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Spatial Dependencies of Wind Power and Interrelations with Spot Price Dynamics

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  • Elberg, Christina

    ()
    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Hagspiel, Simeon

    ()
    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

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    Abstract

    Wind power has seen a strong growth over the last decade. Due to its high intermittency, spot prices have become more volatile and exhibit correlated behavior with wind power fed into the system. In this paper, we develop a stochastic simulation model that incorporates the spatial dependencies of wind power and its interrelations with spot prices: We employ a structural supply and demand based model for the electricity spot price that takes into account stochastic production quantities of wind power. Spatial dependencies are modeled with the help of copulas, thus linking the single turbine wind power to the aggregated wind power in a market. The model is applied to the German electricity market where wind power already today makes up a significant share of total power production. Revenue distributions and the market value of diff erent wind power plants are analyzed. We fi nd that the speci fic location of the considered wind turbine, i.e. its spatial dependency with respect to the aggregated wind power in the system, is of high relevance for its market value. Many of the analyzed locations show an upper tail dependence that adversely impacts the market value. This e ffect becomes more important for increasing levels of wind power penetration.

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    Bibliographic Info

    Paper provided by Energiewirtschaftliches Institut an der Universitaet zu Koeln in its series EWI Working Papers with number 2013-11.

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    Length: 23 pages
    Date of creation: 24 Jun 2013
    Date of revision:
    Handle: RePEc:ris:ewikln:2013_011

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    Related research

    Keywords: Market Value; Wind Power; Market Integration; Copula; Structural Supply and Demand Model; Spot Price Model; Monte Carlo Simulation;

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    References

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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
    3. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial Dependence in Wind and Optimal Wind Power Allocation: A Copula Based Analysis," EWI Working Papers 2011-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln.
    4. Woo, C.K. & Horowitz, I. & Moore, J. & Pacheco, A., 2011. "The impact of wind generation on the electricity spot-market price level and variance: The Texas experience," Energy Policy, Elsevier, vol. 39(7), pages 3939-3944, July.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    6. Gelabert, Liliana & Labandeira, Xavier & Linares, Pedro, 2011. "An ex-post analysis of the effect of renewables and cogeneration on Spanish electricity prices," Energy Economics, Elsevier, vol. 33(S1), pages S59-S65.
    7. Cutler, Nicholas J. & Boerema, Nicholas D. & MacGill, Iain F. & Outhred, Hugh R., 2011. "High penetration wind generation impacts on spot prices in the Australian national electricity market," Energy Policy, Elsevier, vol. 39(10), pages 5939-5949, October.
    8. Jónsson, Tryggvi & Pinson, Pierre & Madsen, Henrik, 2010. "On the market impact of wind energy forecasts," Energy Economics, Elsevier, vol. 32(2), pages 313-320, March.
    9. Grothe, Oliver & Schnieders, Julius, 2011. "Spatial dependence in wind and optimal wind power allocation: A copula-based analysis," Energy Policy, Elsevier, vol. 39(9), pages 4742-4754, September.
    10. Francis A. Longstaff & Ashley W. Wang, 2004. "Electricity Forward Prices: A High-Frequency Empirical Analysis," Journal of Finance, American Finance Association, vol. 59(4), pages 1877-1900, 08.
    11. Hagspiel, Simeon & Papaemannouil, Antonis & Schmid, Matthias & Andersson, Göran, 2012. "Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid," Applied Energy, Elsevier, vol. 96(C), pages 33-44.
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