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Computational and Near-Optimal Trade-Offs in Renewable Electricity System Modelling

Neumann, Fabian


In the decades to come, the European electricity system must undergo an unprecedented transformation to avert the devastating impacts of climate change. To devise various possibilities for achieving a sustainable yet cost-efficient system, in the thesis at hand, we solve large optimisation problems that coordinate the siting of generation, storage and transmission capacities. Thereby, it is critical to capture the weather-dependent variability of wind and solar power as well as transmission bottlenecks. In addition to modelling at high spatial and temporal resolution, this requires a detailed representation of the electricity grid. However, since the resulting computational challenges limit what can be investigated, compromises on model accuracy must be made, and methods from informatics become increasingly relevant to formulate models efficiently and to compute many scenarios.

The first part of the thesis is concerned with justifying such trade-offs between model detail and solving times. The main research question is how to circumvent some of the challenging non-convexities introduced by transmission network representations in joint capacity expansion models while still capturing the core grid physics. ... mehr

Volltext §
DOI: 10.5445/IR/1000137267
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Hochschulschrift
Publikationsdatum 13.09.2021
Sprache Englisch
Identifikator KITopen-ID: 1000137267
HGF-Programm 37.12.04 (POF IV, LK 01) Energy Lab 2.0
Verlag Karlsruher Institut für Technologie (KIT)
Umfang x, 179 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Automation und angewandte Informatik (IAI)
Prüfungsdatum 29.07.2021
Projektinformation HGF, HGF IVF, VH-NG-1352
Externe Relationen Forschungsdaten/Software
Schlagwörter energy systems, electricity systems, power systems, optimisation, energy system modelling, modelling-to-generate alternatives, transmission expansion planning, capacity expansion planning, renewable energy
Relationen in KITopen
Referent/Betreuer Hagenmeyer, V.
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
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