Archive · dataset · 2022
Daily load and flexibility profiles (2030) according to the Slow Progression scenario of the electricity transmission system from Portugal – ATTEST project
Listed in INESC TEC Research Data Repository
This dataset was prepared under the framework of the ATTEST project, financed by the European Commission with grant number 864298.
Description
The dataset contains information about the full transmission test network of Portugal as in 2030, considering a Slow Progression scenario which represents a lower demand increase and less renewables in the generation. The grid topology has been anonymized and contains 312 nodes, 592 branches and 8 interconnections with Spain.
It is operated at 400 kV, 220 kV and 150 kV. There are 299 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 as in 2020 and then updated to 2030 conditions.
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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 and aggregated flexibility per consumption node.
Links
Get the data
- Portuguese Transmission System 2030 Slow rdm.inesctec.pt/dataset/79101f4d-fabd-40a0-af16-326460afca37/resource/a129e1ae… ↗
download · from rdm inesctec pt
Where it is published
- INESC TEC Research Data Repository dataset page rdm.inesctec.pt/dataset/pe-2022-023 ↗
landing page · from rdm inesctec pt
Catalogue records · 1
- CKAN API rdm.inesctec.pt/api/3/action/package_show?id=79101f4d-fabd-40a0-af16-326460afc… ↗
metadata API · from rdm inesctec pt
Topics
- From keywords
- Computer Science & AI · Energy · Engineering
- Inferred from text
- Electrical engineering 70%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| INESC TEC Research Data Repository | 79101f4d-fabd-40a0-af16-326460afca37 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| concepts[field].anzsrc:group:4008 | enrichment · rdm inesctec pt | taxonomy-embedding@1.1.0 | title+keywords+description (70%) |
| concepts[field].local:field:computer-science-ai | mapping · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| concepts[field].local:field:energy | mapping · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| concepts[field].local:field:engineering | mapping · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| created_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| description | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | /notes |
| license_text | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| publication_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | |
| title | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 | /title |
| updated_date | source · rdm inesctec pt | connector:rdm_inesctec_pt@1.0.0 |