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Valuing fuel diversification in power generation capacity planning

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  • Sunderkötter, Malte
  • Weber, Christoph

Abstract

Deterministic capacity planning problems in electricity systems can be solved by comparing technology specific long-term and short-term marginal costs. In an uncertain market environment, Mean-Variance Portfolio (MVP) theory provides a consistent framework to balance risk and return in power generation portfolios. Focusing on fuel price risks, MVP theory can be adopted to determine the welfare efficient system generation technology mix.

Suggested Citation

  • Sunderkötter, Malte & Weber, Christoph, 2012. "Valuing fuel diversification in power generation capacity planning," Energy Economics, Elsevier, vol. 34(5), pages 1664-1674.
    • Handle: RePEc:eee:eneeco:v:34:y:2012:i:5:p:1664-1674
    DOI: 10.1016/j.eneco.2012.02.003
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    Cited by:

    1. Benjamin Botor & Benjamin Boecker & Thomas Kalabis & Christoph Weber, "undated". "Estimating the value of flexibility from real options: On the accuracy of hybrid electricity price models," EWL Working Papers 1805, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    2. Benjamin Boecker & Christoph Weber, "undated". "Thesenpapier: A primer about storage in bottom-up models of future energy systems. Fundamentals of storage operation and investment in competitive long-term equilibria," EWL Working Papers 2002, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    3. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.
    4. Andreas A. Renz & Christoph Weber, 2012. "A Hotelling Model for Fixed-Cost Driven Power Generation," EWL Working Papers 1206, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Jan 2013.
    5. Steffen, Bjarne & Weber, Christoph, 2013. "Efficient storage capacity in power systems with thermal and renewable generation," Energy Economics, Elsevier, vol. 36(C), pages 556-567.
    6. Botor, Benjamin & Böcker, Benjamin & Kallabis, Thomas & Weber, Christoph, 2021. "Information shocks and profitability risks for power plant investments – impacts of policy instruments," Energy Economics, Elsevier, vol. 102(C).
    7. Pérez Odeh, Rodrigo & Watts, David & Negrete-Pincetic, Matías, 2018. "Portfolio applications in electricity markets review: Private investor and manager perspective trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 192-204.
    8. Pöstges, Arne & Weber, Christoph, 2019. "Time series aggregation – A new methodological approach using the “peak-load-pricing” model," Utilities Policy, Elsevier, vol. 59(C), pages 1-1.
    9. Zhou, Y. & Li, Y.P. & Huang, G.H., 2015. "Planning sustainable electric-power system with carbon emission abatement through CDM under uncertainty," Applied Energy, Elsevier, vol. 140(C), pages 350-364.
    10. Scala, Antonio & Facchini, Angelo & Perna, Umberto & Basosi, Riccardo, 2019. "Portfolio analysis and geographical allocation of renewable sources: A stochastic approach," Energy Policy, Elsevier, vol. 125(C), pages 154-159.
    11. Christoph Weber & Philip Vogel, 2014. "Contingent certificate allocation rules and incentives for power plant investment and disinvestment," Journal of Regulatory Economics, Springer, vol. 46(3), pages 292-317, December.
    12. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    13. Tietjen, Oliver & Pahle, Michael & Fuss, Sabine, 2016. "Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets," Energy Economics, Elsevier, vol. 58(C), pages 174-185.
    14. Inzunza, Andrés & Moreno, Rodrigo & Bernales, Alejandro & Rudnick, Hugh, 2016. "CVaR constrained planning of renewable generation with consideration of system inertial response, reserve services and demand participation," Energy Economics, Elsevier, vol. 59(C), pages 104-117.
    15. Pérez Odeh, Rodrigo & Watts, David & Flores, Yarela, 2018. "Planning in a changing environment: Applications of portfolio optimisation to deal with risk in the electricity sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3808-3823.

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    More about this item

    Keywords

    Power plant investments; Capacity planning; Mean-Variance Portfolio theory; Fuel mix diversification;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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