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Capacity Evaluation for Large-Scale Gas Networks

Submission Status:under review
  • Natural gas is important for the energy turnaround in many countries like in Germany, where it serves as a "bridging energy" towards a fossil-free energy supply in the future. About 20% of the total German energy demand is provided by natural gas, which is transported through a complex pipeline network with a total length of about 30000 km and the efficient use of the given transport infrastructure for natural gas is of political, economic, and societal importance. As a consequence of the liberalization of the European gas market in the last decades, gas trading and transport have been decoupled. This has led to new challenges for gas transport companies, and mathematical optimization is perfectly suited for tackling many of these challenges. However, the underlying mathematical problems are by far too hard to be solved by today's general-purpose software so that novel mathematical theory and algorithms are needed. The industrial research project "ForNe: Research Cooperation Network Optimization" has been initiated and funded by Open Grid Europe in 2009 and brought together experts in mathematical optimization from seven German universities and research institutes, which cover almost the entire range of mathematical optimization: integer and nonlinear optimization as well as optimization under uncertainty. The mathematical research results have been put together in a software package that has been delivered to Open Grid Europe at the end of the project. Moreover, the research is still continuing - e.g., in the Collaborative Research Center/Transregio 154 "Mathematical Modelling, Simulation and Optimization using the Example of Gas Networks" funded by the German Research Foundation.

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Author:Martin Schmidt, Benjamin Hiller, Thorsten Koch, Marc Pfetsch, Björn Geißler, René Henrion, Imke Joormann, Alexander Martin, Antonio Morsi, Werner Römisch, Lars Schewe, Rüdiger Schultz, Marc C. Steinbach
Document Type:Preprint
Language:English
Date of Publication (online):2019/11/08
Date of first Publication:2019/11/08
Release Date:2019/11/08
Page Number:8
Institutes:Friedrich-Alexander-Universität Erlangen-Nürnberg
Technische Universität Darmstadt
Humboldt-Universität zu Berlin
Zuse-Institut Berlin (ZIB)
Weierstraß-Institut für Angewandte Analysis und Stochastik
Universität Duisburg-Essen
Universität Trier
University of Edinburgh
Subprojects:A01
A05
A07
B04
B05
B07
B08
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International