IDEAS home Printed from https://ideas.repec.org/p/ris/ewikln/2012_004.html
   My bibliography  Save this paper

The role of grid extensions in a cost-efficient transformation of the European electricity system until 2050

Author

Listed:
  • Fürsch, Michaela

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Hagspiel, Simeon

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Jägemann, Cosima

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Nagl, Stephan

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Lindenberger, Dietmar

    (Energiewirtschaftliches Institut an der Universitaet zu Koeln)

  • Tröster, Eckehard

    (Energynautics GmbH)

Abstract

As an attempt to fi ght global warming, many countries try to reduce CO2 emissions in the power sector by significantly increasing the proportion of renewable energies (RES-E). A highly intermeshed electricity transmission grid allows the achievement of this target cost-efficiently by enabling the usage of most favorable RES-E sites and by facilitating the integration of fluctuating RES-E infeed and regional electricity demands. However, construction of new lines is often proceeding very slowly in areas with a high population density. In this paper, we try to quantify the bene ts of optimal transmission grid extensions for Europe until 2050 compared to moderate extensions when ambitious RES-E and CO2 reduction targets are achieved. We iterate a large-scale dynamic investment and dispatch optimization model for Europe with a load-flow based transmission grid model, in order to determine the optimal deployment of electricity generation technologies and transmission grid extensions from a system integrated point of view. Main findings of our analysis include that large transmission grid extensions are needed to achieve the European targets cost-efficiently. When the electricity network is cost-optimally extended, 228,000 km are built until 2050, representing an increase of 76% compared to today. Further findings include substantial increases of average system costs for electricity until 2050, even if RES-E are deployed efficiently throughout Europe, the grid is extended optimally, and if signi cant cost reductions of RES-E are assumed.

Suggested Citation

  • Fürsch, Michaela & Hagspiel, Simeon & Jägemann, Cosima & Nagl, Stephan & Lindenberger, Dietmar & Tröster, Eckehard, 2012. "The role of grid extensions in a cost-efficient transformation of the European electricity system until 2050," EWI Working Papers 2012-4, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
  • Handle: RePEc:ris:ewikln:2012_004
    as

