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The strong effect of network resolution on electricity system models with high shares of wind and solar

Frysztacki, Martha Maria ORCID iD icon; Hörsch, Jonas; Hagenmeyer, Veit; Brown, Tom


Energy system modellers typically choose a low spatial resolution for their models based on administrative boundaries such as countries, which eases data collection and reduces computation times. However, a low spatial resolution can lead to sub-optimal investment decisions for wind and solar generation. Ignoring power grid bottlenecks within regions tends to underestimate system costs, while combining locations with different wind and solar capacity factors in the same resource class tends to overestimate costs. We investigate these two competing effects in a capacity expansion model for Europe’s power system with a high share of renewables, taking advantage of newly-available high-resolution datasets as well as computational advances. We vary the number of nodes, interpolating between a 37-node model based on country and synchronous zone boundaries, and a 1024-node model based on the location of electricity substations. If we focus on the effect of renewable resource resolution and ignore network restrictions, we find that a higher resolution allows the optimal solution to concentrate wind and solar capacity at sites with better capacity factors and thus reduces system costs by up to 10% compared to a low resolution model. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000131224
Veröffentlicht am 08.04.2021
DOI: 10.1016/j.apenergy.2021.116726
Zitationen: 47
Web of Science
Zitationen: 37
Zitationen: 68
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 06.2021
Sprache Englisch
Identifikator ISSN: 0306-2619
KITopen-ID: 1000131224
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Erschienen in Applied energy
Verlag Elsevier
Band 291
Seiten Article: 116726
Nachgewiesen in Scopus
Web of Science
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