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Curtailing Renewable Feed-In Peaks and Its Impact on Power Grid Extensions in Germany for the Year 2030

A Load Ow Model Using an Enhanced Benders Decomposition Approach

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Advances in Energy System Optimization

Part of the book series: Trends in Mathematics ((TM))

Abstract

Transmission grid extension is a central aspect of the future energy system transition. This is due to the diverging occurrence of renewable energy feed-in and consumption. The existing layout of the German grid was not designed to accommodate this divergence. To analyze the most cost-effective grid extensions, efficient methods for techno-economic analysis are required. The challenge of conducting an analysis of grid extensions involves the lumpy investment decisions and the non-linear character of several restrictions in a real-data environment. The addition of new lines makes the grid characteristic variable for approximately load flow calculations. The following paper presents an application of the Benders Decomposition, dividing the problem into an extension and a dispatch problem combined with a Karush–Kuhn–Tucker-system. This combination enables one to solve the problem within reasonable time by using the favorable conditions contained in the sub-problem. The method is applied to the analysis of the integration of renewable energy within the context of German transmission grid extension planning for the year 2030. It can be shown that curtailing feed-in peaks of renewables can significantly reduce the extent of grid extensions necessary to sustain the energy system in Germany.

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Notes

  1. 1.

    A comprehensive literature about BD and other methods of grid extensions are provided in [10].

  2. 2.

    The assumption is related to the hardship ruling in the EEG 2014. It defines, that all lost revenues have to compensated above 1% of annual income of a year.

  3. 3.

    The individual LCOE as curtailment cost rate are represented with the parameter \(c^{curt}_{ren}\).

  4. 4.

    The discussion can be read in [12].

  5. 5.

    From the system view, the load at every node is to be covered at minimal costs provided by RES. For this intention new transmission capacities are required. This leads to the trade-off between building a new line for transferring RES energy to other regions or curtail regional surplus supply. The non-sold energy is valuated with the LCOE of the individual generators. So the overall costs have to be rectified considering this amount.

  6. 6.

    As part of the ESA\(^2\)-project, an alternative road-map for European energy system transformation to a low carbon economy was calculated. The outcome of the project was based on synergies arising from coupled and highly specified models for calculating the demand, investment in power plants and generation dispatch on a time horizon up to 2050. The EU27+ countries were considered. It is assumed for this paper that the capacities of the neighboring countries will develop according to a similar path presented in the EU Roadmap. The central assumptions are analogical. The complete report is available at researchgate.net.

  7. 7.

    To cope with network security requirements like the n-1-criterion, a transmission reliability margin of 20% is assumed.

  8. 8.

    The demolition or downgrading of existing lines is assumed to be impossible. The TSO can use these existing transmission capacities for transmission reliability measurements.

  9. 9.

    An assumption of the model is the application of nodal price system in Germany. It is assumed that this is going to be implemented by 2030.

  10. 10.

    The line upgrade component model contains binary decisions referring to voltage increase. This method is similar to the extension component model and therefore not demonstrated here.

  11. 11.

    The installation of a further line additionally influences the corridor’s line parameters like series conductance and series susceptance which are summarized in H.

  12. 12.

    If the difference between the upper and lower bound falls below a tolerance level of 6%, the iteration process will stop. The level was chosen after applying different sensitivities. A reduction of this level only leads to longer computational times. Due to the high non linearity (see e.g. Eqs. (12) and (13)) the obtained solution has no global optimality evidence. The process gains at least a local optimum.

  13. 13.

    As discussed in [12], the curtailment compensation can influence the location of further RES plants. If the compensation is not capable of covering the RES investment, the financial risk of additional RES installations will increase since revenues decline.

  14. 14.

    The influence of decentralized storages are investigated in [9].

  15. 15.

    The calculated time slices consider different combinations of wind, photovoltaic feed-in and inelastic demand. Every time slice is weighted by the frequency of similar situations during a year. The authors have verified the adequate level of representation of the used snapshot of 8760h a by successfully meeting the annual conventional and intermittent generation of the reference year 2012.

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Authors and Affiliations

  1. Chair of Energy Economics, TU Dresden, Dresden, Germany

    David Gunkel & Dominik Möst

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  1. David Gunkel
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  2. Dominik Möst
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Correspondence to David Gunkel .

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Editors and Affiliations

  1. Economic Analysis, The Economic and Social Research Institute, Dublin, Ireland

    Valentin Bertsch

  2. Karlsruhe Institute of Technology, Karlsruhe, Germany

    Wolf Fichtner

  3. University of Heidelberg, Heidelberg, Germany

    Vincent Heuveline

  4. Karlsruhe Institute of Technology, Institute of Electric Energy Systems and High-Voltage Technology, Karlsruhe, Germany

    Thomas Leibfried

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Gunkel, D., Möst, D. (2017). Curtailing Renewable Feed-In Peaks and Its Impact on Power Grid Extensions in Germany for the Year 2030. In: Bertsch, V., Fichtner, W., Heuveline, V., Leibfried, T. (eds) Advances in Energy System Optimization. Trends in Mathematics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-51795-7_9

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