Abstract
A large part of the European natural gas imports originates from unstable regions exposed to the risk of supply failure due to economical and political reasons. This has increased the concerns on the security of supply in the European natural gas market. In this paper, we analyze the security of external supply of the Italian gas market that mainly relies on natural gas imports to cover its internal demand. To this aim, we develop an optimization problem that describes the equilibrium state of a gas supply chain where producers, mid-streamers, and final consumers exchange natural gas and liquefied natural gas. Both long-term contracts (LTCs) and spot pricing systems are considered. Mid-streamers are assumed to be exposed to the external supply risk, which is estimated with indicators that we develop starting from those already existing in the literature. In addition, we investigate different degrees of mid-streamers’ flexibility by comparing a situation where mid-streamers fully satisfy the LTC volume clause (“No FLEX” assumption) to a case where the fulfillment of this volume clause is not compulsory (“FLEX” assumption). Our analysis shows that, in the “No FLEX” case, mid-streamers do not significantly change their supplying choices even when the external supply risk is considered. Under this assumption, they face significant profit losses that, instead, disappear in the “FLEX” case when mid-streamers are more flexible and can modify their supply mix. However, the “FLEX” strategy limits the gas availability in the supply chain leading to a curtailment of the social welfare.
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Notes
Note that all the other indicators presented above are computed per each destination country even though not explicitly indicated.
This assumption is taken from Egging et al. [8].
This annual report is in Italian and refer to 2015 data. An English version is available at http://www.autorita.energia.it/allegati/relaz_ann/15/annual_report2015.pdf but refers to 2014 data.
See Table 14 at page 2410 of Egging et al. [8].
Gross domestic product (GDP) measures the final market value of all goods and services produced within a country. It is the most frequently used indicator of economic activity. The GDP by expenditure approach measures total final expenditures (at purchasers’ prices), including exports less imports. This concept is adjusted for inflation. For our simulation, we GDP data from Bloomberg (ticker: EUGDEMU). See https://www.bloomberg.com/quote/EUGNEMUY:IND.
Note that, in the “No FLEX” case, the weighted average gas and LNG prices computed over the involved supplying countries and paid by the mid-streamer are: 0.50 €/cm (gas LTCs), 0.66 €/cm (LNG LTCs), 0.32 €/cm (gas spot), and 0.50 €/cm (LNG spot). In contrast, the weighted average price that the mid-streamer applies to final consumers is 0.48 €/cm).
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Acknowledgements
The E. Allevi and G. Oggioni are grateful to the UniBS H&W Project “Brescia 20-20-20” for the financial support. The research of G. Oggioni have also been supported by “Gruppo Nazionale per il Calcolo Scientifico (GNCS-INdAM)”.
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Appendices
Appendix A: Complementarity formulation of the welfare optimization problem under the “no flexibility” assumption
In this appendix, we report the complementarity formulation of the welfare optimization problem presented in Sect. 3.4.1.
Appendix B: Complementarity formulation of the welfare optimization problem under the “flexibility” assumption
To model the “flexibility” assumption we only replace constraints (31) and (32) in the welfare optimization problem described in Sect. 3.4.1 with the constraints (39) and (40) presented in Sect. 3.4.2. This modification leads to some changes in the KKT conditions presented in “Appendix A”. In particular, conditions (50), (52), (66), and (67) are respectively substituted with the following ones:
More precisely, since constraints (39) and (40) impose upper bounds on the primal variables \(y^G_{nmt}\) and \( y^{{ LNG}}_{nmt}\), the associated dual variables \(\psi _{mn}^{G}\) and \(\psi _{mn}^{{ LNG}}\) enter with a positive sign in the KKT conditions (78) and (79) of these primal variables. The reverse happens in the complementarity formulation of the optimization problem under the “no flexibility” assumption. Since constraints (31) and (32) define lower bounds on variables \(y^G_{nmt}\) and \( y^{{ LNG}}_{nmt}\) the associated dual variables \(\psi _{mn}^{G}\) and \(\psi _{mn}^{{ LNG}}\) enter with a negative sign in the KKT conditions (50) and (52) of these primal variables. Finally, all the other KKT conditions are as indicated in “Appendix A”.
Appendix C: Additional results
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Allevi, E., Boffino, L., De Giuli, M.E. et al. Evaluating the impacts of the external supply risk in a natural gas supply chain: the case of the Italian market. J Glob Optim 70, 347–384 (2018). https://doi.org/10.1007/s10898-017-0584-z
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DOI: https://doi.org/10.1007/s10898-017-0584-z