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.
Highlights
Modern power systems are experiencing fundamental changes that are driven by global warming policies, market forces, and the advancement of technology
Power systems of today face a two-pronged challenge, emanating from an increased penetration of renewable energy sources, coupled with a simultaneous decommissioning of the conventional carbon-fired power plants. This shift of balance between RESs and conventional power plants exposes a major downside of the renewables today, which is a reduced system inertia
This paper provided a state-of-the-art of peer-reviewed research, published mostly within the last five years, on the topic of applying machine learning, deep learning, and reinforcement learning to the power system transient stability assessment (TSA) problem
Summary
Modern power systems are experiencing fundamental changes that are driven by global warming policies, market forces, and the advancement of technology They are, at the same time, facing multiple challenges on different fronts. Power systems of today face a two-pronged challenge, emanating from an increased penetration of renewable energy sources (i.e., wind and photovoltaic power plants, RESs), coupled with a simultaneous decommissioning of the conventional carbon-fired power plants. This shift of balance between RESs and conventional power plants exposes a major downside of the renewables today, which is a reduced system inertia (when less generators with rotating mass are in operation). Transient stability disruptions can be the leading causes behind major outages, which are often accompanied by severe economic losses
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