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Representing node-internal transmission and distribution grids in energy system models

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  • Hess, Denis
  • Wetzel, Manuel
  • Cao, Karl-Kiên

Abstract

Today's energy system models calculate power flows between simplified nodes representing transmission and distribution grid of a region or a country – so called copper plates. Such nodes are often restricted to a few tens thus the grid is not well represented or totally neglected in the whole energy system analysis due to limited computational performance using such models. Here we introduce our new methodology of node-internal grid calculation representing the electricity grid in cost values based on strong correlations between peak load, grid cost and feed-in share of wind and photovoltaic capacity. We validate in our case study this approach using a 491 node model for Germany. This examination area is modelled as enclosed energy system to calculate the grid in a 100% renewable energy system in 2050 enabling maximum grid expansion. Our grid model facilitates grid expansion cost and reduces computational effort. The quantification of the German electricity grid show that the grid makes up to 12% of total system cost equivalent up to 12 billion € per year.

Suggested Citation

  • Hess, Denis & Wetzel, Manuel & Cao, Karl-Kiên, 2018. "Representing node-internal transmission and distribution grids in energy system models," Renewable Energy, Elsevier, vol. 119(C), pages 874-890.
    • Handle: RePEc:eee:renene:v:119:y:2018:i:c:p:874-890
    DOI: 10.1016/j.renene.2017.10.041
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    Cited by:

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    2. Hansen, Kenneth & Breyer, Christian & Lund, Henrik, 2019. "Status and perspectives on 100% renewable energy systems," Energy, Elsevier, vol. 175(C), pages 471-480.
    3. Oei, Pao-Yu & Burandt, Thorsten & Hainsch, Karlo & Löffler, Konstantin & Kemfert, Claudia, 2020. "Lessons from Modeling 100% Renewable Scenarios Using GENeSYS-MOD," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(1), pages 103-120.
    4. Siala, Kais & Mier, Mathias & Schmidt, Lukas & Torralba-Díaz, Laura & Sheykhha, Siamak & Savvidis, Georgios, 2022. "Which model features matter? An experimental approach to evaluate power market modeling choices," Energy, Elsevier, vol. 245(C).
    5. Valeriya Azarova & Mathias Mier, 2021. "Investor Type Heterogeneity in Bottom-Up Optimization Models," ifo Working Paper Series 362, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    6. Frysztacki, Martha Maria & Hörsch, Jonas & Hagenmeyer, Veit & Brown, Tom, 2021. "The strong effect of network resolution on electricity system models with high shares of wind and solar," Applied Energy, Elsevier, vol. 291(C).
    7. Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2020. "Reviewing energy system modelling of decentralized energy autonomy," Energy, Elsevier, vol. 203(C).

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