Machine learning driven smart electric power systems: Current trends and new perspectives
MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …
Ensuring cybersecurity of smart grid against data integrity attacks under concept drift
For achieving increasing artificial intelligence in future smart grids, a very precise state
estimation (SE) is required as a prerequisite for many other key functionalities for successful …
estimation (SE) is required as a prerequisite for many other key functionalities for successful …
Distribution system state estimation and false data injection attack detection with a multi-output deep neural network
Distribution system state estimation (DSSE) has been introduced to monitor distribution
grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE …
grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE …
Defending Smart Electrical Power Grids against Cyberattacks with Deep -Learning
A key to ensuring the security of smart electrical power grids is to devise and deploy effective
defense strategies against cyberattacks. To achieve this goal, an essential task is to simulate …
defense strategies against cyberattacks. To achieve this goal, an essential task is to simulate …
A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids
The electric grid is a key enabling infrastructure for the ambitious transition towards carbon
neutrality as we grapple with climate change. With deepening penetration of renewable …
neutrality as we grapple with climate change. With deepening penetration of renewable …
Attack power system state estimation by implicitly learning the underlying models
N Costilla-Enriquez, Y Weng - IEEE Transactions on Smart Grid, 2022 - ieeexplore.ieee.org
False data injection attacks (FDIAs) are a real and latent threat in modern power systems
networks due to the unprecedented integration of data acquisition systems. It is of utmost …
networks due to the unprecedented integration of data acquisition systems. It is of utmost …
[HTML][HTML] Simulation of multi-stage attack and defense mechanisms in smart grids
The power grid is a vital infrastructure in modern society, essential for ensuring public safety
and welfare. As it increasingly relies on digital technologies for its operation, it becomes …
and welfare. As it increasingly relies on digital technologies for its operation, it becomes …
An accurate false data injection attack (FDIA) detection in renewable-rich power grids
M Mohammadpourfard, Y Weng… - 2022 10th Workshop …, 2022 - ieeexplore.ieee.org
An accurate state estimation (SE) considering increased uncertainty by the high penetration
of renewable energy systems (RESs) is more and more important to enhance situational …
of renewable energy systems (RESs) is more and more important to enhance situational …
Image processing based approach for false data injection attacks detection in power systems
H Moayyed, M Mohammadpourfard… - IEEE …, 2021 - ieeexplore.ieee.org
With more sensors being installed by utilities for accurate control of power grids, there is a
growing risk of vulnerability to sophisticated data integrity attacks such as false data injection …
growing risk of vulnerability to sophisticated data integrity attacks such as false data injection …
Machine learning: the new language for applications
Machine learning and artificial intelligence are becoming a significant influence on various
research and commercial fields. This review attempts to equip the researchers and industrial …
research and commercial fields. This review attempts to equip the researchers and industrial …