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This paper gives an overview of the modeling
framework that is being developed within the Horizon2020 project
plan4res. In the context of energy transition, integration of high
shares of renewable energies will play a vital role for achieving the
proposed climate targets. This brings new challenges to modeling
tools, including data construction, implementation and solution
techniques. In order to address these challenges, plan4res aims to
create a well-structured and highly modular framework that will
provide insights into the needs of future energy systems. An
overview of the central modeling aspects is given in this paper.
Finally, three case studies are presented that show the adequacy
and relevance of the proposed optimization framework.
In recent years, European gas transport has been affected by major disruptive events like political issues such as, most recently, the Russian war on Ukraine. To incorporate the impacts of such events into decision-making during the energy transition, more complex models for gas network analysis are required. However, the limited availability of consistent data presents a significant obstacle in this endeavor. We use a mathematical-modeling-based scenario generator to deal with this obstacle. The scenario generator consists of capacitated network flow models representing the gas network at different aggregation levels. In this study, we present the coarse-to-fine approach utilized in this scenario generator.