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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
  • Friedrich Kunz

Abstract

In northern Europe wind energy has become a dominating 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 and cannot not 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 an exemplary week. Three different cases of considering uncertain wind generation are analyzed. The results reveal that the flexibility of the generation dispatch is increased either by using more flexible generation technologies or by flexibilizing the generation pattern of rather inflexible technologies.

Suggested Citation

  • Jan Abrell & Friedrich Kunz, 2013. "Integrating Intermittent Renewable Wind Generation: A Stochastic Multi-Market Electricity Model for the European Electricity Market," Discussion Papers of DIW Berlin 1301, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1301
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    References listed on IDEAS

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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, pages 4014-4023.
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    5. repec:kap:netspa:v:17:y:2017:i:2:d:10.1007_s11067-017-9338-1 is not listed on IDEAS
    6. repec:kap:netspa:v:17:y:2017:i:2:d:10.1007_s11067-016-9336-8 is not listed on IDEAS
    7. 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.
    8. 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.
    9. Mulder, Machiel & Scholtens, Bert, 2016. "A plant-level analysis of the spill-over effects of the German Energiewende," Applied Energy, Elsevier, pages 1259-1271.
    10. Friedrich Kunz & Alexander Zerrahn, 2016. "Coordinating Cross-Country Congestion Management," Discussion Papers of DIW Berlin 1551, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    Electricity; Unit Commitment; Stochasticity; Renewable Energy;

    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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