IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v37y2016i3_supplp5-32.html
   My bibliography  Save this article

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

Author

Listed:
  • Marte Fodstad
  • Ruud Egging
  • Kjetil Midthun
  • 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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Marte Fodstad & Ruud Egging & Kjetil Midthun & Asgeir Tomasgard, 2016. "Stochastic Modeling of Natural Gas Infrastructure Development in Europe under Demand Uncertainty," The Energy Journal, , vol. 37(3_suppl), pages 5-32, December.
  • Handle: RePEc:sae:enejou:v:37:y:2016:i:3_suppl:p:5-32
    DOI: 10.5547/01956574.37.SI3.mfod
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.37.SI3.mfod
    Download Restriction: no

    File URL: https://libkey.io/10.5547/01956574.37.SI3.mfod?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. S. Siddiqui & S. Gabriel, 2013. "An SOS1-Based Approach for Solving MPECs with a Natural Gas Market Application," Networks and Spatial Economics, Springer, vol. 13(2), pages 205-227, June.
    2. Qipeng P. Zheng & Panos M. Pardalos, 2010. "Stochastic and Risk Management Models and Solution Algorithm for Natural Gas Transmission Network Expansion and LNG Terminal Location Planning," Journal of Optimization Theory and Applications, Springer, vol. 147(2), pages 337-357, November.
    3. Huppmann, Daniel & Egging, Ruud, 2014. "Market power, fuel substitution and infrastructure – A large-scale equilibrium model of global energy markets," Energy, Elsevier, vol. 75(C), pages 483-500.
    4. Christian Gollier, 2004. "The Economics of Risk and Time," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262572249, December.
    5. Siu, Barbara W.Y. & Lo, Hong K., 2008. "Doubly uncertain transportation network: Degradable capacity and stochastic demand," European Journal of Operational Research, Elsevier, vol. 191(1), pages 166-181, November.
    6. Harald Hecking & Timo Panke, 2012. "COLUMBUS - A global gas market model," EWI Working Papers 2012-6, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. 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.
    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. Olmez Turan, Merve & Flamand, Tulay, 2023. "Optimizing investment and transportation decisions for the European natural gas supply chain," Applied Energy, Elsevier, vol. 337(C).
    5. 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.
    6. Riepin, Iegor & Schmidt, Matthew & Baringo, Luis & Müsgens, Felix, 2022. "Adaptive robust optimization for European strategic gas infrastructure planning," Applied Energy, Elsevier, vol. 324(C).
    7. 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).
    8. 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).
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olufolajimi Oke & Daniel Huppmann & Max Marshall & Ricky Poulton & Sauleh Siddiqui, 2019. "Multimodal Transportation Flows in Energy Networks with an Application to Crude Oil Markets," Networks and Spatial Economics, Springer, vol. 19(2), pages 521-555, June.
    2. Anne Neumann & Juan Rosellón & Hannes Weigt, 2015. "Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market—A Proposed Merchant-Regulatory Mechanism," Networks and Spatial Economics, Springer, vol. 15(1), pages 149-181, March.
    3. Feijoo, Felipe & Huppmann, Daniel & Sakiyama, Larissa & Siddiqui, Sauleh, 2016. "North American natural gas model: Impact of cross-border trade with Mexico," Energy, Elsevier, vol. 112(C), pages 1084-1095.
    4. Lorenczik, Stefan & Panke, Timo, 2016. "Assessing market structures in resource markets — An empirical analysis of the market for metallurgical coal using various equilibrium models," Energy Economics, Elsevier, vol. 59(C), pages 179-187.
    5. Vitor Miguel Ribeiro & Gustavo Soutinho & Isabel Soares, 2023. "Natural Gas Prices in the Framework of European Union’s Energy Transition: Assessing Evolution and Drivers," Energies, MDPI, vol. 16(4), pages 1-46, February.
    6. Siddiqui, Sauleh & Christensen, Adam, 2016. "Determining energy and climate market policy using multiobjective programs with equilibrium constraints," Energy, Elsevier, vol. 94(C), pages 316-325.
    7. Harald Hecking, 2015. "CO2 abatement policies in the power sector under an oligopolistic gas market," EWI Working Papers 2014-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    8. Matthias Schmidt & Hermann Held & Elmar Kriegler & Alexander Lorenz, 2013. "Climate Policy Under Uncertain and Heterogeneous Climate Damages," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(1), pages 79-99, January.
    9. Xiaosheng Mu & Luciano Pomatto & Philipp Strack & Omer Tamuz, 2021. "From Blackwell Dominance in Large Samples to Rényi Divergences and Back Again," Econometrica, Econometric Society, vol. 89(1), pages 475-506, January.
    10. Montserrat Guillén & Jean Pinquet, 2008. "Long-Term Care: Risk Description of a Spanish Portfolio and Economic Analysis of the Timing of Insurance Purchase," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 33(4), pages 659-672, October.
    11. Hermann Held, 2019. "Cost Risk Analysis: Dynamically Consistent Decision-Making under Climate Targets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 247-261, January.
    12. Quentin Stoeffler & Michael Carter & Catherine Guirkinger & Wouter Gelade, 2022. "The Spillover Impact of Index Insurance on Agricultural Investment by Cotton Farmers in Burkina Faso," The World Bank Economic Review, World Bank, vol. 36(1), pages 114-140.
    13. Jaber Valinejad & Mousa Marzband & Michael Elsdon & Ameena Saad Al-Sumaiti & Taghi Barforoushi, 2019. "Dynamic Carbon-Constrained EPEC Model for Strategic Generation Investment Incentives with the Aim of Reducing CO 2 Emissions," Energies, MDPI, vol. 12(24), pages 1-35, December.
    14. Koeniger, Winfried, 2001. "Labor and Financial Market Interactions: The Case of Labor Income Risk and Car Insurance in the UK 1969-95," IZA Discussion Papers 240, Institute of Labor Economics (IZA).
    15. Irina Georgescu, 2018. "The Effect of Prudence on the Optimal Allocation in Possibilistic and Mixed Models," Mathematics, MDPI, vol. 6(8), pages 1-19, August.
    16. Christian Gollier, 2007. "Whom should we believe? Aggregation of heterogeneous beliefs," Journal of Risk and Uncertainty, Springer, vol. 35(2), pages 107-127, October.
    17. LiCalzi, Marco & Sorato, Annamaria, 2006. "The Pearson system of utility functions," European Journal of Operational Research, Elsevier, vol. 172(2), pages 560-573, July.
    18. Marc A. Ragin & Benjamin L. Collier & Johannes G. Jaspersen, 2021. "The effect of information disclosure on demand for high‐load insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(1), pages 161-193, March.
    19. Martin Barbie & Marcus Hagedorn & Ashok Kaul, 2006. "Fostering Within-Family Human-Capital Investment: An Intragenerational Insurance Perspective of Social Security," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 62(4), pages 503-529, December.
    20. Mel Devine & James Gleeson & John Kinsella & David Ramsey, 2014. "A Rolling Optimisation Model of the UK Natural Gas Market," Networks and Spatial Economics, Springer, vol. 14(2), pages 209-244, June.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • F0 - International Economics - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:enejou:v:37:y:2016:i:3_suppl:p:5-32. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.