Optimizing gas entry–exit capacity utilization under uncertainty

Natural gas is vital to Europe's energy system, with Norway supplying 30% of European gas demand. Effective management of entry-exit capacity in the Norwegian network can enhance market efficiency and energy security, but is far from trivial due to uncertain demand and prices. This study develops a stochastic programming model to determine optimal capacity allocation under uncertainty, with a focus on scalability. Concerned about network stability, operators tend to be risk averse in deviating from their initial decisions when allocating bookable capacities. We use our model in a case study on Norway's gas pipeline network and find that moderating risk aversion can yield considerable system welfare gains. Additionally, we give insights into the system bottlenecks for policymakers and industry stakeholders and show the value of flexibility in this context. Finally, we provide a comprehensive dataset to advance future research.

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Publication Details

Journal
Computational Management Science
Published
2026-01-19
DOI
https://doi.org/10.1007/s10287-025-00552-3
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
21.93
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article

Optimizing gas entry–exit capacity utilization under uncertainty

Berend Markhorst, Ruurd Buijs, Ruud Egging-Bratseth, Rob van der Mei
1 citations
Computational Management Science
Integrated Energy Systems Optimization
21.93
article

Optimizing gas entry–exit capacity utilization under uncertainty

Berend Markhorst, Ruurd Buijs, Ruud Egging-Bratseth, Rob van der Mei
article en
1 citations

Abstract

Natural gas is vital to Europe's energy system, with Norway supplying 30% of European gas demand. Effective management of entry-exit capacity in the Norwegian network can enhance market efficiency and energy security, but is far from trivial due to uncertain demand and prices. This study develops a stochastic programming model to determine optimal capacity allocation under uncertainty, with a focus on scalability. Concerned about network stability, operators tend to be risk averse in deviating from their initial decisions when allocating bookable capacities. We use our model in a case study on Norway's gas pipeline network and find that moderating risk aversion can yield considerable system welfare gains. Additionally, we give insights into the system bottlenecks for policymakers and industry stakeholders and show the value of flexibility in this context. Finally, we provide a comprehensive dataset to advance future research.

Computational Management ScienceVol. 23(1)
Centrum Wiskunde & Informatica (NL), SINTEF (NO), SINTEF Industry (NO), Vrije Universiteit Amsterdam (NL)
Affordable and clean energy
Openalex Percentile: Top 2%
Integrated Energy Systems Optimization
21.93
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Optimizing gas entry–exit capacity utilization under uncertainty — Berend Markhorst, Ruurd Buijs, et al. · Computational Management Science (2026) | TGRS Research Map | TGRS