Artificial intelligence techniques in smart grid: A survey

OA Omitaomu, H Niu - Smart Cities, 2021 - mdpi.com
The smart grid is enabling the collection of massive amounts of high-dimensional and multi-
type data about the electric power grid operations, by integrating advanced metering …

Integrating artificial intelligence Internet of Things and 5G for next-generation smartgrid: A survey of trends challenges and prospect

E Esenogho, K Djouani, AM Kurien - Ieee Access, 2022 - ieeexplore.ieee.org
Smartgrid is a paradigm that was introduced into the conventional electricity network to
enhance the way generation, transmission, and distribution networks interrelate. It involves …

Foundations and challenges of low-inertia systems

F Milano, F Dörfler, G Hug, DJ Hill… - 2018 power systems …, 2018 - ieeexplore.ieee.org
The electric power system is currently undergoing a period of unprecedented changes.
Environmental and sustainability concerns lead to replacement of a significant share of …

A deep-learning intelligent system incorporating data augmentation for short-term voltage stability assessment of power systems

Y Li, M Zhang, C Chen - Applied Energy, 2022 - Elsevier
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 …

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 …

A review of machine learning approaches to power system security and stability

OA Alimi, K Ouahada, AM Abu-Mahfouz - IEEE Access, 2020 - ieeexplore.ieee.org
Increasing use of renewable energy sources, liberalized energy markets and most
importantly, the integrations of various monitoring, measuring and communication …

Intelligent fault detection scheme for microgrids with wavelet-based deep neural networks

JQ James, Y Hou, AYS Lam… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Fault detection is essential in microgrid control and operation, as it enables the system to
perform fast fault isolation and recovery. The adoption of inverter-interfaced distributed …

Online false data injection attack detection with wavelet transform and deep neural networks

JQ James, Y Hou, VOK Li - IEEE Transactions on Industrial …, 2018 - ieeexplore.ieee.org
State estimation is critical to the operation and control of modern power systems. However,
many cyber-attacks, such as false data injection attacks, can circumvent conventional …

Recent developments in machine learning for energy systems reliability management

L Duchesne, E Karangelos… - Proceedings of the …, 2020 - ieeexplore.ieee.org
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 …

[HTML][HTML] Dynamic modeling, stability analysis and control of interconnected microgrids: A review

M Naderi, Y Khayat, Q Shafiee, F Blaabjerg, H Bevrani - Applied Energy, 2023 - Elsevier
This paper reviews concepts of interconnected microgrids (IMGs) as well as compare and
classify their modeling, stability analysis, and control methods. To develop benefits of …