500
relation.isAuthorOfPublication.latestForDiscoverya0c5b011-98c5-49d3-9ac6-ddfb6027f500
relation.isProjectOfPublication6a3c4750-e4dc-49dd-87f0-3e5dea9c51e2
relation.isProjectOfPublication.latestForDiscovery6a3c4750-e4dc-49dd-87f0-3e5dea9c51e2

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