A system to evaluate gas network capacities: Concepts and implementation

Abstract In 2005 the European Union liberalized the gas market with a disruptive change and decoupled trading of natural gas from its transport. The gas is now transported by independent so-called transmissions system operators or TSOs. The market model established by the European Union views the gas transmission network as a black box, providing shippers (gas traders and consumers) the opportunity to transport gas from any entry to any exit. TSOs are required to offer the maximum possible capacities at each entry and exit such that any resulting gas flow can be realized by the network. The revenue from selling these capacities is more than one billion Euro in Germany alone, but overestimating the capacity might compromise the security of supply. Therefore, evaluating the available transport capacities is extremely important to the TSOs. This is a report on a large project in mathematical optimization, set out to develop a new toolset for evaluating gas network capacities. The goals and the challenges as they occurred in the project are described, as well as the developments and design decisions taken to meet the requirements.

[1]  Björn Geißler,et al.  Penalty Alternating Direction Methods for Mixed-Integer Optimization: A New View on Feasibility Pumps , 2017, SIAM J. Optim..

[2]  Patrice Marcotte,et al.  An overview of bilevel optimization , 2007, Ann. Oper. Res..

[3]  Alexander Martin,et al.  Combination of Nonlinear and Linear Optimization of Transient Gas Networks , 2011, INFORMS J. Comput..

[4]  Martin Schmidt,et al.  High detail stationary optimization models for gas networks , 2015 .

[5]  Armin Fügenschuh,et al.  Validation of nominations in gas network optimization: models, methods, and solutions , 2015, Optim. Methods Softw..

[6]  Armin Fügenschuh,et al.  The Specialized MINLP Approach , 2015 .

[7]  Thorsten Koch,et al.  Regulatory rules for gas markets in Germany and other European countries , 2015 .

[8]  Robert Schwarz,et al.  Using Bilevel Optimization to find Severe Transport Situations in Gas Transmission Networks , 2016 .

[9]  Thorsten Koch,et al.  Gas network topology optimization for upcoming market requirements , 2011, 2011 8th International Conference on the European Energy Market (EEM).

[10]  Andy B. Yoo,et al.  Approved for Public Release; Further Dissemination Unlimited X-ray Pulse Compression Using Strained Crystals X-ray Pulse Compression Using Strained Crystals , 2002 .

[11]  Martin Schmidt,et al.  A generic interior-point framework for nonsmooth and complementarity constrained nonlinear optimization , 2013 .

[12]  Jonas Schweiger Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty , 2017 .

[13]  Ambros M. Gleixner,et al.  SCIP: global optimization of mixed-integer nonlinear programs in a branch-and-cut framework , 2018, Optim. Methods Softw..

[14]  Martin Schmidt,et al.  High detail stationary optimization models for gas networks: validation and results , 2016 .

[15]  Björn Geißler,et al.  Solving power-constrained gas transportation problems using an MIP-based alternating direction method , 2015, Comput. Chem. Eng..

[16]  Tom van der Hoeven,et al.  Math in gas and the art of linearization , 2004 .

[17]  Thorsten Koch,et al.  Mathematical optimization for evaluating gas network capacities , 2015 .

[18]  Björn Geißler,et al.  A New Algorithm for MINLP Applied to Gas Transport Energy Cost Minimization , 2013 .

[19]  Marc C. Steinbach,et al.  Computational optimization of gas compressor stations: MINLP models versus continuous reformulations , 2016, Mathematical Methods of Operations Research.

[20]  Björn Geißler,et al.  Solving Highly Detailed Gas Transport MINLPs: Block Separability and Penalty Alternating Direction Methods , 2018, INFORMS J. Comput..

[21]  René Henrion,et al.  On the quantification of nomination feasibility in stationary gas networks with random load , 2016, Math. Methods Oper. Res..

[22]  Jonas Schweiger,et al.  A decomposition approach for optimal gas network extension with a finite set of demand scenarios , 2018 .

[23]  Jarig J. Steringa,et al.  A Systematic Approach to Transmission Stress Tests in Entry-Exit Systems , 2015 .

[24]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[25]  Marc E. Pfetsch,et al.  A characterization of irreducible infeasible subsystems in flow networks , 2016, Networks.

[26]  Björn Geißler,et al.  Using Piecewise Linear Functions for Solving MINLP s , 2012 .

[27]  Martin Schmidt,et al.  A Primal Heuristic for Nonsmooth Mixed Integer Nonlinear Optimization , 2013 .

[28]  Bernhard M. Willert,et al.  Validation of nominations in gas networks and properties of technical capacities , 2014 .

[29]  Alexander Martin,et al.  Mixed integer linear models for the optimization of dynamical transport networks , 2011, Math. Methods Oper. Res..

[30]  Tobias Achterberg,et al.  SCIP: solving constraint integer programs , 2009, Math. Program. Comput..

[31]  Christodoulos A. Floudas,et al.  ADVANCES FOR THE POOLING PROBLEM: MODELING, GLOBAL OPTIMIZATION, AND COMPUTATIONAL STUDIES , 2009 .

[32]  Thorsten Koch,et al.  Evaluating Gas Network Capacities , 2015, MOS-SIAM Series on Optimization.

[33]  René Saitenmacher,et al.  Polyhedral 3D Models for Compressors in Gas Networks , 2017, OR.

[34]  Jesco Humpola Gas Network Optimization by Minlp , 2017 .

[35]  Martin Schmidt An interior-point method for nonlinear optimization problems with locatable and separable nonsmoothness , 2015, EURO J. Comput. Optim..