Deep learning based on Transformer architecture for power system short-term voltage stability assessment with class imbalance
Most existing data-driven power system short-term voltage stability assessment (STVSA)
approaches presume class-balanced input data. However, in practical applications, the …
approaches presume class-balanced input data. However, in practical applications, the …
Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions
Smart grid is the new trend for clean, sustainable, efficient and reliable energy generation,
delivery and use. To ensure stable and secure operation is essential for the smart grid …
delivery and use. To ensure stable and secure operation is essential for the smart grid …
Detecting false data injection attacks in smart grids: A semi-supervised deep learning approach
The dependence on advanced information and communication technology increases the
vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data …
vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data …
A deep-learning intelligent system incorporating data augmentation for short-term voltage stability assessment of power systems
Facing the difficulty of expensive and trivial data collection and annotation, how to make a
deep learning-based short-term voltage stability assessment (STVSA) model work well on a …
deep learning-based short-term voltage stability assessment (STVSA) model work well on a …
Recent developments in machine learning for energy systems reliability management
This article reviews recent works applying machine learning (ML) techniques in the context
of energy systems' reliability assessment and control. We showcase both the progress …
of energy systems' reliability assessment and control. We showcase both the progress …
Prospects and challenges of the machine learning and data-driven methods for the predictive analysis of power systems: A review
W Strielkowski, A Vlasov, K Selivanov, K Muraviev… - Energies, 2023 - mdpi.com
The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …
systems offers the potential to accurately predict and manage the behavior of these systems …
A review on application of artificial intelligence techniques in microgrids
A microgrid can be formed by the integration of different components such as loads,
renewable/conventional units, and energy storage systems in a local area. Microgrids with …
renewable/conventional units, and energy storage systems in a local area. Microgrids with …
[HTML][HTML] Power quality monitoring in electric grid integrating offshore wind energy: A review
The rising integration of offshore wind energy into the electric grid provides remarkable
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …
The research progress and prospect of data mining methods on corrosion prediction of oil and gas pipelines
L Xu, Y Wang, L Mo, Y Tang, F Wang, C Li - Engineering Failure Analysis, 2023 - Elsevier
As the principal means of oil and natural gas transportation, oil and gas pipeline systems
suffer from common corrosion problems, accurate corrosion prediction of oil and gas …
suffer from common corrosion problems, accurate corrosion prediction of oil and gas …
Applications of artificial intelligence in power system operation, control and planning: a review
As different artificial intelligence (AI) techniques continue to evolve, power systems are
undergoing significant technological changes with the primary goal of reducing …
undergoing significant technological changes with the primary goal of reducing …