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Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market

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  • Jan Abrell

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  • Friedrich Kunz

    ()

Abstract

In northern Europe, wind energy has become a dominate renewable energy source, due to natural conditions and national support schemes. However, the uncertainty about wind generation affects existing network infrastructure and power production planning of generators, which cannot be fully diminished by wind forecasts. In this paper we develop a stochastic electricity market model to analyze the impact of uncertain wind generation on the different electricity markets as well as network congestion management. Stochastic programming techniques are used to incorporate uncertain wind generation. The technical characteristics of transporting electrical energy as well as power plants are explicitly taken into account. The consecutive clearing of the electricity markets is incorporated by a rolling planning procedure reflecting the market regime of European markets. The model is applied to the German electricity system covering one week. Two different approaches of considering uncertain wind generation are analyzed and compared to a deterministic approach. The results reveal that the flexibility of generation dispatch is increased either by using more flexible generation technologies or by operating rather inflexible technologies under part-load conditions. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Jan Abrell & Friedrich Kunz, 2015. "Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market," Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
  • Handle: RePEc:kap:netspa:v:15:y:2015:i:1:p:117-147
    DOI: 10.1007/s11067-014-9272-4
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    1. Wang, J. & Botterud, A. & Bessa, R. & Keko, H. & Carvalho, L. & Issicaba, D. & Sumaili, J. & Miranda, V., 2011. "Wind power forecasting uncertainty and unit commitment," Applied Energy, Elsevier, vol. 88(11), pages 4014-4023.
    2. Jan Abrell & Hannes Weigt, 2012. "Combining Energy Networks," Networks and Spatial Economics, Springer, vol. 12(3), pages 377-401, September.
    3. Helga Habis & Dávid Csercsik, 2015. "Cooperation with Externalities and Uncertainty," Networks and Spatial Economics, Springer, vol. 15(1), pages 1-16, March.
    4. Traber, Thure & Kemfert, Claudia, 2011. "Gone with the wind? -- Electricity market prices and incentives to invest in thermal power plants under increasing wind energy supply," Energy Economics, Elsevier, vol. 33(2), pages 249-256, March.
    5. 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.
    6. van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F., 2012. "The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty," Energy Economics, Elsevier, vol. 34(6), pages 2089-2101.
    7. Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Azizipanah-Abarghooee, Rasoul, 2013. "An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties," Energy, Elsevier, vol. 50(C), pages 232-244.
    8. Neuhoff, Karsten & Barquin, Julian & Bialek, Janusz W. & Boyd, Rodney & Dent, Chris J. & Echavarren, Francisco & Grau, Thilo & von Hirschhausen, Christian & Hobbs, Benjamin F. & Kunz, Friedrich & Nabe, 2013. "Renewable electric energy integration: Quantifying the value of design of markets for international transmission capacity," Energy Economics, Elsevier, vol. 40(C), pages 760-772.
    9. Tuohy, Aidan & Meibom, Peter & Denny, Eleanor & O'Malley, Mark, 2009. "Unit commitment for systems with significant wind penetration," MPRA Paper 34849, University Library of Munich, Germany.
    10. Friedrich Kunz, 2013. "Improving Congestion Management: How to Facilitate the Integration of Renewable Generation in Germany," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    11. Florian Leuthold & Hannes Weigt & Christian Hirschhausen, 2012. "A Large-Scale Spatial Optimization Model of the European Electricity Market," Networks and Spatial Economics, Springer, vol. 12(1), pages 75-107, March.
    12. Mel Devine & James Gleeson & John Kinsella & David Ramsey, 2014. "A Rolling Optimisation Model of the UK Natural Gas Market," Networks and Spatial Economics, Springer, vol. 14(2), pages 209-244, June.
    13. Leuthold, Florian & Jeske, Till & Weigt, Hannes & von Hirschhausen, Christian, 2009. "When the Wind Blows Over Europe: A Simulation Analysis and the Impact of Grid Extensions," MPRA Paper 65655, University Library of Munich, Germany.
    14. Stein W. Wallace & Stein-Erik Fleten, 2002. "Stochastic programming in energy," GE, Growth, Math methods 0201001, University Library of Munich, Germany, revised 13 Nov 2003.
    15. Hannes Weigt & Jan Abrell, 2012. "Storage and Investments in a Combined Energy Network Model," EcoMod2012 4319, EcoMod.
    16. Giorgia Oggioni & Yves Smeers & Elisabetta Allevi & Siegfried Schaible, 2012. "A Generalized Nash Equilibrium Model of Market Coupling in the European Power System," Networks and Spatial Economics, Springer, vol. 12(4), pages 503-560, December.
    17. Olaf Jonkeren & Ivano Azzini & Luca Galbusera & Stavros Ntalampiras & Georgios Giannopoulos, 2015. "Analysis of Critical Infrastructure Network Failure in the European Union: A Combined Systems Engineering and Economic Model," Networks and Spatial Economics, Springer, vol. 15(2), pages 253-270, June.
    18. Weigt, Hannes & Jeske, Till & Leuthold, Florian & von Hirschhausen, Christian, 2010. ""Take the long way down": Integration of large-scale North Sea wind using HVDC transmission," Energy Policy, Elsevier, vol. 38(7), pages 3164-3173, July.
    19. Delarue, Erik & D'haeseleer, William, 2008. "Adaptive mixed-integer programming unit commitment strategy for determining the value of forecasting," Applied Energy, Elsevier, vol. 85(4), pages 171-181, April.
    20. Spiecker, Stephan & Weber, Christoph, 2014. "The future of the European electricity system and the impact of fluctuating renewable energy – A scenario analysis," Energy Policy, Elsevier, vol. 65(C), pages 185-197.
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    Cited by:

