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Energy transition under scenario uncertainty: a mean-field game of stopping with common noise

Author

Listed:
  • Roxana Dumitrescu

    (King’s College London)

  • Marcos Leutscher

    (Institut Polytechnique de Paris)

  • Peter Tankov

    (Institut Polytechnique de Paris)

Abstract

We study the impact of transition scenario uncertainty, namely that of future carbon price and electricity demand, on the pace of decarbonization of the electricity industry. To this end, we develop a theory of optimal stopping mean-field games with non-Markovian common noise and partial observation. For mathematical tractability, the theory is formulated in discrete time and with common noise restricted to a finite probability space. We prove the existence of Nash equilibria for this game using the linear programming approach. We then apply the general theory to build a discrete time model for the long-term dynamics of the electricity market subject to common random shocks affecting the carbon price and the electricity demand. We consider two classes of agents: conventional producers and renewable producers. The former choose an optimal moment to exit the market and the latter choose an optimal moment to enter the market by investing into renewable generation. The agents interact through the market price determined by a merit order mechanism with an exogenous stochastic demand. We illustrate our model by an example inspired by the UK electricity market, and show that scenario uncertainty leads to significant changes in the speed of replacement of conventional generators by renewable production.

Suggested Citation

  • Roxana Dumitrescu & Marcos Leutscher & Peter Tankov, 2024. "Energy transition under scenario uncertainty: a mean-field game of stopping with common noise," Mathematics and Financial Economics, Springer, volume 18, number 4, December.
    • Handle: RePEc:spr:mathfi:v:18:y:2024:i:2:d:10.1007_s11579-023-00352-w
    DOI: 10.1007/s11579-023-00352-w
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    1. Olivier Sassi & Renaud Crassous & Jean-Charles Hourcade & Vincent Gitz & Henri Waisman & Celine Guivarch, 2010. "IMACLIM-R: a modelling framework to simulate sustainable development pathways," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 10(1/2), pages 5-24.
    2. Ottmar Edenhofer & Kai Lessmann & Claudia Kemfert & Michael Grubb & Jonathan Köhler, 2006. "Induced Technological Change: Exploring its Implications for the Economics of Atmospheric Stabilization: Synthesis Report from the innovation Modeling Comparison Project," The Energy Journal, , vol. 27(1_suppl), pages 57-108, January.
    3. René Aïd & Roxana Dumitrescu & Peter Tankov, 2021. "The entry and exit game in the electricity markets: A mean-field game approach," Post-Print hal-03215763, HAL.
    4. Richard Loulou & Maryse Labriet, 2008. "ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure," Computational Management Science, Springer, vol. 5(1), pages 7-40, February.
    5. Martin L. Weitzman, 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," The Review of Economics and Statistics, MIT Press, vol. 91(1), pages 1-19, February.
    6. DeCarolis, Joseph & Daly, Hannah & Dodds, Paul & Keppo, Ilkka & Li, Francis & McDowall, Will & Pye, Steve & Strachan, Neil & Trutnevyte, Evelina & Usher, Will & Winning, Matthew & Yeh, Sonia & Zeyring, 2017. "Formalizing best practice for energy system optimization modelling," Applied Energy, Elsevier, vol. 194(C), pages 184-198.
    7. Monasterolo, Irene & Roventini, Andrea & Foxon, Tim J., 2019. "Uncertainty of climate policies and implications for economics and finance: An evolutionary economics approach," Ecological Economics, Elsevier, vol. 163(C), pages 177-182.
    8. Clémence Alasseur & Imen Ben Taher & Anis Matoussi, 2020. "An Extended Mean Field Game for Storage in Smart Grids," Journal of Optimization Theory and Applications, Springer, vol. 184(2), pages 644-670, February.
    9. William Nordhaus, 2018. "Projections and Uncertainties about Climate Change in an Era of Minimal Climate Policies," American Economic Journal: Economic Policy, American Economic Association, vol. 10(3), pages 333-360, August.
    10. Rene Carmona & Francois Delarue & Daniel Lacker, 2016. "Mean field games of timing and models for bank runs," Papers 1606.03709, arXiv.org, revised Jan 2017.
    11. Fabio Bagagiolo & Dario Bauso, 2014. "Mean-Field Games and Dynamic Demand Management in Power Grids," Dynamic Games and Applications, Springer, vol. 4(2), pages 155-176, June.
    12. René Carmona & Gökçe Dayanıklı & Mathieu Laurière, 2022. "Mean Field Models to Regulate Carbon Emissions in Electricity Production," Dynamic Games and Applications, Springer, vol. 12(3), pages 897-928, September.
    13. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.
    14. Nico Bauer & Lavinia Baumstark & Marian Leimbach, 2012. "The REMIND-R model: the role of renewables in the low-carbon transformation—first-best vs. second-best worlds," Climatic Change, Springer, vol. 114(1), pages 145-168, September.
    15. Romuald Élie & Emma Hubert & Thibaut Mastrolia & Dylan Possamaï, 2021. "Mean–field moral hazard for optimal energy demand response management," Mathematical Finance, Wiley Blackwell, vol. 31(1), pages 399-473, January.
    16. Peter M. Cox & Chris Huntingford & Mark S. Williamson, 2018. "Emergent constraint on equilibrium climate sensitivity from global temperature variability," Nature, Nature, vol. 553(7688), pages 319-322, January.
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    Cited by:

    1. Jingguo Zhang & Lianhai Ren, 2024. "A mean field game model of green economy," Digital Finance, Springer, vol. 6(4), pages 657-692, December.

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    More about this item

    Keywords

    Electricity market; Energy transition; Scenario uncertainty; Mean-field games; Common noise; Optimal stopping; Partial information;
    All these keywords.

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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