Daily load and flexibility profiles (2020) of the electricity transmission system from Portugal – ATTEST project

This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298. The dataset contains information about the full transmission test network of Portugal as in 2020. The grid topology has been anonymized and contains 304 nodes, 557 branches and 7 interconnections with Spain. It is operated at 400 kV, 220 kV and 150 kV. There are 270 generators, and a label classifies each of them according to the generation technology type (e.g., Fossil Gas, Wind Onshore, etc.). A network model (MatPower format) including the grid information and considering realistic assumptions for unknown data was built from scratch taking into account the available public data released by the Portuguese TSO. Furthermore, this model contains a built-in snapshot regarding the 2019 winter peak. Considering the day when this peak load occurred, the auxiliary spreadsheet contains the following hourly data: load data, generator status obtained from unit commitment, regulated voltage magnitude setpoint of each generator, transformer tap ratio, power transformer data, power lines/cables data and aggregated flexibility per consumption node.

Data en bronnen

Extra Informatie

Veld Waarde
Auteur Henrique Teixeira, Nuno Fonseca, Fernando Ribeiro, Leonel Carvalho, André Madureira, Filipe Soares
Laatst gewijzigd april 22, 2022, 14:16 (UTC)
Gecreëerd februari 15, 2022, 10:42 (UTC)
Citation Teixeira, H., Fonseca, N., Ribeiro, F., Carvalho, L., Madureira, A., & Soares, F. (2022). Daily load and flexibility profiles (2020) of the electricity transmission system from Portugal – ATTEST project [Data set]. INESC TEC. https://doi.org/10.25747/GNA2-MW65
DOI https://doi.org/10.25747/gna2-mw65
dc.Coverage.Spatial Network is geographically located in Portugal.
dc.Coverage.Temporal The network characteristics represent the circumstances of 2020. Load, generation and flexibility data are expressed in intervals of 1 hour for a peak load day occurred in 2019.
dc.Created February, 2021
ddi.Software Any text editor to read the network file. Excel to read and operate load, generation and flexibility profiles. Matlab (with MatPower extension) or Pypower (Python) to test the network.