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Insights on Germany’s Future Congestion Management from a Multi-Model Approach

Hladik, Dirk; Fraunholz, Christoph 1; Kühnbach, Matthias; Manz, Pia; Kunze, Robert
1 Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

In Germany, the political decision to phase out nuclear and coal-fired power as well as delays in the planned grid extension are expected to intensify the current issue of high grid congestion volumes. In this article, we investigate two instruments which may help to cope with these challenges: market splitting and the introduction of a capacity mechanism. For this purpose, we carry out a comprehensive system analysis by jointly applying the demand side models FORECAST and eLOAD, the electricity market model PowerACE and the optimal power flow model ELMOD. While a German market splitting has a positive short-term impact on the congestion volumes, we find the optimal zonal delimination determined for 2020 to become outdated by 2035 resulting in new grid bottlenecks. Yet, readjusting the zonal configuration would lower the ability of the market split to provide regional investment incentives. Introducing a capacity mechanism with a congestion indicator allows allocating new power plants in regions with higher electricity demand. Consequently, we find the required congestion management to be substantially reduced in this setting. However, given the large amount of design parameters, any capacity mechanism needs to be carefully planned before its introduction to avoid new inefficiences on the market side.

Verlagsausgabe §
DOI: 10.5445/IR/1000122722
Veröffentlicht am 17.08.2020
DOI: 10.3390/en13164176
Zitationen: 6
Zitationen: 7
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1996-1073
KITopen-ID: 1000122722
Erschienen in Energies
Verlag MDPI
Band 13
Heft 16
Seiten 4176
Projektinformation AverS-KIT (BMWK, 0324002A)
Vorab online veröffentlicht am 12.08.2020
Schlagwörter congestion management; market splitting; capacity mechanism; model coupling; demand-side modeling; agent-based modeling; optimal power flow
Nachgewiesen in Scopus
Web of Science
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