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

Detalhes bibliográficos
Autor(a) principal: Couto, António
Data de Publicação: 2021
Tipo de documento: Relatório
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.9/3726
Resumo: ABSTRACT: 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.
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spelling Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2Renewable energy sourcesElectrical networksIntegrationElectricity marketsMIBELABSTRACT: 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.Repositório do LNEGCouto, António2022-01-25T18:22:05Z2021-092021-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/reportapplication/pdfhttp://hdl.handle.net/10400.9/3726enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-10T11:32:16Zoai:null:10400.9/3726Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:14:21.528381Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
title Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
spellingShingle Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
Couto, António
Renewable energy sources
Electrical networks
Integration
Electricity markets
MIBEL
title_short Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
title_full Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
title_fullStr Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
title_full_unstemmed Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
title_sort Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
author Couto, António
author_facet Couto, António
author_role author
dc.contributor.none.fl_str_mv Repositório do LNEG
dc.contributor.author.fl_str_mv Couto, António
dc.subject.por.fl_str_mv Renewable energy sources
Electrical networks
Integration
Electricity markets
MIBEL
topic Renewable energy sources
Electrical networks
Integration
Electricity markets
MIBEL
description ABSTRACT: 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.
publishDate 2021
dc.date.none.fl_str_mv 2021-09
2021-09-01T00:00:00Z
2022-01-25T18:22:05Z
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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