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. 2025 Feb 16;12(1):277.
doi: 10.1038/s41597-025-04550-7.

Modelling the high-voltage grid using open data for Europe and beyond

Bobby Xiong  1 , Davide Fioriti  2 , Fabian Neumann  3 , Iegor Riepin  3 , Tom Brown  3
Affiliations

Modelling the high-voltage grid using open data for Europe and beyond

Bobby Xiong et al. Sci Data. .

Abstract

This paper provides the background, methodology and validation for constructing a representation of the European high-voltage grid (AC lines from 220 to 750 kV and all DC lines) based on OpenStreetMap data. Grid components include commissioned substations, transmission lines and cables, transformers, and converters as well as technical parameters based on standard types. The data is provided as easy-to-access comma-separated values files which makes it suitable for model-independent, large-scale electricity and energy system modelling. For further ease-of-use, an interactive map is included to enable visual inspection. To assess the data quality, this paper compares the dataset with official statistics and representative model runs using PyPSA-Eur based on different electricity grid representations. The dataset and workflow are provided as part of PyPSA-Eur, an open-source, sector-coupled optimisation model of the European energy system. By integrating with the codebase for initiatives such as PyPSA-Earth, the benefits of this work of this work extend to the global context. The dataset is published under the Open Data Commons Open Database (ODbL 1.0) licence.

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Conflict of interest statement

Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Process diagram depicting the creation of the European high-voltage grid from OSM data, implemented through individual Snakemake rules.
Fig. 2
Fig. 2
Illustration of the steps to create a PyPSA-ready network from OSM data. Note that Step 4 does not make changes to the topology and is hence omitted from this illustration.
Fig. 3
Fig. 3
Example — Simplification of a DC link relation: Moyle interconnector (Scotland - Northern Ireland), OSM relation ID 6914309. Different colors show the four segments, i.e., ways that compose the OSM relation.
Fig. 4
Fig. 4
Illustration of building a topologically connected grid.
Fig. 5
Fig. 5
Example of bus clustering. The darkred shape represents the union of the buffer around virtual buses and an original OSM substation polygon (yellow). The bright red dot represents the internal point of the union, this point sets the geographic coordinates of the obtained bus. Lines and cables are connected to the respective voltage level within the substation, transformers are added to connect buses of different voltage levels.
Fig. 6
Fig. 6
Map of the OSM-based European high-voltage grid. This map was generated using the grid dataset provided with this publication.
Fig. 7
Fig. 7
Comparison of total route and circuit lengths per country.
Fig. 8
Fig. 8
Comparison of line volume per NUTS1 region — Colors represent individual countries. Line volume is the product of the nominal capacity and the length, summed over all lines within the region.
Fig. 9
Fig. 9
Comparison of the weighted degree distribution in both transmission grid representations before and after clustering (NUTS2). Ukraine at geoBoundaries administration level 1, Moldova at full bus resolution. A comparison at NUTS3 resolution is provided in Fig. 12.
Fig. 10
Fig. 10
Regional dispatch, line utilisation and curtailment. A map comparing nominal ratings of the two clustered grids is provided in the Fig. 13.
Fig. 11
Fig. 11
Regional dispatch, line utilisation and curtailment (delta). Blue indicates an increase in curtailment or line utilisation from the ENTSO-E map to the OSM-based transmission grid, while red indicates a decrease. For full transparency, note that this map shows an outer join of all transmission grid elements, including lines and links that are not present in the other network.
Fig. 12
Fig. 12
Comparison of the weighted degree distribution in both networks before and after clustering (NUTS3). Ukraine at geoBoundaries administration level 1, Moldova at full bus resolution.
Fig. 13
Fig. 13
Clustered AC line capacities, DC link nominal ratings, and optimal generation capacities.
Fig. 14
Fig. 14
Main results — CO2 price: 100 €/t. Comparison of nodal prices, capital expenditures (CAPEX) and operational expenditures (OPEX).
Fig. 15
Fig. 15
Sensitivity run — CO2 price: 200 €/t. Comparison of nodal prices, capital expenditures (CAPEX) and operational expenditures (OPEX).
Fig. 16
Fig. 16
Sensitivity run — CO2 price: 300 €/t. Comparison of nodal prices, capital expenditures (CAPEX) and operational expenditures (OPEX).
Fig. 17
Fig. 17
Comparison of OSM and ENTSO-E map-based transmission grid with reference 50Hertz static grid model. Dashed grey lines underneath show the 50Hertz static grid model for comparative purposes. Note that the geospatial data is provided in simplified, point-to-point form, only. Many of the dashed grey lines are also included in the OSM or ENTSO-E map-based grid representations, however, intermediary buses may exist along the line. As such, in their simplification they are not simplified to the level of the 50Hertz static grid model.
Fig. 18
Fig. 18
Comparison of AC line/cable resistance and reactance between the OSM-based transmission grid and reference 50Hertz static grid model. nosm and nsgm refer to the number of parallel circuits for a distinct line in each network, while Δinom=|inom,osm−inom,sgm|inom,sgm refers to the relative change in underlying nominal current.
Fig. 19
Fig. 19
Screenshot of the interactive map visualising the OSM-based transmission grid. The map is included in the dataset released on Zenodo (map.html).
See this image and copyright information in PMC

References

    1. Hörsch, J. & Brown, T. The role of spatial scale in joint optimisations of generation and transmission for European highly renewable scenarios. In 2017 14th International Conference on the European Energy Market (EEM), 1–7, 10.1109/EEM.2017.7982024 (2017).
    1. ENTSO-E. ENTSO-E Transmission System Map. https://www.entsoe.eu/data/map/.
    1. 50Hertz. Static grid model. https://www.50hertz.com/Transparency/GridData/Gridfigures/Staticgridmodel/ (2022).
    1. JAO. Static Grid Model. https://www.jao.eu/static-grid-model (2023).
    1. Egerer, J. et al. Electricity sector data for policy-relevant modeling: Data documentation and applications to the German and European electricity markets. Research Report 72, DIW Data Documentation (2014).

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