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Mean-Variance optimization of power generation portfolios under uncertainty in the merit order

Author

Listed:
  • Malte Sunderkötter
  • Christoph Weber

    (Chair for Management Sciences and Energy Economics, University of Duisburg-Essen)

Abstract

In this article we discuss welfare-optimal capacity allocation of different electricity generation technologies available for serving system demand. While the classical peak load pricing theory derives the efficient portfolio structure from a deterministic marginal production cost curve ("merit order"), we investigate in particular the implications of possible reversals in the merit order —sometimes also referred to as fuel switch risks- induced by uncertain operating costs. We propose a static, non-convex optimization model combining the classic peak load pricing model with elements of mean-variance portfolio (MVP) theory and analytically discuss possible solution cases and important optimality properties. We examine the approach in a case study on the efficient structure of generation portfolios consisting of CCGT and hard coal technologies in Germany. With special emphasis, we study the emergence of overcapacities (exceeding maximal demand) in efficient portfolios and show that diversification is not beneficial per-se. The results show that the efficient technology mix may be significantly impacted by a risk for reversals in the merit order. Therefore, our findings support the importance of considering this risk factor especially with long-term investment horizons. The model is applicable to various investment problems related to production of nonstorable goods under price uncertainty of input factors. Similar problems can e.g. be found in transportation systems or in the process industry.

Suggested Citation

  • Malte Sunderkötter & Christoph Weber, 2011. "Mean-Variance optimization of power generation portfolios under uncertainty in the merit order," EWL Working Papers 1105, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2011.
    • Handle: RePEc:dui:wpaper:1105
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    References listed on IDEAS

    as
    1. Christoph Weber, 2005. "Uncertainty in the Electric Power Industry," International Series in Operations Research and Management Science, Springer, number 978-0-387-23048-1, December.
    2. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    3. Fleten, S.-E. & Maribu, K.M. & Wangensteen, I., 2007. "Optimal investment strategies in decentralized renewable power generation under uncertainty," Energy, Elsevier, vol. 32(5), pages 803-815.
    4. Mohammadi, Hassan, 2009. "Electricity prices and fuel costs: Long-run relations and short-run dynamics," Energy Economics, Elsevier, vol. 31(3), pages 503-509, May.
    5. Gotham, Douglas & Muthuraman, Kumar & Preckel, Paul & Rardin, Ronald & Ruangpattana, Suriya, 2009. "A load factor based mean-variance analysis for fuel diversification," Energy Economics, Elsevier, vol. 31(2), pages 249-256, March.
    6. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    7. Crew, Michael A & Fernando, Chitru S & Kleindorfer, Paul R, 1995. "The Theory of Peak-Load Pricing: A Survey," Journal of Regulatory Economics, Springer, vol. 8(3), pages 215-248, November.
    8. Malte Sunderkoetter & Christoph Weber, 2009. "Valuing fuel diversification in optimal investment policies for electricity generation portfolios," EWL Working Papers 0904, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Nov 2009.
    9. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
    10. Robert S. Pindyck, 2001. "The Dynamics of Commodity Spot and Futures Markets: A Primer," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-30.
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    Cited by:

    1. Böckers, Veit & Giessing, Leonie & Rösch, Jürgen, 2013. "The green game changer: An empirical assessment of the effects of wind and solar power on the merit order," DICE Discussion Papers 104, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    2. Sunderkötter, Malte & Weber, Christoph, 2012. "Valuing fuel diversification in power generation capacity planning," Energy Economics, Elsevier, vol. 34(5), pages 1664-1674.

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    Keywords

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    JEL classification:

    • 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
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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