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

Bobby Xiong, Davide Fioriti, Fabian Neumann, Iegor Riepin, Tom Brown
Author Information
  1. Bobby Xiong: Department of Digital Transformation in Energy Systems, Institute of Energy Engineering, Technische Universität Berlin, Berlin, Germany. xiong@tu-berlin.de. ORCID
  2. Davide Fioriti: Department of Energy Systems, Territory and Construction Engineering, Università di Pisa, Pisa, Italy. ORCID
  3. Fabian Neumann: Department of Digital Transformation in Energy Systems, Institute of Energy Engineering, Technische Universität Berlin, Berlin, Germany. ORCID
  4. Iegor Riepin: Department of Digital Transformation in Energy Systems, Institute of Energy Engineering, Technische Universität Berlin, Berlin, Germany.
  5. Tom Brown: Department of Digital Transformation in Energy Systems, Institute of Energy Engineering, Technische Universität Berlin, Berlin, Germany. ORCID

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.

References

  1. PLoS One. 2020 Apr 24;15(4):e0231866 [PMID: 32330167]
  2. Joule. 2020 Sep 16;4(9):1929-1948 [PMID: 32999994]
  3. F1000Res. 2021 Jan 18;10:33 [PMID: 34035898]
  4. Sci Data. 2022 Oct 14;9(1):623 [PMID: 36241673]

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