scigrid_gas — European gas transmission network (SciGRID_gas IGGIELGN, 2021)

Description

Networks of the European natural gas transmission system, compiled by J. Diettrich, A. Pluta and W. Medjroubi (DLR Institute of Networked Energy Systems) in the SciGRID_gas project. The IGGIELGN data set combines several public sources: the InternetDaten (INET) data set, collected from web pages, press releases and other public documents, the data sets of Gas Infrastructure Europe (GIE), Gas Storage Europe (GSE) and the International Gas Union (IGU), the network of the LKD project, the ENTSOG transmission capacity map, and data sets for Great Britain and Norway; missing attributes (e.g. diameters, capacities and pressures of pipes) were estimated by heuristics and statistical methods.

A node is a point of the network (the end of a pipe segment, or a facility), and an edge is a pipeline segment between two nodes, positioned along the pipeline's route. The networks are undirected (the direction of the segments in the data is not kept); some pairs of nodes are joined by several segments (parallel pipelines), and some segments start and end at the same node (self-loops). The facilities (compressor stations, LNG terminals, storages, production sites, consumers and border points) are attached to nodes, and are included as counts at each node; their attributes (capacities, operators, ...) are not included, and neither are the courses of the pipes (as polylines) and the uncertainties and estimation methods of the attributes.

There is one network for each of the three versions of the data set (v1.0.0, v1.1.1 and v1.1.2, published from March to May 2021). The network of version 1.0.0 is connected and has 4 self-loops; those of versions 1.1.1 and 1.1.2 have 24 components and 106 and 128 self-loops, respectively. In version 1.1.1, the country codes of all pipe segments are FI (apparently an error, corrected in version 1.1.2).

The networks have the following properties:

(Node) name: the node's id.
(Node) label: its name in the data (if any).
(Node) latitude and longitude: the geographical position.
(Node) country: the two-letter country code (XX for nodes offshore or outside Europe).
(Node) nuts_id: the NUTS 3 region (versions 1.1.1 and 1.1.2).
(Node) num_compressors, num_lngs, num_storages, num_productions, num_consumers and num_border_points: the numbers of facilities of each kind at the node.
(Edge) name: the segment's id (its prefix indicates the source of the data).
(Edge) source_id: the id of the original pipeline in the source data.
(Edge) countries: the country codes of the two ends, separated by a semicolon.
(Edge) diameter (mm): length (km), max_capacity (millions of cubic meters per day) and max_pressure (bar), the pipe's diameter, length, maximum capacity and maximum pressure.
(Edge) is_h_gas: whether it transports high-calorific gas.
(Edge) bidirectional: whether the gas can flow in both directions.
(Edge) start_year and end_year: the years of commissioning and decommissioning (if known).
(Edge) water_depth: the water depth of offshore pipes (m, version 1.0.0). Missing values are NaN.

Tags

Technological Spatial Weighted Multigraph Metadata

Added

2026-10-27

Citation

J. Diettrich, A. Pluta, W. Medjroubi, "SciGRID_gas IGGIELGN." Zenodo, versions 1.0.0, 1.1.1 and 1.1.2 (2021) 10.5281/zenodo.4642568 Sci-Hub
A. Pluta, W. Medjroubi, J. C. Diettrich, J. Dasenbrock, H.-P. Tetens, J. E. Sandoval, O. Lunsdorf, "SciGRID_gas - Data Model of the European Gas Transport Network." 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES), 1-7 (2022) 10.1109/OSMSES54027.2022.9769122 Sci-Hub

Upstream URL OK

https://zenodo.org/records/4767098

Upstream license

Creative Commons Attribution 4.0 International (CC BY 4.0), https://creativecommons.org/licenses/by/4.0/

Networks

Tip: click on a column header to sort the list, or hover over it for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
v1.0.0	4,804	6,263	2.61	1.66	3.71	9481.84	0.21	0.06	131	1.00	Undirected	Unipartite	name label latitude longitude country num_compressors num_lngs num_storages num_productions num_consumers num_border_points	name source_id countries diameter length max_capacity max_pressure is_h_gas bidirectional start_year end_year water_depth	218 KiB	301 KiB	292 KiB	275 KiB
v1.1.1	4,787	6,462	2.70	1.76	4.32	10136.59	0.35	0.05	133	0.99	Undirected	Unipartite	name label latitude longitude country nuts_id num_compressors num_lngs num_storages num_productions num_consumers num_border_points	name source_id countries diameter length max_capacity max_pressure is_h_gas bidirectional start_year end_year	244 KiB	321 KiB	309 KiB	295 KiB
v1.1.2	4,675	6,323	2.71	1.77	4.32	9876.40	0.35	0.06	132	0.99	Undirected	Unipartite	name label latitude longitude country nuts_id num_compressors num_lngs num_storages num_productions num_consumers num_border_points	name source_id countries diameter length max_capacity max_pressure is_h_gas bidirectional start_year end_year	244 KiB	318 KiB	306 KiB	294 KiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.