Abstract

Due to the energy transition, the operational management of electrical grids is becoming an increasingly complex task, resulting in new requirements for grid monitoring and control systems. In this presentation, various use cases from this area will be considered for which the use of ML/AI is possible. Here, the individual applications will be explained in outline, as well as the expected benefits from using the various AI techniques. Topics include data-driven modeling of hydrogen-based generation units, inertia prediction in future inverter-dominated grids and finally an open-source framework is introduced to facilitate the application of ML-methods in power systems.