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Optimization of power plant investments under uncertain renewable energy development paths - A multistage stochastic programming approach

Author

Listed:
  • Fürsch, Michaela

    () (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Nagl, Stephan

    () (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Lindenberger, Dietmar

    () (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

Abstract

Electricity generation from renewable energy sources (RES-E) is supposed to increase signi ficantly within the coming decades. However, uncertainty about the progress of necessary infrastructure investments, public acceptance and cost developments of renewable energies renders the achievement of political plans uncertain. Implementation risks of renewable energy targets are challenging for investment planning, because di fferent RES-E shares fundamentally change the optimal mix of dispatchable power plants. Speci cally, uncertain future RES-E deployment paths induce uncertainty about the steepness of the residual load duration curve and the hourly residual load structure. In this paper, we show how uncertain future RES-E penetrations impact the electricity system and try to quantify eff ects for the Central European power market. We use a multi-stage stochastic investment and dispatch model to analyze e ffects on investment choices, electricity generation and system costs. Our main findings include that the uncertain achievement of RES-E targets signi ficantly effects optimal investment decisions. First, a higher share of technologies with a medium capital/operating cost ratio is cost-efficient. Second, the value of storage units in systems with high RES-E penetrations might decrease. Third, in the case of the Central European power market, costs induced by the implementation risk of renewable energies seem to be rather small compared to total system costs.

Suggested Citation

  • Fürsch, Michaela & Nagl, Stephan & Lindenberger, Dietmar, 2012. "Optimization of power plant investments under uncertain renewable energy development paths - A multistage stochastic programming approach," EWI Working Papers 2012-8, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2012_008
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    References listed on IDEAS

    as
    1. Nagl, Stephan & Fürsch, Michaela & Jägemann, Cosima & Bettzüge, Marc Oliver, 2011. "The economic value of storage in renewable power systems - the case of thermal energy storage in concentrating solar plants," EWI Working Papers 2011-8, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    2. Fabien A. Roques & William J. Nuttall & David M. Newbery & Richard de Neufville & Stephen Connors, 2006. "Nuclear Power: A Hedge against Uncertain Gas and Carbon Prices?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-24.
    3. Gardner, Douglas T., 1996. "Flexibility in electric power planning: Coping with demand uncertainty," Energy, Elsevier, vol. 21(12), pages 1207-1218.
    4. De Jonghe, Cedric & Delarue, Erik & Belmans, Ronnie & D'haeseleer, William, 2011. "Determining optimal electricity technology mix with high level of wind power penetration," Applied Energy, Elsevier, vol. 88(6), pages 2231-2238, June.
    5. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    6. Weigt, Hannes, 2009. "Germany's wind energy: The potential for fossil capacity replacement and cost saving," Applied Energy, Elsevier, vol. 86(10), pages 1857-1863, October.
    7. Lamont, Alan D., 2008. "Assessing the long-term system value of intermittent electric generation technologies," Energy Economics, Elsevier, vol. 30(3), pages 1208-1231, May.
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    Cited by:

    1. Malischek, Raimund & Trüby, Johannes, 2016. "The future of nuclear power in France: an analysis of the costs of phasing-out," Energy, Elsevier, vol. 116(P1), pages 908-921.
    2. 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 (EWI).

    More about this item

    Keywords

    Multi-Stage Stochastic Programming; Renewable Energy; Power Plant Optimization;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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