Paving the Way for Reinforcement Learning in Smart Grid Co-simulations

Vereno, Dominik; Harb, Jonas; Neureiter, Christian

doi:10.1007/978-3-031-26236-4_21

Cited by 5 publications

References 27 publications

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Introducing a Three‐Layer Model Taxonomy to Facilitate System‐of‐Systems Co‐Simulation

Vereno,

Polanec,

Gross

et al. 2024

INCOSE International Symp

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The growing demand for efficient, resilient, and sustainable electricity infrastructure has led to the emergence of smart grids as cyber‐physical systems of systems. Co‐simulation has proven an effective tool for their analysis and validation by coordinating independent subsystem simulations. However, the reuse and integration of diverse models in co‐simulation poses challenges, requiring compatibility and integration efforts. In response, this paper proposes a model taxonomy with the purpose of facilitating co‐simulation; it comprises three layers: concrete‐instance models, abstract‐instance models, and type models. The taxonomy contributes to the creation of independently developed models that can be seamlessly integrated into a coupled co‐simulation. Furthermore, it reflects the emergence of digital twins in smart grid engineering by the explicit distinction of abstract and concrete instances. The three‐layer taxonomy was derived and validated through a case study on co‐simulation of electric‐vehicle charging infrastructure. The research further analyzes and formalizes three modeling‐and‐simulation challenges framed through the lens of the taxonomy: the integration of models across all three layers, the merging of layers, and the consolidation of instance models to craft joint co‐simulation scenarios. Finally, three concrete recommendations for research and industrial practice are given. Thereby, the study contributes to the efficient and effective model‐based validation of cyber‐physical systems of systems using co‐simulation.

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