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Optimal Transition to Renewable Energy with Threshold of Irreversible Pollution

Author

Listed:
  • Noël Bonneuil

    (Institut national d’études démographiques, and École des hautes études en sciences sociales)

  • Raouf Boucekkine

    (Aix-Marseille University (Aix-Marseille School of Economics), CNRS & EHESS)

Abstract
When cheap fossil energy is polluting and pollutant no longer absorbed beyond a certain concentration, there is a moment when the introduction of a cleaner renewable energy, although onerous, is optimal with respect to inter-temporal utility. The cleaner technology is adopted either instantaneously or gradually at a controlled rate. The problem of optimum under viability constraints is 6-dimensional under a continuous-discrete dynamic controlled by energy consumption and investment into production of renewable energy. Viable optima are obtained either with gradual or with instantaneous adoption. A longer time horizon increases the probability of adoption of renewable energy and the time for starting this adoption. It also increases maximal utility and the probability to cross the threshold of irreversible pollution. Exploiting a renewable energy starts sooner when adoption is gradual rather than instantaneous. The shorter the period remaining after adoption until the time horizon, the higher the investment into renewable energy.

Suggested Citation

  • Noël Bonneuil & Raouf Boucekkine, 2014. "Optimal Transition to Renewable Energy with Threshold of Irreversible Pollution," AMSE Working Papers 1434, Aix-Marseille School of Economics, France, revised Aug 2014.
  • Handle: RePEc:aim:wpaimx:1434
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Noël Bonneuil & Raouf Boucekkine, 2016. "Viable Nash Equilibria in the Problem of Common Pollution," Working Papers halshs-01341983, HAL.
    2. Kollenbach, Gilbert, 2017. "On the optimal accumulation of renewable energy generation capacity," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 157-179.
    3. Germain, Marc, 2020. "Limits to growth and structural change," Structural Change and Economic Dynamics, Elsevier, vol. 55(C), pages 204-221.
    4. Marc Germain, 2020. "Limits to growth and structural change," Post-Print hal-03129992, HAL.
    5. Ekaterina Gromova & Anastasiia Zaremba & Shimai Su, 2021. "Time-Consistency of an Imputation in a Cooperative Hybrid Differential Game," Mathematics, MDPI, vol. 9(15), pages 1-14, August.
    6. Barbosa, Luciana & Nunes, Cláudia & Rodrigues, Artur & Sardinha, Alberto, 2020. "Feed-in tariff contract schemes and regulatory uncertainty," European Journal of Operational Research, Elsevier, vol. 287(1), pages 331-347.
    7. Jean-François Fagnart & Marc Germain & Benjamin Peeters, 2020. "Can the Energy Transition Be Smooth? A General Equilibrium Approach to the EROEI," Sustainability, MDPI, vol. 12(3), pages 1-29, February.
    8. Anastasiia Zaremba & Ekaterina Gromova & Anna Tur, 2020. "A Differential Game with Random Time Horizon and Discontinuous Distribution," Mathematics, MDPI, vol. 8(12), pages 1-21, December.
    9. Arega Getaneh Abate & Rosana Riccardi & Carlos Ruiz, 2021. "Dynamic tariff-based demand response in retail electricity market under uncertainty," Papers 2105.03405, arXiv.org, revised Nov 2024.
    10. Haichao Wang & Giulia Di Pietro & Xiaozhou Wu & Risto Lahdelma & Vittorio Verda & Ilkka Haavisto, 2018. "Renewable and Sustainable Energy Transitions for Countries with Different Climates and Renewable Energy Sources Potentials," Energies, MDPI, vol. 11(12), pages 1-32, December.
    11. Gärttner, Johannes & Flath, Christoph M. & Weinhardt, Christof, 2018. "Portfolio and contract design for demand response resources," European Journal of Operational Research, Elsevier, vol. 266(1), pages 340-353.
    12. Dmitry Gromov & Ekaterina Gromova, 2017. "On a Class of Hybrid Differential Games," Dynamic Games and Applications, Springer, vol. 7(2), pages 266-288, June.
    13. Wu, Fei & Xiao, Xuanqi & Zhou, Xinyu & Zhang, Dayong & Ji, Qiang, 2022. "Complex risk contagions among large international energy firms: A multi-layer network analysis," Energy Economics, Elsevier, vol. 114(C).

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    More about this item

    Keywords

    multi-stage optimal control; threshold e?ects; irreversibility; non-renewable resources; viability;
    All these keywords.

    JEL classification:

    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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