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 …
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
Smartgrid is a paradigm that was introduced into the conventional electricity network to
enhance the way generation, transmission, and distribution networks interrelate. It involves …
enhance the way generation, transmission, and distribution networks interrelate. It involves …
Foundations and challenges of low-inertia systems
The electric power system is currently undergoing a period of unprecedented changes.
Environmental and sustainability concerns lead to replacement of a significant share of …
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
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 …
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 …
A review of machine learning approaches to power system security and stability
Increasing use of renewable energy sources, liberalized energy markets and most
importantly, the integrations of various monitoring, measuring and communication …
importantly, the integrations of various monitoring, measuring and communication …
Intelligent fault detection scheme for microgrids with wavelet-based deep neural networks
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 …
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
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 …
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 …
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
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 …
classify their modeling, stability analysis, and control methods. To develop benefits of …