TRR 154: Mathematical Modelling, Simulation and Optimisation Using the Example of Gas Networks

Third Party Funds Group - Overall project

Project Details

Project leader:
Prof. Dr. Alexander Martin

Contributing FAU Organisations:
Economics - Discrete Optimization - Mathematics (EDOM)
Sonderforschungsbereich/Transregio 154: Mathematische Modellierung, Simulation und Optimierung am Beispiel von Gasnetzwerken

Funding source: DFG / Sonderforschungsbereich / Transregio (SFB / TRR)
Acronym: TRR 154
Start date: 01/07/2014

Research Fields

Economics - Discrete Optimization - Mathematics (EDOM)

Abstract (technical / expert description):

The "turnaround in energy policy" is currently in the main focus of public opinion. It concerns social, political and scientific aspects as the dependence on a reliable, efficient and affordable energy supply becomes increasingly dominant. On the other side, the desire for a clean, environmentally consistent and climate-friendly energy production is stronger than ever. To balance these tendencies while making a transition to nuclear-free energy supply, gas becomes more and more important in the decades to come. Natural gas is and will be sufficiently available, is storable and can be traded.

On the other side, focussing on an efficient handling of gas transportation induces a number of technical and regulatory problems, also in the context of coupling to other energy carriers. As an example, energy transporters are required by law to provide evidence that within the given capacities all contracts defining the market are physically and technically feasible. Given the amount of data and the potential of stochastic effects, this is a formidable task all by itself, regardless from the actual process of distributing the proper amount of gas with the required quality to the customer.

It is the goal of the Transregional Collaborative Research Centre to provide certified novel answers to these grand challenges, based on mathematical modelling, simulation and optimisation. In order to achieve this goal new paradigms in the integration of these disciplines and in particular in the interplay between integer and nonlinear programming in the context of stochastic data have to be established and brought to bear. Clearly, without a specified underlying structure of the problems to face, such a breakthrough is rather unlikely.

Thus, the particular network structure, the given hierarchical hybrid modelling in terms of switching algebraic, ordinary and partial differential-algebraic equations of hyperbolic type that is present in gas network transportation systems gives rise to the confidence that the challenges can be met by the team of the Transregional Collaborative Research Centre. Moreover, the fundamental research conducted here will also be applicable in the context of other energy networks such as fresh- and waste-water networks.

In this respect, the research goes beyond the exemplary problem chosen and will provide, besides a cutting edge in enabling technologies, new mathematics in the emerging area of discrete, respectively, integer and continuous problems.

The following Sub projects are located at FAU:

Sub projects:

Mixed integer-continuous dynamical Systems with partial differential equations (A03)
Decomposition methods for mixed-integer optimal control (A05) (2014 - 2018)
Robustification of Physics Parameters in Gas Networks (B06) (2014 - 2018)
Adaptive MIP-Relaxations for MINLPs (B07) (2014 - 2018)
Admissible Robust nodal control (C03)
Central Tasks (Z03) (2014 - 2022)
Integrated graduate school research training group (MGK)
Multilevel mixed-integer nonlinear optimization for gas markets (B08) (2018 - 2022)
Decomposition methods for mixed-integer optimal control (A05) (2018 - 2022)
Robustification of Physics Parameters in Gas Networks (B06) (2018 - 2022)
Adaptive MIP-Relaxations for MINLPs (B07) (2018 - 2022)

External Partners

Humboldt-Universität zu Berlin
Technische Universität Berlin
Technische Universität Darmstadt
Konrad-Zuse-Zentrum für Informationstechnik / Zuse Institute Berlin (ZIB)
Weierstraß-Institut für Angewandte Analysis und Stochastik (WIAS) - Leibniz-Institut im Forschungsverbund Berlin e. V.
Universität Duisburg-Essen (UDE)

Last updated on 2018-24-07 at 15:51