Artificial Intelligence Techniques for Power System Transient Stability Assessment

The high penetration of renewable energy sources, coupled with decommissioning conventional power plants, leads to the reduction system inertia. This has negative repercussions on transient stability systems. purpose this paper is review state-of-the-art regarding application artificial intelligence assessment, a focus different machine, deep, and reinforcement learning techniques. covers data generation processes (from measurements simulations), processing pipelines (features engineering, splitting strategy, dimensionality reduction), model building training (including ensembles hyperparameter optimization techniques), deployment, management (with monitoring for detecting bias drift). focuses, in particular, deep models that show promising results standard benchmark test cases. final aim point out advantages disadvantages approaches, present current challenges existing models, offer view possible future research opportunities.