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3007. Benefits and challenges of soft-linking for large-scale energy system modelling

Invited abstract in session MB-21: Energy sector coupling, optimization and equilibrium, stream OR in Energy.

Monday, 10:30-12:00
Room: 49 (building: 116)

Authors (first author is the speaker)

1. Mathias Berg Rosendal
Department of Management, Technology and Economics, Technical University of Denmark
2. Jean-Marc Janin
R&D, RTE
3. David Pisinger
Management, DTU
4. Rasmus Bramstoft
Technical University of Denmark
5. Marie Münster
DTU Management Engineering, Technical University of Denmark

Abstract

Computational tractability remains a significant challenge in modelling large-scale, sector-coupled energy systems. This study investigates the soft-linking of models to broaden the analysis scope while maintaining practical computation times. A case study is defined because soft-linking applications are unique to the specific research question. Resource adequacy assessment is therefore defined as the scope in a bidirectional coupling of Balmorel (which performs investment and dispatch on time slices) and the stochastic dispatch model, Antares, which optimises dispatch in multiple weather years with hourly resolution. The models are fully harmonised in terms of data, geographical granularity and level of sector-coupling in a pan-European context. The bidirectional soft link is analysed by comparing computation times at different temporal aggregation levels with the objective of finding the least-cost system with the lowest loss of electricity and hydrogen load. A higher degree of aggregation leads to lower computation times per iteration but more inadequate systems. Thus, more iterations are required to adjust investments. The opposite is valid for a less aggregated approach. A discussion is carried out of the different methods used to signal the need for more investment in carrier transmission, generation capacity, etc., and a conclusion on the benefits and challenges of soft-linking is derived from these findings.

Keywords

Status: accepted


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