Reichelt, David GeorgKühne, StefanScheller, FabianAbitz, DanielJohanning, SimonReussner, Ralf H.Koziolek, AnneHeinrich, Robert2021-01-272021-01-272021978-3-88579-701-2https://dl.gi.de/handle/20.500.12116/34728Decision makers strive for optimal ways of production and usage of energy. To adjust their behavior to the future situation of markets and technology, the execution of different models predicting e.g. energy consumption, energy production, prices and consumer behavior is necessary. This execution is itself time-consuming and requires input data management. Furthermore, since different models cover different aspects of the energy domain, they need to be linked. To speed up the linkage and reduce manual errors, these linkage needs to be automated. We present IRPsim, an infrastructure for computation of different models and their linkage. The IRPsim-infrastructure enables management of model data in a structured database, parallelized model execution and automatic model linkage. Thereby, IRPsim allows researchers and practitioners to use energy system models for strategic business model analysis.en10.18420/inf2020_211617-5468