Optimization and Engineering

, Volume 19, Issue 2, pp 297–326 | Cite as

A decomposition approach for optimal gas network extension with a finite set of demand scenarios

  • Jonas SchweigerEmail author
  • Frauke Liers


Today’s gas markets demand more flexibility from the network operators which in turn have to invest in their network infrastructure. As these investments are very cost-intensive and long-lasting, network extensions should not only focus on a single bottleneck scenario, but should increase the flexibility to fulfill different demand scenarios. In this work, we formulate a model for the network extension problem for multiple demand scenarios and propose a scenario decomposition in order to solve the resulting challenging optimization tasks. In fact, each subproblem consists of a mixed-integer nonlinear optimization problem. Valid bounds on the objective value are derived even without solving the subproblems to optimality. Furthermore, we develop heuristics that prove capable of improving the initial solutions substantially. The results of computational experiments on realistic network topologies are presented. It turns out that our method is able to solve these challenging instances to optimality within a reasonable amount of time.


Decomposition Robust Gas network extension MINLP 



thank The authors thank the anonymous referees for their valuable and constructive feedback. The authors are grateful to Open Grid Europe GmbH (OGE, Essen/Germany) for supporting this work and furthermore thank the DFG for their support within projects B06 and Z01 in CRC TRR 154. This research was performed as part of the Energie Campus Nürnberg and supported by funding through the ‘Aufbruch Bayern (Bavaria on the move)’ initiative of the state of Bavaria. The authors thank all collaborators in the ForNe project and all developers of Lamatto++.


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Authors and Affiliations

  1. 1.Department Mathematical OptimizationZuse Institute BerlinBerlinGermany
  2. 2.Department of MathematicsUniversity Erlangen-NürnbergErlangenGermany

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