2022
DOI: 10.1038/s41597-022-01737-0
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OSeMOSYS Global, an open-source, open data global electricity system model generator

Abstract: This paper describes OSeMOSYS Global, an open-source, open-data model generator for creating global electricity system models for an active global modelling community. This version of the model generator is freely available and can be used to create interconnected electricity system models for both the entire globe and for any geographically diverse subset of the globe. Compared to other existing global models, OSeMOSYS Global allows for full user flexibility in determining the time slice structure and geograp… Show more

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Cited by 23 publications
(8 citation statements)
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“…Recent studies have highlighted the role of global energy system models such as the Open-Source Energy Modelling System (OSeMOSYS) in generating low-carbon scenarios to assist with the decarbonisation of national energy systems [16,17].…”
Section: Previous Modelling Workmentioning
confidence: 99%
“…Recent studies have highlighted the role of global energy system models such as the Open-Source Energy Modelling System (OSeMOSYS) in generating low-carbon scenarios to assist with the decarbonisation of national energy systems [16,17].…”
Section: Previous Modelling Workmentioning
confidence: 99%
“…There are several computational energy and electric power system tools capable of evaluating interconnected electricity systems around the globe (e.g. [3] , [4] , [5] ). For these computational tools, it is essential that reliable and comprehensive data is used to represent existing systems as well as to include planned developments that are consistent with current policies.…”
Section: Introductionmentioning
confidence: 99%
“…
Figure 1 Overview about existing tools and models in comparison with DAVE. Tools: OSMoGrid 7 , 8 , Ding0 9 , 10 , OpenGridMap 11 , FlexiGIS 12 , GridTool 13 and OSeMOsys Global 14 . Models: PyPSA-Eur 15 , 16 , SimBench 17 , 18 , SciGRID 19 – 21 , GasLib 22 and osmTGmod 23 .
…”
Section: Introductionmentioning
confidence: 99%