Tackling the multitude of uncertainties in energy systems analysis by model coupling and high-performance computing

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 achiev...

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Bibliographic Details
Published in:Frontiers in environmental economics Vol. 3
Main Authors: Frey, Ulrich J., Sasanpour, Shima, Breuer, Thomas, Buschmann, Jan, Cao, Karl-Kiên
Format: Journal Article
Language:English
Published: Frontiers Media S.A 23.10.2024
Subjects:
agent-based modeling and simulation
energy system optimization model
high-performance computing
model coupling
uncertainty
ISSN:2813-2823, 2813-2823
Online Access:Get full text
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Summary: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.
ISSN:2813-2823
2813-2823
DOI:10.3389/frevc.2024.1398358