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The costs of electricity systems with a high share of fluctuating renewables - a stochastic investment and dispatch optimization model for Europe

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Author Info

  • Nagl, Stephan

    ()
    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Fürsch, Michaela

    ()
    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Lindenberger, Dietmar

    ()
    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

Abstract

Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for di fferent shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.

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Bibliographic Info

Paper provided by Energiewirtschaftliches Institut an der Universitaet zu Koeln in its series EWI Working Papers with number 2012-1.

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Length: 35 pages
Date of creation: 09 Jan 2012
Date of revision:
Handle: RePEc:ris:ewikln:2012_001

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Keywords: Stochastic programming; electricity; renewable energy;

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References

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  1. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
  2. Neuhoff, K. & Ehrenmann, A. & Butler, L. & Cust, J. & Hoexter, H. & Keats, K. & Kreczko,A. & Sinden, G., 2006. "Space and Time: Wind in an Investment Planning Model," Cambridge Working Papers in Economics 0620, Faculty of Economics, University of Cambridge.
  3. Beenstock, Michael, 1995. "The stochastic economics of windpower," Energy Economics, Elsevier, vol. 17(1), pages 27-37, January.
  4. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
  5. DeCarolis, Joseph F. & Keith, David W., 2006. "The economics of large-scale wind power in a carbon constrained world," Energy Policy, Elsevier, vol. 34(4), pages 395-410, March.
  6. Richter, Jan, 2011. "DIMENSION - A Dispatch and Investment Model for European Electricity Markets," EWI Working Papers 2011-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
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Citations

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Cited by:
  1. Andreas Schröder & Maximilian Bracke, 2012. "Integrated Electricity Generation Expansion and Transmission Capacity Planning: An Application to the Central European Region," Discussion Papers of DIW Berlin 1250, DIW Berlin, German Institute for Economic Research.
  2. Unteutsch, Michaela, 2014. "Who Benefits from Cooperation? - A Numerical Analysis of Redistribution Effects Resulting from Cooperation in European RES-E Support," EWI Working Papers 2014-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  3. Lion Hirth, 2013. "The Optimal Share of Variable Renewables. How the Variability of Wind and Solar Power Affects their Welfare-optimal Deployment," Working Papers 2013.90, Fondazione Eni Enrico Mattei.
  4. Nagl, Stephan, 2013. "Prices vs. Quantities: Incentives for Renewable Power Generation - Numerical Analysis for the European Power Market," EWI Working Papers 2013-4, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  5. Nagl, Stephan, 2013. "The Effect of Weather Uncertainty on the Financial Risk of Green Electricity Producers under Various Renewable Policies," EWI Working Papers 2013-15, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  6. Jägemann, Cosima, 2012. "Decarbonizing Europe’s power sector by 2050 - Analyzing the implications of alternative decarbonization pathways," EWI Working Papers 2012-13, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  7. Fürsch, Michaela & Malischek, Raimund & Lindenberger, Dietmar, 2012. "Der Merit-Order-Effekt der erneuerbaren Energien - Analyse der kurzen und langen Frist," EWI Working Papers 2012-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
  8. Lion Hirth & Falko Ueckerdt & Ottmar Edenhofer, 2014. "Why Wind Is Not Coal: On the Economics of Electricity," Working Papers 2014.39, Fondazione Eni Enrico Mattei.
  9. repec:dui:wpaper:1305 is not listed on IDEAS

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