Daily profiles (2050) of load of an urban electricity distribution network 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 a real Portuguese Distribution test network, totally anonymized, located in an urban area as in 2050. A network file (including grid topology, nodes, generators, consumption, all of which connected by power lines or transformers) and auxiliary files are provided. The network file (MatPower format) includes a “snapshot” or “steady-state” at a given time with a converged power flow solution. The grid, which is operated at 10 kV and 60 kV, has 207 nodes (99 with consumption) and 206 branches. The auxiliary load data comprises 12  typical days representing the combination of each season and the type of day (business day, Saturday, Sunday) gathering the active and reactive consumption at each node of the network in intervals of 15 minutes. In addition, a “read me” file  called “Manual” includes technical detailed information about how to read the data properly.

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Additional Info

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Author Nuno Fonseca, Henrique Teixeira, Fernando Ribeiro, André Madureira, Filipe Soares
Last Updated February 28, 2022, 17:53 (Europe/Lisbon)
Created February 14, 2022, 15:13 (Europe/Lisbon)
Citation Fonseca, N., Teixeira, H., Ribeiro, F., Madureira, A., & Soares, F. (2022). Daily profiles (2050) of load of an urban electricity distribution network from Portugal – ATTEST project [Data set]. INESC TEC. https://doi.org/10.25747/BBKS-DB26
DOI https://doi.org/10.25747/bbks-db26
dc.Coverage.Spatial Network is geographically located in an urban area.
dc.Coverage.Temporal The network characteristics represent the circumstances of 2050. Load profiles are expressed in intervals of 15 minutes for 12 typical days of the year: Business day, Saturday and Sunday for each season of the year.
dc.Created February, 2021
ddi.Software Any text editor to read the network file. Excel to read and operate load profiles. Matlab (with MatPower extension) or Pypower (Python) to test the network.