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@ARTICLE{Frey:1032014,
      author       = {Frey, Ulrich J. and Sasanpour, Shima and Breuer, Thomas and
                      Buschmann, Jan and Cao, Karl-Kiên},
      title        = {{T}ackling the multitude of uncertainties in energy systems
                      analysis by model coupling and high-performance computing},
      journal      = {Frontiers in environmental economics},
      volume       = {3},
      issn         = {2813-2823},
      address      = {Lausanne},
      publisher    = {Frontiers Media SA},
      reportid     = {FZJ-2024-05929},
      pages        = {1398358},
      year         = {2024},
      abstract     = {This paper identifies and addresses three key challenges in
                      energy systems analysis—varying assumptions, computational
                      limitations, and coverage of a few indicators only. First,
                      results depend strongly on assumptions, i.e., varying input
                      data. Hence, comparisons and robust results are hard to
                      achieve. To address this, we use a broad range of possible
                      inputs through an extensive literature review by scenario
                      experts. Second, we overcome computational limitations using
                      high-performance computing (HPC) and an automated workflow.
                      Third, by coupling models and developing 13 indicators to
                      evaluate the overall quality of energy systems in Germany
                      for 2030, we include many aspects of security of supply,
                      market impact, life cycle analysis and cost optimization. A
                      cluster analysis of scenarios by indicators reveals three
                      recognizable clusters, separating systems with a high share
                      of renewables clearly from more conventional sets.
                      Additionally, scenarios can be identified which perform very
                      positive for many of the 13 indicators. We conclude that an
                      automated, coupled workflow on supercomputers based on a
                      broad parameter space is able to produce robust results for
                      many important aspects of future energy systems. Since all
                      models and software components are released as open-source,
                      all components of a multi-perspective model-chain are now
                      available to the energy system modeling community.},
      cin          = {JSC},
      ddc          = {630},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / Verbundvorhaben: UNSEEN '
                      Bewertung der Unsicherheiten in linear optimierenden
                      Energiesystem-Modellen unter Zuhilfenahme Neuronaler Netze,
                      Teilvorhaben: Entwicklung einer integrierten HPC-Workflow
                      Umgebung zur Kopplung von Optimierungsmethoden mit Methode
                      (03EI1004F) / ATMLAO - ATML Application Optimization and
                      User Service Tools (ATMLAO)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(BMWi)03EI1004F /
                      G:(DE-Juel-1)ATMLAO},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.3389/frevc.2024.1398358},
      url          = {https://juser.fz-juelich.de/record/1032014},
}