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This talk will present the LF Energy project AINETUS, which implements AI-based decision-support (AI assistant) capabilities for power system operations, addressing the increasing complexity of modern grids driven by high levels of renewable energy integration. Traditional tools are often limited in their ability to anticipate system dynamics and support operators under rapidly changing conditions. AINETUS tackles this gap by combining data-driven techniques with domain knowledge to provide proactive, explainable, and operator-centric support. It will show a set of components designed to work together or independently within existing operational environments, in particular: (1) Human-AI interaction tools that enhance situational awareness. (2) Reinforcement learning agents that identify optimal operational strategies, capable of adapting to evolving grid conditions while respecting physical constraints. (3) Explainability tools and uncertainty estimation that help to provide transparent recommendations to support informed decision-making. AINETUS is designed to integrate with existing platforms and workflows, leveraging environments such as Grid2Op for training and validation.
