Abstract
The high penetration of renewable energy sources, coupled with decommissioning of conventional power plants, leads to the reduction of power system inertia. This has negative repercussions on the transient stability of power systems. The purpose of this paper is to review the state-of-the-art regarding the application of artificial intelligence to the power system transient stability assessment, with a focus on different machine, deep, and reinforcement learning techniques. The review covers data generation processes (from measurements and simulations), data processing pipelines (features engineering, splitting strategy, dimensionality reduction), model building and training (including ensembles and hyperparameter optimization techniques), deployment, and management (with monitoring for detecting bias and drift). The review focuses, in particular, on different deep learning models that show promising results on standard benchmark test cases. The final aim of the review is to point out the advantages and disadvantages of different approaches, present current challenges with existing models, and offer a view of the possible future research opportunities.
Petar Sarajčev
Full Professor | Department of Power Grids and Substations
Goran Petrović
Full Professor | Department of Electrical Measurements
Prof. dr. sc. Goran Petrović is a full professor at the Faculty of Electrical Engineering, Mechanical Engineering and Architecture in Split. His research interests include measurement of electrical and process quantities, analysis of geoelectrical and geothermal features of the soil, instrumentation for smart grids, measurement and application of synchrophasors. He is the author of numerous papers published in top-tier scientific journals and contributed to valuable international and national scientific projects.
Marin Despalatović
Full Professor | Department of Electrical Drives and Industrial Control
Full professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses Electric Machines, Electric Drive Systems, and Electromechanical System Modeling. His research focuses on power systems, energy storage, and smart grid technologies, with active participation in multiple national and international projects aimed at advancing energy infrastructure and improving system stability.