---

Abstract: In the context of renewable energies, precise and reliable forecasts are necessary to ensure a sustainable and economic operation of energy systems. This paper presents a methodology and environment that allows modelling, simulation and analysis of decentralized and heterogeneous energy system scenarios on a virtual level. An essential requirement for the modelling and simulation of complex network scenarios is a capable abstraction strategy, which allows hierarchical clustering and interaction of several network levels. The approach presented in this contribution provides mechanisms that allow a realistic modelling of complex energy system scenarios covering several network levels, taking into account the specific components, interactions and relationships that exist at each level (e.g. specific electrical lines etc.). The simulation follows a hierarchical tree-based approach, which allows to integrate already existing simulation models into the environment and to generate only a small overhead over the simulation run time. As we can show, the developed environment not only serves as an excellent basis for analysis and optimization purposes but also for the application of artificial intelligence techniques, as it supports the effective generation of training data and verification of optimization results.

---