Motivation and Approach

As of today, only limited data of the structure of European Gas Transport Networks is publicly available for research and related purposes. The lack of such data hinders attempts to compare and validate high resolution energy system models.

Motivation and aim

Details of gas transport networks are currently integrated in a number of in-house energy system models which are not publicly available. The assumptions, simplifications and the degree of abstraction involved in the gas transport network models used are, hence, unknown and often undocumented. This fact implies that the learning curve in the construction of network models is rather low, since there is hardly any (scientific) discussion on the underlying approaches, procedures and results. At the same time, the output of energy system models takes an important role in the decision making process concerning future sustainable technologies and energy strategies. Recent examples of such strategies are the ones under debate and discussion for the Energiewende in Germany.

In this framework, the SciGRID_gas project initiated by the research center DLR Institute of Networked Energy Systems in Oldenburg aims to create an open source model of the European Gas Transport network. Releasing SciGRID_gas as open source is an attempt to make reliable data on the gas transport network available. Appropriate (open) licenses attached to gas transport network data ensures that established models and their assumptions can be published, discussed and validated in a well-defined and self-consistent manner. In addition to the gas transport network network data, the methods developed for the construction of the SciGRID_gas model are published under the Apache 2.0 license.

The main purpose of SciGRID_gas is hence to open the door to new gas transport network models and ideas in energy system modeling by providing freely available and well-documented data on the European gas transport network.

Technical approach

On the technical level, the SciGRID_gas model will be written in a modular fashion using Python and SQL commands, and is mainly based on data available in openstreetmap.org under the Open Database License (ODbL).