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Control techniques and the modeling of electrical power flow across transmission networks

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  • Syranidis, Konstantinos
  • Robinius, Martin
  • Stolten, Detlef

Abstract

The ever greater share of renewable energy sources (RES) in the European energy market stresses the transmission grid to its limits with rising frequency. Therefore, there is a pressing need for a spatially and temporally detailed model of the European power system to serve as a basis for investigating the efficient integration of RES. Here we outline a far-reaching description of transmission grid operation and present a review of approaches developed for modeling the physical power flows and the respective congestion management techniques that control them. By this, we hope to equip the interdisciplinary energy research community with a better understanding of power systems and corresponding modeling tools, thus enhancing their respective efforts. Additionally, a literature review and classification of existing studies on these topics is included in the paper as well. The analysis shows that the fundamental modeling components determining power flows across power systems include the electricity market, the inter-zonal power trading and the intra-zonal congestion management models, where a complete incorporation of all of them requires an iterative or multi-level approach. However, due to the high complexity of such an approach, most common and computationally efficient strategies apply integrated approaches using linearized descriptions for the physical flows.

Suggested Citation

  • Syranidis, Konstantinos & Robinius, Martin & Stolten, Detlef, 2018. "Control techniques and the modeling of electrical power flow across transmission networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3452-3467.
  • Handle: RePEc:eee:rensus:v:82:y:2018:i:p3:p:3452-3467
    DOI: 10.1016/j.rser.2017.10.110
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    4. Martin Robinius & Lars Schewe & Martin Schmidt & Detlef Stolten & Johannes Thürauf & Lara Welder, 2019. "Robust optimal discrete arc sizing for tree-shaped potential networks," Computational Optimization and Applications, Springer, vol. 73(3), pages 791-819, July.
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