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dc.contributor.author
Bröchin, Manuel
dc.contributor.author
Pickering, Brynmor
dc.contributor.author
Tröndle, Tim
dc.contributor.author
Pfenninger, Stefan
dc.date.accessioned
2024-06-11T13:50:23Z
dc.date.available
2024-06-10T06:03:23Z
dc.date.available
2024-06-11T13:50:23Z
dc.date.issued
2024
dc.identifier.issn
2192-0567
dc.identifier.other
10.1186/s13705-024-00458-z
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/677329
dc.identifier.doi
10.3929/ethz-b-000677329
dc.description.abstract
Background: Energy system models based on linear programming have been growing in size with the increasing need to model renewables with high spatial and temporal detail. Larger models lead to high computational requirements. Furthermore, seemingly small changes in a model can lead to drastic differences in runtime. Here, we investigate measures to address this issue. Results: We review the mathematical structure of a typical energy system model, and discuss issues of sparsity, degeneracy and large numerical range. We introduce and test a method to automatically scale models to improve numerical range. We test this method as well as tweaks to model formulation and solver preferences, finding that adjustments can have a substantial impact on runtime. In particular, the barrier method without crossover can be very fast, but affects the structure of the resulting optimal solution. Conclusions: We conclude with a range of recommendations for energy system modellers: first, on large and difficult models, manually select the barrier method or barrier+crossover method. Second, use appropriate units that minimize the model’s numerical range or apply an automatic scaling procedure like the one we introduce here to derive them automatically. Third, be wary of model formulations with cost-free technologies and dummy costs, as those can dramatically worsen the numerical properties of the model. Finally, as a last resort, know the basic solver tolerance settings for your chosen solver and adjust them if necessary.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
BioMed Central
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
Energy system models
en_US
dc.subject
Scaling
en_US
dc.subject
Linear programming
en_US
dc.subject
Numerical issues
en_US
dc.subject
Interior-point
en_US
dc.subject
Simplex
en_US
dc.subject
Benchmark
en_US
dc.title
Harder, better, faster, stronger: understanding and improving the tractability of large energy system models
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2024-06-03
ethz.journal.title
Energy, Sustainability and Society
ethz.journal.volume
14
en_US
ethz.journal.issue
1
en_US
ethz.pages.start
27
en_US
ethz.size
21 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
Sustainable Energy Transition Laboratory
en_US
ethz.grant
SEEDS
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.status
published
en_US
ethz.grant.agreementno
837089
ethz.grant.agreementno
195537
ethz.grant.fundername
EC
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100000780
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
H2020
ethz.grant.program
ERA-NET + EJP
ethz.date.deposited
2024-06-10T06:03:29Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2024-06-11T13:50:24Z
ethz.rosetta.lastUpdated
2024-06-11T13:50:24Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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