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Open Source Electricity Model for Germany (ELMOD-DE)

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  • Jonas Egerer

Abstract

This data documentation introduces to nodal dispatch models and the literature of the ELMOD model framework, which focuses on bottom-up electricity sector models with detailed spatial representation of the transmission system. The paper provides the technical description of ELMOD-DE, a nodal DC load flow model for the German electricity sector. In alignment with this paper, the described model, including its GAMS code and dataset, is made publicly available as open source model on the website of the DIW Berlin. The dataset uses publicly accessible data sources and includes hourly system data for the German electricity sector of the year 2012. The data documentation also illustrates the variety of insights into the German electricity system, ELMOD-DE provides on nodal level, with examples for hourly nodal system states and aggregated results.

Suggested Citation

  • Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwddc:dd83
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    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.528927.de/diw_datadoc_2016-083.pdf
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    References listed on IDEAS

    as
    1. Casimir Lorenz & Clemens Gerbaulet, 2014. "New Cross-Border Electricity Balancing Arrangements in Europe," Discussion Papers of DIW Berlin 1400, DIW Berlin, German Institute for Economic Research.
    2. Huppmann, Daniel & Egerer, Jonas, 2015. "National-strategic investment in European power transmission capacity," European Journal of Operational Research, Elsevier, vol. 247(1), pages 191-203.
    3. repec:aen:journl:eeep3_2_03egerer is not listed on IDEAS
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    12. Jonas Egerer & Roman Mendelevitch & Christian von Hirschhausen, 2014. "A Lower Carbon Strategy for the Electricity Sector of Kazakhstan to 2030/50: Scenarios for Generation and Network Development ; Technical Report," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 85, number pbk85.
    13. Clemens Gerbaulet & Alexander Weber, 2014. "Is There Still a Case for Merchant Interconnectors?: Insights from an Analysis of Welfare and Distributional Aspects of Options for Network Expansion in the Baltic Sea Region," Discussion Papers of DIW Berlin 1404, DIW Berlin, German Institute for Economic Research.
    14. Egerer, Jonas & Kunz, Friedrich & Hirschhausen, Christian von, 2013. "Development scenarios for the North and Baltic Seas Grid – A welfare economic analysis," Utilities Policy, Elsevier, vol. 27(C), pages 123-134.
    15. 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.
    16. 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).
    17. Ingmar Schlecht & Hannes Weigt, 2015. "Linking Europe: The Role of the Swiss Electricity Transmission Grid until 2050," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 151(II), pages 39-79, June.
    18. 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.
    19. 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.
    20. Jonas Egerer & Clemens Gerbaulet & Richard Ihlenburg & Friedrich Kunz & Benjamin Reinhard & Christian von Hirschhausen & Alexander Weber & Jens Weibezahn, 2014. "Electricity Sector Data for Policy-Relevant Modeling: Data Documentation and Applications to the German and European Electricity Markets," Data Documentation 72, DIW Berlin, German Institute for Economic Research.
    21. Schill, Wolf-Peter & Egerer, Jonas & Rosellón, Juan, 2015. "Testing Regulatory Regimes for Power Transmission Expansion with Fluctuating Demand and Wind Generation," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1-28.
    22. Gabriel, Steven A. & Leuthold, Florian U., 2010. "Solving discretely-constrained MPEC problems with applications in electric power markets," Energy Economics, Elsevier, vol. 32(1), pages 3-14, January.
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    25. Kunz, Friedrich & Zerrahn, Alexander, 2015. "Benefits of coordinating congestion management in electricity transmission networks: Theory and application to Germany," Utilities Policy, Elsevier, vol. 37(C), pages 34-45.
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    Cited by:

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    2. 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.
    3. Assembayeva, Makpal & Egerer, Jonas & Mendelevitch, Roman & Zhakiyev, Nurkhat, 2018. "A spatial electricity market model for the power system: The Kazakhstan case study," Energy, Elsevier, vol. 149(C), pages 762-778.
    4. Md. Nasimul Islam Maruf, 2021. "A Novel Method for Analyzing Highly Renewable and Sector-Coupled Subnational Energy Systems—Case Study of Schleswig-Holstein," Sustainability, MDPI, vol. 13(7), pages 1-24, March.
    5. Charitopoulos, V. & Fajardy, M. & Chyong, C. K. & Reiner, D., 2022. "The case of 100% electrification of domestic heat in Great Britain," Cambridge Working Papers in Economics 2210, Faculty of Economics, University of Cambridge.
    6. vom Scheidt, Frederik & Qu, Jingyi & Staudt, Philipp & Mallapragada, Dharik S. & Weinhardt, Christof, 2022. "Integrating hydrogen in single-price electricity systems: The effects of spatial economic signals," Energy Policy, Elsevier, vol. 161(C).
    7. Lang, Lukas Maximilian & Dallinger, Bettina & Lettner, Georg, 2020. "The meaning of flow-based market coupling on redispatch measures in Austria," Energy Policy, Elsevier, vol. 136(C).
    8. Egerer, Jonas & Weibezahn, Jens & Hermann, Hauke, 2016. "Two price zones for the German electricity market — Market implications and distributional effects," Energy Economics, Elsevier, vol. 59(C), pages 365-381.
    9. 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.
    10. Yoro, Kelvin O. & Daramola, Michael O. & Sekoai, Patrick T. & Wilson, Uwemedimo N. & Eterigho-Ikelegbe, Orevaoghene, 2021. "Update on current approaches, challenges, and prospects of modeling and simulation in renewable and sustainable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    11. Jens Weibezahn & Mario Kendziorski, 2019. "Illustrating the Benefits of Openness: A Large-Scale Spatial Economic Dispatch Model Using the Julia Language," Energies, MDPI, vol. 12(6), pages 1-21, March.
    12. Staudt, Philipp & Oren, Shmuel S., 2021. "Merchant transmission in single-price electricity markets with cost-based redispatch," Energy Economics, Elsevier, vol. 104(C).
    13. Makpal Assembayeva & Jonas Egerer & Roman Mendelevitch & Nurkhat Zhakiyev, 2017. "A Spatial Electricity Market Model for the Power System of Kazakhstan," Discussion Papers of DIW Berlin 1659, DIW Berlin, German Institute for Economic Research.

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