Poster (After Call)

FZJ-2022-04941

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Enabling energy systems research on HPC

Breuer, T. (Corresponding author)FZJ* ; Cao, K.-K. ; Wetzel, M. ; Frey, U. ; Sasanpour, S. ; Buschmann, J. ; Böhme, A. ; Vanaret, C.

2022

Please use a persistent id in citations: http://hdl.handle.net/2128/32753

Abstract: Energy systems research strongly relies on large modeling frameworks. Many of them use linear optimization approaches to calculate blueprints for ideal future energy systems, which become increasingly complex, as do the models. The state of the art is to compute them with shared-memory computers combined with approaches to reduce the model size. We overcome this and implement a fully automated workflow on HPC using a newly developed solver for distributed memory architectures. Moreover, we address the challenge of uncertainty in scenario analysis by performing sophisticated parameter variations for large-scale power system models, which cannot be solved in the conventional way. Preliminary results show that we are able to identify clusters of future energy system designs, which perform well from different perspectives of energy system research and also consider disruptive events. Furthermore, we also observe that our approach provides the most insights when being applied to complex rather than simple models.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
2. 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) (03EI1004F)
3. ATMLAO - ATML Application Optimization and User Service Tools (ATMLAO) (ATMLAO)

Appears in the scientific report 2022

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Database coverage:

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