Robust nonlinear mathematical transmission expansion planning based on German electricity market simulation

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  • Fraunhofer Institute for Energy Economics and Energy System Technology (IEE)
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Original languageEnglish
Article number106685
JournalElectric power systems research
Volume189
Early online date15 Sept 2020
Publication statusPublished - Dec 2020

Abstract

Requirements on electrical energy transmission and the work of system operators are changing due to the shift from centralized towards decentralized generation. This leads to an increased need of transport capacities in grids. In this paper, a robust method is presented to solve the resulting transmission expansion planning (TEP) problem using a nonlinear mathematical optimization. In terms of TEP optimization successive measures are considered in the used mathematical formulation such as grid optimization, grid enhancement and grid extension. The mathematical optimization is based on a DC power flow formulation using unreduced grid models. The concept of the TEP model design and the implementation of different measures are given in detail in the paper. The applicability of the developed approach is shown by the application to a model of the German transmission grid based on a German electricity market simulation for a yearly simulation calculating an expansion demand of 3047 GWkm.

Keywords

    Grid planning, Market modeling, Mathematical optimization, Planning tool, Transmission expansion planning

ASJC Scopus subject areas

Cite this

Robust nonlinear mathematical transmission expansion planning based on German electricity market simulation. / Stock, David Sebastian; Harms, Yannic; Mende, Denis et al.
In: Electric power systems research, Vol. 189, 106685, 12.2020.

Research output: Contribution to journalArticleResearchpeer review

Stock DS, Harms Y, Mende D, Hofmann L. Robust nonlinear mathematical transmission expansion planning based on German electricity market simulation. Electric power systems research. 2020 Dec;189:106685. Epub 2020 Sept 15. doi: 10.1016/j.epsr.2020.106685
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AU - Mende, Denis

AU - Hofmann, Lutz

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