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Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
Project OPTIGRID - Methodology for Analysis of Dynamic Line Capacity and Optimized Management of Electric Grids: https://optigrid.lneg.pt/ ; 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. ; N/A
Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
Project OPTIGRID - Methodology for Analysis of Dynamic Line Capacity and Optimized Management of Electric Grids: https://optigrid.lneg.pt/ ; 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. ; N/A
Meteorological forecast data: Coupling NWP and CFD Modeling. Merging the datasets: Deliverable D2.2
Couto, António (author)
2022-01-25
Paper
Electronic Resource
English
DDC:
690
Deliverable D2.2: Coordination algorithm and architecture document
Fraunhofer Publica | 2009
|Deliverable D2.2: Coordination algorithm and architecture document
DataCite | 2009
|Fraunhofer Publica | 2016
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