    Download full text from publisher

    File URL: https://www.ewi.uni-koeln.de/cms/wp-content/uploads/2015/12/EWI_WP_12-04_Role_of_grid_Extensions.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Neuhoff, Karsten & Ehrenmann, Andreas & Butler, Lucy & Cust, Jim & Hoexter, Harriet & Keats, Kim & Kreczko, Adam & Sinden, Graham, 2008. "Space and time: Wind in an investment planning model," Energy Economics, Elsevier, vol. 30(4), pages 1990-2008, July.
    2. Nagl, Stephan & Fürsch, Michaela & Jägemann, Cosima & Bettzüge, Marc Oliver, 2011. "The economic value of storage in renewable power systems - the case of thermal energy storage in concentrating solar plants," EWI Working Papers 2011-8, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    3. Palmer, Karen & Burtraw, Dallas, 2005. "Cost-effectiveness of renewable electricity policies," Energy Economics, Elsevier, vol. 27(6), pages 873-894, November.
    4. Nagl, Stephan & Fürsch, Michaela & Lindenberger, Dietmar, 2012. "The costs of electricity systems with a high share of fluctuating renewables - a stochastic investment and dispatch optimization model for Europe," EWI Working Papers 2012-1, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    5. Enzo Sauma & Shmuel Oren, 2006. "Proactive planning and valuation of transmission investments in restructured electricity markets," Journal of Regulatory Economics, Springer, vol. 30(3), pages 358-387, November.
    6. 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.
    7. 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.
    8. Richter, Jan, 2011. "DIMENSION - A Dispatch and Investment Model for European Electricity Markets," EWI Working Papers 2011-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    9. 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.
    10. Mirkhani, Sh. & Saboohi, Y., 2012. "Stochastic modeling of the energy supply system with uncertain fuel price – A case of emerging technologies for distributed power generation," Applied Energy, Elsevier, vol. 93(C), pages 668-674.
    11. Richard Green, 2007. "Nodal pricing of electricity: how much does it cost to get it wrong?," Journal of Regulatory Economics, Springer, vol. 31(2), pages 125-149, April.
    12. Buijs, Patrik & Bekaert, David & Cole, Stijn & Van Hertem, Dirk & Belmans, Ronnie, 2011. "Transmission investment problems in Europe: Going beyond standard solutions," Energy Policy, Elsevier, vol. 39(3), pages 1794-1801, March.
    13. DeCarolis, Joseph F. & Keith, David W., 2006. "The economics of large-scale wind power in a carbon constrained world," Energy Policy, Elsevier, vol. 34(4), pages 395-410, March.
    14. Ludig, Sylvie & Haller, Markus & Schmid, Eva & Bauer, Nico, 2011. "Fluctuating renewables in a long-term climate change mitigation strategy," Energy, Elsevier, vol. 36(11), pages 6674-6685.
    15. Nagl, Stephan & Fürsch, Michaela & Paulus, Moritz & Richter, Jan & Trüby, Johannes & Lindenberger, Dietmar, 2011. "Energy policy scenarios to reach challenging climate protection targets in the German electricity sector until 2050," Utilities Policy, Elsevier, vol. 19(3), pages 185-192.
    16. Paulus, Moritz & Borggrefe, Frieder, 2011. "The potential of demand-side management in energy-intensive industries for electricity markets in Germany," Applied Energy, Elsevier, vol. 88(2), pages 432-441, February.
    17. Enzo Sauma & Shmuel Oren, 2006. "Proactive planning and valuation of transmission investments in restructured electricity markets," Journal of Regulatory Economics, Springer, vol. 30(3), pages 261-290, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stephan Nagl, Michaela Fursch, and Dietmar Lindenberger, 2013. "The Costs of Electricity Systems with a High Share of Fluctuating Renewables: A Stochastic Investment and Dispatch Optimization Model for Europe," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    2. Jägemann, Cosima & Fürsch, Michaela & Hagspiel, Simeon & Nagl, Stephan, 2013. "Decarbonizing Europe's power sector by 2050 — Analyzing the economic implications of alternative decarbonization pathways," Energy Economics, Elsevier, vol. 40(C), pages 622-636.
    3. Lion Hirth, 2015. "The Optimal Share of Variable Renewables: How the Variability of Wind and Solar Power affects their Welfare-optimal Deployment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    4. Joachim Bertsch & Simeon Hagspiel & Lisa Just, 2016. "Congestion management in power systems," Journal of Regulatory Economics, Springer, vol. 50(3), pages 290-327, December.
    5. Gacitua, L. & Gallegos, P. & Henriquez-Auba, R. & Lorca, Á. & Negrete-Pincetic, M. & Olivares, D. & Valenzuela, A. & Wenzel, G., 2018. "A comprehensive review on expansion planning: Models and tools for energy policy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 346-360.
    6. Bertsch, Joachim & Hagspiel, Simeon & Just, Lisa, 2016. "Congestion management in power systems - Long-term modeling framework and large-scale application," EWI Working Papers 2015-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    7. Hagspiel, S. & Jägemann, C. & Lindenberger, D. & Brown, T. & Cherevatskiy, S. & Tröster, E., 2014. "Cost-optimal power system extension under flow-based market coupling," Energy, Elsevier, vol. 66(C), pages 654-666.
    8. Simshauser, Paul, 2024. "On static vs. dynamic line ratings in renewable energy zones," Energy Economics, Elsevier, vol. 129(C).
    9. Paul Simshauser & Farhad Billimoria & Craig Rogers, 2021. "Optimising VRE plant capacity in Renewable Energy Zones," Working Papers EPRG2121, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    10. Ambrosius, M. & Egerer, J. & Grimm, V. & Weijde, A.H. van der, 2020. "Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 285(1), pages 343-359.
    11. Simshauser, Paul, 2021. "Renewable Energy Zones in Australia's National Electricity Market," Energy Economics, Elsevier, vol. 101(C).
    12. Francisco Munoz & Enzo Sauma & Benjamin Hobbs, 2013. "Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards," Journal of Regulatory Economics, Springer, vol. 43(3), pages 305-338, June.
    13. Jägemann, Cosima, 2014. "A note on the inefficiency of technology- and region-specific renewable energy support - The German case," EWI Working Papers 2014-5, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    14. Vincent Rious & Yannick Perez & Philippe Dessante, 2008. "Is combination of nodal pricing and average participation tariff the best solution to coordinate the location of power plants with lumpy transmission investments?," Post-Print hal-00323878, HAL.
    15. Lion Hirth & Falko Ueckerdt & Ottmar Edenhofer, 2014. "Why Wind Is Not Coal: On the Economics of Electricity," Working Papers 2014.39, Fondazione Eni Enrico Mattei.
    16. Wolf-Peter Schill & Jonas Egerer & Juan Rosellón, 2015. "Testing regulatory regimes for power transmission expansion with fluctuating demand and wind generation," Journal of Regulatory Economics, Springer, vol. 47(1), pages 1-28, February.
    17. Zerrahn, Alexander & Schill, Wolf-Peter, 2017. "Long-run power storage requirements for high shares of renewables: review and a new model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1518-1534.
    18. Michaela Fursch & Dietmar Lindenberger & Raimund Malischek & Stephan Nagl & Timo Panke & Johannes Truby, 2012. "German Nuclear Policy Reconsidered: Implications for the Electricity Market," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 3).
    19. Grimm, Veronika & Martin, Alexander & Schmidt, Martin & Weibelzahl, Martin & Zöttl, Gregor, 2016. "Transmission and generation investment in electricity markets: The effects of market splitting and network fee regimes," European Journal of Operational Research, Elsevier, vol. 254(2), pages 493-509.
    20. Alexander Zerrahn & Daniel Huppmann, 2014. "Network Expansion to Mitigate Market Power: How Increased Integration Fosters Welfare," Discussion Papers of DIW Berlin 1380, DIW Berlin, German Institute for Economic Research.

    More about this item

    Keywords

    Renewable energy; GHG reduction; transmission grid; power system optimization;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:ewikln:2012_004. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sabine Williams (email available below). General contact details of provider: https://edirc.repec.org/data/ewikode.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.