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Stochastic Modeling of Natural Gas Infrastructure Development in Europe under Demand Uncertainty

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  • Marte Fodstad, Ruud Egging, Kjetil Midthun, and Asgeir Tomasgard

Abstract

We present an analysis of the optimal development of natural gas infrastructure in Europe based on the scenario studies of Holz and von Hirschhausen (2013). We use a stochastic mixed integer quadratic model to analyze the impact of uncertainty about future natural gas consumption in Europe on optimal investments in pipelines. Our data is based on results from the PRIMES model of natural gas demand and technology scenarios discussed in Knopf et al. (2013). We present a comparison between the results from the stochastic model and the expected value model, as well as an analysis of the individual scenarios. We also performed sensitivity analyses on the probabilities of the future scenarios. Comparison of the results from the stochastic model to those of a deterministic expected value model reveals a negligible Value of the Stochastic Solution. We do, however, find structurally different infrastructure solutions in the stochastic and the deterministic models. Regarding infrastructure expansions, we find that 1) the largest pipeline investments will be towards Asia, 2) there is a trend towards a larger gas supply from Africa to Europe, and 3) within Europe, eastward connections will be strengthened. Our main finding using the stochastic approach is that there is limited option value in delaying investments in natural gas infrastructure, until more information is available regarding policy and technology in 2020, due to the low costs of overcapacity.

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  • Marte Fodstad, Ruud Egging, Kjetil Midthun, and Asgeir Tomasgard, 2016. "Stochastic Modeling of Natural Gas Infrastructure Development in Europe under Demand Uncertainty," The Energy Journal, International Association for Energy Economics, vol. 0(Sustainab).
    • Handle: RePEc:aen:journl:ej37-si3-fodsta
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    Cited by:

    1. Stevie Lochran, 2021. "GNOME: A Dynamic Dispatch and Investment Optimisation Model of the European Natural Gas Network and Its Suppliers," SN Operations Research Forum, Springer, vol. 2(4), pages 1-44, December.
    2. Selei, Adrienn & Takácsné Tóth, Borbála, 2022. "A modelling-based assessment of EU supported natural gas projects of common interest," Energy Policy, Elsevier, vol. 166(C).
    3. Hauser, Philipp, 2021. "Does ‘more’ equal ‘better’? – Analyzing the impact of diversification strategies on infrastructure in the European gas market," Energy Policy, Elsevier, vol. 153(C).
    4. Riepin, Iegor & Möbius, Thomas & Müsgens, Felix, 2021. "Modelling uncertainty in coupled electricity and gas systems—Is it worth the effort?," Applied Energy, Elsevier, vol. 285(C).
    5. Riepin, Iegor & Schmidt, Matthew & Baringo, Luis & Müsgens, Felix, 2022. "Adaptive robust optimization for European strategic gas infrastructure planning," Applied Energy, Elsevier, vol. 324(C).
    6. Olmez Turan, Merve & Flamand, Tulay, 2023. "Optimizing investment and transportation decisions for the European natural gas supply chain," Applied Energy, Elsevier, vol. 337(C).
    7. Riepin, I. & Müsgens, F., 2019. "Seasonal Flexibility in the European Natural Gas Market," Cambridge Working Papers in Economics 1976, Faculty of Economics, University of Cambridge.
    8. Sesini, Marzia & Giarola, Sara & Hawkes, Adam D., 2021. "Strategic natural gas storage coordination among EU member states in response to disruption in the trans Austria gas pipeline: A stochastic approach to solidarity," Energy, Elsevier, vol. 235(C).
    9. Iegor Riepin & Thomas Mobius & Felix Musgens, 2020. "Modelling uncertainty in coupled electricity and gas systems -- is it worth the effort?," Papers 2008.07221, arXiv.org, revised Sep 2020.

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