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Linepack storage valuation under price uncertainty

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  • Arvesen, Ø.
  • Medbø, V.
  • Fleten, S.-E.
  • Tomasgard, A.
  • Westgaard, S.

Abstract

Natural gas flows in pipelines as a consequence of the pressure difference at the inlet and outlet. Adjusting these pressures makes it possible to inject natural gas at one rate and withdraw at a different rate, hence using the pipeline as storage as well as transport. We study the value of using the so called pipeline linepack as a short-term gas storage and how this functionality may offset the discrepancy between the low flexibility in take-or-pay contracts and the high inherent flexibility of a gas-fired power plant. To value the storage option, we consider a cycling power plant facing volatile power prices while purchasing gas on a take-or-pay contract. We estimate a Markov regime-switching model for power prices and a mean reverting jump diffusion model for gas prices. Applying Least Squares Monte Carlo simulation to the operation of the linepack storage, we find that the storage option indeed has significant value for the plant, enabling it to better exploit the sometimes extreme price fluctuations. Finally, we show how power price volatility and jump frequency are the main value drivers, and that the size of the storage increases the value up to a point where no additional flexibility is used.

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  • Arvesen, Ø. & Medbø, V. & Fleten, S.-E. & Tomasgard, A. & Westgaard, S., 2013. "Linepack storage valuation under price uncertainty," Energy, Elsevier, vol. 52(C), pages 155-164.
    • Handle: RePEc:eee:energy:v:52:y:2013:i:c:p:155-164
    DOI: 10.1016/j.energy.2012.12.031
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    6. Tran, Trung Hieu & French, Simon & Ashman, Rhys & Kent, Edward, 2018. "Linepack planning models for gas transmission network under uncertainty," European Journal of Operational Research, Elsevier, vol. 268(2), pages 688-702.
    7. Ida Bakke & Stein-Erik Fleten & Lars Ivar Hagfors & Verena Hagspiel & Beate Norheim & Sonja Wogrin, 2016. "Investment in electric energy storage under uncertainty: a real options approach," Computational Management Science, Springer, vol. 13(3), pages 483-500, July.
    8. Paraschiv, Florentina & Fleten, Stein-Erik & Schürle, Michael, 2015. "A spot-forward model for electricity prices with regime shifts," Energy Economics, Elsevier, vol. 47(C), pages 142-153.
    9. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
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    11. Lars Ivar Hagfors & Hilde Hørthe Kamperud & Florentina Paraschiv & Marcel Prokopczuk & Alma Sator & Sjur Westgaard, 2016. "Prediction of extreme price occurrences in the German day-ahead electricity market," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1929-1948, December.
    12. Hagfors, Lars Ivar & Bunn, Derek & Kristoffersen, Eline & Staver, Tiril Toftdahl & Westgaard, Sjur, 2016. "Modeling the UK electricity price distributions using quantile regression," Energy, Elsevier, vol. 102(C), pages 231-243.
    13. Deng, Qianli & Jiang, Xianglin & Cui, Qingbin & Zhang, Limao, 2015. "Strategic design of cost savings guarantee in energy performance contracting under uncertainty," Applied Energy, Elsevier, vol. 139(C), pages 68-80.
    14. Stefansdottir, Bryndis & Depping, Verena & Grunow, Martin & Kulozik, Ulrich, 2018. "Impact of shelf life on the trade-off between economic and environmental objectives: A dairy case," International Journal of Production Economics, Elsevier, vol. 201(C), pages 136-148.
    15. Secomandi, Nicola & Seppi, Duane J., 2014. "Real Options and Merchant Operations of Energy and Other Commodities," Foundations and Trends(R) in Technology, Information and Operations Management, now publishers, vol. 6(3-4), pages 161-331, July.
    16. Weiliang Wang & Dan Wang & Liu Liu & Hongjie Jia & Yunqiang Zhi & Zhengji Meng & Wei Du, 2019. "Research on Modeling and Hierarchical Scheduling of a Generalized Multi-Source Energy Storage System in an Integrated Energy Distribution System," Energies, MDPI, vol. 12(2), pages 1-28, January.
    17. Nadarajah, Selvaprabu & Margot, François & Secomandi, Nicola, 2017. "Comparison of least squares Monte Carlo methods with applications to energy real options," European Journal of Operational Research, Elsevier, vol. 256(1), pages 196-204.
    18. Shaton, Katerina, 2015. "Value of Flexibility in Gas Pipeline Investments," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Innovations and Strategies for Logistics and Supply Chains: Technologies, Business Models and Risk Management. Proceedings of the Hamburg Internationa, volume 20, pages 333-357, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    19. Cho, Jaeyoung & Lim, Gino J. & Kim, Seon Jin & Biobaku, Taofeek, 2018. "Liquefied natural gas inventory routing problem under uncertain weather conditions," International Journal of Production Economics, Elsevier, vol. 204(C), pages 18-29.

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    More about this item

    Keywords

    Linepack; Gas storage valuation; Regime-switching models; Natural gas prices; Electricity prices; Power plant;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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