Computing technical capacities in the European entry-exit gas market is NP-hard

Artikel

As a result of its liberalization, the European gas market is organized as an entry-exit system in order to decouple the trading and transport of natural gas. Roughly summarized, the gas market organization consists of four subsequent stages. First, the transmission system operator (TSO) is obliged to allocate so-called maximal technical capacities for the nodes of the network. Second, the TSO and the gas traders sign mid- to long-term capacity-right contracts, where the capacity is bounded above by the allocated technical capacities. These contracts are called bookings. Third, on a day-ahead basis, gas traders can nominate the amount of gas that they inject or withdraw from the network at entry and exit nodes, where the nominated amount is bounded above by the respective booking. Fourth and finally, the TSO has to operate the network such that the nominated amounts of gas can be transported. By signing the booking contract, the TSO guarantees that all possibly resulting nominations can indeed be transported. Consequently, maximal technical capacities have to satisfy that all nominations that comply with these technical capacities can be transported through the network. This leads to a highly challenging mathematical optimization problem. We consider the specific instantiations of this problem in which we assume capacitated linear as well as potential-based flow models. In this contribution, we formally introduce the problem of Computing Technical Capacities (CTC) and prove that it is NP-complete on trees and NP-hard in general. To this end, we first reduce the Subset Sum problem to CTC for the case of capacitated linear flows in trees. Afterward, we extend this result to CTC with potential-based flows and show that this problem is also NP-complete on trees by reducing it to the case of capacitated linear flow. Since the hardness results are obtained for the easiest case, i.e., on tree-shaped networks with capacitated linear as well as potential-based flows, this implies the hardness of CTC for more general graph classes.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Annals of Operations Research ; ISSN: 1572-9338 ; Volume: 295 ; Year: 2020 ; Issue: 1 ; Pages: 337-362 ; New York, NY: Springer US

Classification and Topics

• Classification: Allgemeines, Wissenschaft ; History of Economic Thought through 1925: General ; Multiple or Simultaneous Equation Models: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions ; Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General ; Design of Experiments: General
• Subject: European entry-exit gas market ; Technical capacities ; Potential-based flows ; Computational complexity ; NP-hardness

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Schewe, Lars ; Schmidt, Martin ; Thürauf, Johannes
• Event: Veröffentlichung
• (who): Springer US
• (where): New York, NY
• (when): 2020

Further information

• DOI: doi:10.1007/s10479-020-03725-2
• Last update: 10.03.2025, 11:44 AM CET