    1. Kunz, Friedrich, 2018. "Quo Vadis? (Un)scheduled electricity flows under market splitting and network extension in central Europe," Energy Policy, Elsevier, vol. 116(C), pages 198-209.
    2. Zhaomiao Guo & Yueyue Fan, 2017. "A Stochastic Multi-agent Optimization Model for Energy Infrastructure Planning under Uncertainty in An Oligopolistic Market," Networks and Spatial Economics, Springer, vol. 17(2), pages 581-609, June.
    3. Zepter, Jan Martin & Weibezahn, Jens, 2019. "Unit commitment under imperfect foresight – The impact of stochastic photovoltaic generation," Applied Energy, Elsevier, vol. 243(C), pages 336-349.
    4. Heuberger, Clara F. & Bains, Praveen K. & Mac Dowell, Niall, 2020. "The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment," Applied Energy, Elsevier, vol. 257(C).
    5. Clemens Gerbaulet & Casimir Lorenz, 2017. "dynELMOD: A Dynamic Investment and Dispatch Model for the Future European Electricity Market," Data Documentation 88, DIW Berlin, German Institute for Economic Research.
    6. Salehizadeh, Mohammad Reza & Soltaniyan, Salman, 2016. "Application of fuzzy Q-learning for electricity market modeling by considering renewable power penetration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1172-1181.
    7. Bjørndal, Endre & Bjørndal, Mette & Midthun, Kjetil & Tomasgard, Asgeir, 2018. "Stochastic electricity dispatch: A challenge for market design," Energy, Elsevier, vol. 150(C), pages 992-1005.
    8. Friedrich Kunz and Alexander Zerrahn, 2016. "Coordinating Cross-Country Congestion Management: Evidence from Central Europe," The Energy Journal, International Association for Energy Economics, vol. 0(Sustainab).
    9. Mulder, Machiel & Scholtens, Bert, 2016. "A plant-level analysis of the spill-over effects of the German Energiewende," Applied Energy, Elsevier, vol. 183(C), pages 1259-1271.
    10. Han, Jinil & Papavasiliou, Anthony, 2015. "Congestion management through topological corrections: A case study of Central Western Europe," Energy Policy, Elsevier, vol. 86(C), pages 470-482.
    11. Friedrich Kunz & Alexander Zerrahn, 2016. "Coordinating Cross-Country Congestion Management," Discussion Papers of DIW Berlin 1551, DIW Berlin, German Institute for Economic Research.
    12. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    13. Alexander Zerrahn & Daniel Huppmann, 2017. "Network Expansion to Mitigate Market Power," Networks and Spatial Economics, Springer, vol. 17(2), pages 611-644, June.
    14. Jonas Egerer, Clemens Gerbaulet, and Casimir Lorenz, 2016. "European Electricity Grid Infrastructure Expansion in a 2050 Context," The Energy Journal, International Association for Energy Economics, vol. 0(Sustainab).
    15. Chen, Liang & Kettunen, Janne, 2017. "Is certainty in carbon policy better than uncertainty?," European Journal of Operational Research, Elsevier, vol. 258(1), pages 230-243.
    16. Savvidis, Georgios & Siala, Kais & Weissbart, Christoph & Schmidt, Lukas & Borggrefe, Frieder & Kumar, Subhash & Pittel, Karen & Madlener, Reinhard & Hufendiek, Kai, 2019. "The gap between energy policy challenges and model capabilities," Energy Policy, Elsevier, vol. 125(C), pages 503-520.
    17. Alexander Zerrahn, 2017. "Wind Power: Mitigated and Imposed External Costs and Other Indirect Economic Effects," DIW Roundup: Politik im Fokus 111, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    Electricity markets; Unit commitment; Stochasticity; Renewable energy; Transmission network;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D41 - Microeconomics - - Market Structure, Pricing, and Design - - - Perfect Competition
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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