[HTML][HTML] Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities

R Machlev, L Heistrene, M Perl, KY Levy, J Belikov… - Energy and AI, 2022 - Elsevier
Despite widespread adoption and outstanding performance, machine learning models are
considered as “black boxes”, since it is very difficult to understand how such models operate …

Artificial intelligence techniques for stability analysis and control in smart grids: Methodologies, applications, challenges and future directions

Z Shi, W Yao, Z Li, L Zeng, Y Zhao, R Zhang, Y Tang… - Applied Energy, 2020 - Elsevier
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 …

Review on interpretable machine learning in smart grid

C Xu, Z Liao, C Li, X Zhou, R Xie - Energies, 2022 - mdpi.com
In recent years, machine learning, especially deep learning, has developed rapidly and has
shown remarkable performance in many tasks of the smart grid field. The representation …

A review of machine learning applications in power system resilience

J Xie, I Alvarez-Fernandez… - 2020 IEEE Power & Energy …, 2020 - ieeexplore.ieee.org
The integration of power electronics enabled devices and the high penetration of renewable
energy drastically increase the complexity of power system operation and control. Power …

AI-oriented smart power system transient stability: the rationality, applications, challenges and future opportunities

W Guo, NMF Qureshi, MA Jarwar, J Kim… - … Energy Technologies and …, 2023 - Elsevier
Nowadays, the power grid has become an active colossal resource generation and
management system due to the wide use of renewable energy and dynamic workloads …

Interpretable time-adaptive transient stability assessment based on dual-stage attention mechanism

Q Chen, N Lin, S Bu, H Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Fast and reliable transient stability assessment (TSA) is significant for safe and stable power
system operation. Deep learning provides a new tool for TSA. However, it is difficult to apply …

A critical review of data-driven transient stability assessment of power systems: principles, prospects and challenges

S Zhang, Z Zhu, Y Li - Energies, 2021 - mdpi.com
Transient stability assessment (TSA) has always been a fundamental means for ensuring
the secure and stable operation of power systems. Due to the integration of new elements …

Artificial intelligence techniques for power system transient stability assessment

P Sarajcev, A Kunac, G Petrovic, M Despalatovic - Energies, 2022 - mdpi.com
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 …

A graph attention networks-based model to distinguish the transient rotor angle instability and short-term voltage instability in power systems

R Zhang, W Yao, Z Shi, L Zeng, Y Tang… - International Journal of …, 2022 - Elsevier
Digital simulation is significant for the operating mode and control decision-making of power
systems. In the process of simulation data analysis, stability analysis is an essential part …

Fault diagnosis of electric motors using deep learning algorithms and its application: A review

Y Yang, MMM Haque, D Bai, W Tang - Energies, 2021 - mdpi.com
Electric motors are used extensively in numerous industries, and their failure can result not
only in machine damage but also a slew of other issues, such as financial loss, injuries, etc …