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CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis

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  • Lucheroni, Carlo
  • Mari, Carlo

Abstract

Market based pricing of CO2 was designed to control CO2 emissions by means of the price level, since high CO2 price levels discourage emissions. In this paper, it will be shown that the level of uncertainty on CO2 market prices, i.e. the volatility of CO2 prices itself, has a strong influence not only on generation portfolio risk management but also on CO2 emissions abatement. A reduction of emissions can be obtained when rational power generation capacity investors decide that the capacity expansion cost risk induced jointly by CO2 volatility and fossil fuels prices volatility can be efficiently hedged adding to otherwise fossil fuel portfolios some nuclear power as a carbon free asset. This intriguing effect will be discussed using a recently introduced economic analysis tool, called stochastic LCOE theory. The stochastic LCOE theory used here was designed to investigate diversification effects on energy portfolios. In previous papers this theory was used to study diversification effects on portfolios composed of carbon risky fossil technologies and a carbon risk-free nuclear technology in a risk-reward trade-off frame. In this paper the stochastic LCOE theory will be extended to include uncertainty about nuclear power plant construction times, i.e. considering nuclear risky as well, this being the main uncertainty source of financial risk in nuclear technology. Two measures of risk will be used, standard deviation and CVaR deviation, to derive efficient frontiers for generation portfolios. Frontier portfolios will be analyzed in their implications on emissions control.

Suggested Citation

  • Lucheroni, Carlo & Mari, Carlo, 2017. "CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis," Applied Energy, Elsevier, vol. 190(C), pages 278-290.
  • Handle: RePEc:eee:appene:v:190:y:2017:i:c:p:278-290
    DOI: 10.1016/j.apenergy.2016.12.125
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    References listed on IDEAS

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    Cited by:

    1. Aquila, Giancarlo & Coelho, Eden de Oliveira Pinto & Bonatto, Benedito Donizeti & Pamplona, Edson de Oliveira & Nakamura, Wilson Toshiro, 2021. "Perspective of uncertainty and risk from the CVaR-LCOE approach: An analysis of the case of PV microgeneration in Minas Gerais, Brazil," Energy, Elsevier, vol. 226(C).
    2. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2019. "Assessing Renewable Energy Sources for Electricity (RES-E) Potential Using a CAPM-Analogous Multi-Stage Model," Energies, MDPI, vol. 12(19), pages 1-20, September.
    3. Huthaifa Sameeh Alqaralleh & Ahmad Al-Saraireh & Alessandra Canepa, 2021. "Energy Market Risk Management under Uncertainty: A VaR Based on Wavelet Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 130-137.
    4. Paulino Martinez-Fernandez & Fernando deLlano-Paz & Anxo Calvo-Silvosa & Isabel Soares, 2018. "Pollutant versus non-pollutant generation technologies: a CML-analogous analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 199-212, December.
    5. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    6. Tran, Thomas T.D. & Smith, Amanda D., 2018. "Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies," Applied Energy, Elsevier, vol. 216(C), pages 157-171.
    7. Carlo Mari, 2020. "Stochastic NPV Based vs Stochastic LCOE Based Power Portfolio Selection Under Uncertainty," Energies, MDPI, vol. 13(14), pages 1-18, July.
    8. Tazi, Nacef & Safaei, Fatemeh & Hnaien, Faicel, 2022. "Assessment of the levelized cost of energy using a stochastic model," Energy, Elsevier, vol. 238(PB).
    9. Shen, Wei & Chen, Xi & Qiu, Jing & Hayward, Jennifier A & Sayeef, Saad & Osman, Peter & Meng, Ke & Dong, Zhao Yang, 2020. "A comprehensive review of variable renewable energy levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    10. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    11. Carlo Mari, 2018. "CO 2 Price Volatility Effects on Optimal Power System Portfolios," Energies, MDPI, vol. 11(7), pages 1-18, July.
    12. Aquila, Giancarlo & Nakamura, Wilson Toshiro & Junior, Paulo Rotella & Souza Rocha, Luiz Celio & de Oliveira Pamplona, Edson, 2021. "Perspectives under uncertainties and risk in wind farms investments based on Omega-LCOE approach: An analysis in São Paulo state, Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    13. Maria del Carmen Gomez-Rios & Dora Carmen Galvez-Cruz, 2021. "Simulation of Levelized Costs of Electricity Considering Externalities," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 16(4), pages 1-23, Octubre -.
    14. Carlo Lucheroni & Carlo Mari, 2021. "Internal hedging of intermittent renewable power generation and optimal portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 873-893, April.
    15. Gong, Xu & Shi, Rong & Xu, Jun & Lin, Boqiang, 2021. "Analyzing spillover effects between carbon and fossil energy markets from a time-varying perspective," Applied Energy, Elsevier, vol. 285(C).
    16. Carlo Lucheroni & Carlo Mari, 2018. "Optimal Integration of Intermittent Renewables: A System LCOE Stochastic Approach," Energies, MDPI, vol. 11(3), pages 1-21, March.

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    More about this item

    Keywords

    Levelized cost of electricity; Nuclear power; Risk and deviation measures;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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