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The coordination of centralised and distributed generation

Author

Listed:
  • René Aïd

    (LEDa - Laboratoire d'Economie de Dauphine - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres)

  • Matteo Basei

    (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique)

  • Huyên Pham

    (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - X - École polytechnique - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - CNRS - Centre National de la Recherche Scientifique, LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper analyses the interaction between centralised carbon emissive technologies and distributed intermittent non-emissive technologies. In our model, there is a representative consumer who can satisfy her electricity demand by investing in distributed generation (solar panels) and by buying power from a centralised firm at a price the firm sets. Distributed generation is intermittent and induces an externality cost to the consumer. The firm provides non-random electricity generation subject to a carbon tax and to transmission costs. The objective of the consumer is to satisfy her demand while minimising investment costs, payments to the firm and intermittency costs. The objective of the firm is to satisfy the consumer's residual demand while minimising investment costs, demand deviation costs, and maximising the payments from the consumer. We formulate the investment decisions as McKean-Vlasov control problems with stochastic coefficients. We provide explicit, price model-free solutions to the optimal decision problems faced by each player, the solution of the Pareto optimum, and the Stackelberg equilibrium where the firm is the leader. We find that, from the social planner's point of view, the carbon tax or transmission costs are necessary to justify a positive share of distributed capacity in the long-term, whatever the respective investment costs of both technologies are. The Stackelberg equilibrium is far from the Pareto equilibrium and leads to an over-investment in distributed energy and to a much higher price for centralised energy.

Suggested Citation

  • René Aïd & Matteo Basei & Huyên Pham, 2017. "The coordination of centralised and distributed generation," Working Papers hal-01517165, HAL.
  • Handle: RePEc:hal:wpaper:hal-01517165
    Note: View the original document on HAL open archive server: https://hal.science/hal-01517165
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    References listed on IDEAS

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    Cited by:

    1. Rama Cont & Xin Guo & Renyuan Xu, 2020. "Pareto Optima for a Class of Singular Control Games," Working Papers hal-03049246, HAL.
    2. Rama Cont & Xin Guo & Renyuan Xu, 2021. "Interbank lending with benchmark rates: Pareto optima for a class of singular control games," Mathematical Finance, Wiley Blackwell, vol. 31(4), pages 1357-1393, October.
    3. Arvind Shrivats & Sebastian Jaimungal, 2019. "Optimal Behaviour in Solar Renewable Energy Certificate (SREC) Markets," Papers 1904.06337, arXiv.org, revised Apr 2020.

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    Keywords

    stochastic game; decarbonation; distributed generation; McKean-Vlasov;
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