Benchmark of machine learning algorithms on transient stability prediction in renewable rich power grids under cyber-attacks
K Aygul, M Mohammadpourfard, M Kesici… - Internet of Things, 2024 - Elsevier
This study addresses the problem of ensuring accurate online transient stability prediction in
modern power systems that are increasingly dependent on smart grid technology and are …
modern power systems that are increasingly dependent on smart grid technology and are …
Cyber attacks on power grids: Causes and propagation of cascading failures
Cascading effects in the power grid involve an uncontrolled, successive failure of elements.
The root cause of such failures is the combined occurrence of multiple, statistically rare …
The root cause of such failures is the combined occurrence of multiple, statistically rare …
[HTML][HTML] Electric load forecasting under False Data Injection Attacks using deep learning
Precise electric load forecasting at different time horizons is an essential aspect for electricity
producers and consumers who participate in energy markets in order to maximize their …
producers and consumers who participate in energy markets in order to maximize their …
Detection of cyber attacks in grid-tied PV systems using dynamic watermarking
In this article an active defense mechanism for detecting cyber-attacks on a grid-tied PV
system is discussed. The proposed defense mechanism introduces a unique random signal …
system is discussed. The proposed defense mechanism introduces a unique random signal …
Anomaly detection and state correction in smart grid using ekf and data compensation techniques
P Hu, W Gao, Y Li, X Guo, F Hua… - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
The smart grid is built on an integrated and high-speed communication network, which
renders it more vulnerable to cyber-attacks. False data injection attacks (FDIAs) and sudden …
renders it more vulnerable to cyber-attacks. False data injection attacks (FDIAs) and sudden …
Real-time detection of cyber-attacks in modern power grids with uncertainty using deep learning
M Mohammadpourfard, F Ghanaatpishe… - … on Smart Energy …, 2022 - ieeexplore.ieee.org
The smart grid, which is critical for developing smart cities, has a tool called state estimation
(SE), which enables operators to monitor the system's stability. While the SE result is …
(SE), which enables operators to monitor the system's stability. While the SE result is …
A Method to Detect Man in the Middle Attack (MiTM) on a Grid Following PV Inverter
In this paper, a method to detect a man-in-the-middle attack (MiTM) on a grid following PV
inverter is discussed. The control objective of the grid following inverter is to utilize the …
inverter is discussed. The control objective of the grid following inverter is to utilize the …
Anomaly Detection in Load Forecasting for Electric Vehicles Using Image Processing Techniques
The incorporation of electric vehicles (EVs) into the power grid presents significant
challenges, particularly in meeting the electricity requirements of EVs through effective …
challenges, particularly in meeting the electricity requirements of EVs through effective …
Employing Machine Learning Algorithms to Identify False Data Injection in Smart Grid
M Tajdinian, M Mohammadpourfard… - 2024 9th International …, 2024 - ieeexplore.ieee.org
Enhancement in demand of electrical energy from industrial or residential consumers has
resulted in encouraging policy makers to utilize of new generation of power network named …
resulted in encouraging policy makers to utilize of new generation of power network named …
A Review of Cybersecurity Attacks on Bulk Power System: Assessing Risks
MFN Khan, F de Leon - Authorea Preprints, 2024 - techrxiv.org
Cyber security for power systems is becoming a concern for many researchers. However,
the impact of cyberattacks on actual power systems is unclear. This paper discusses …
the impact of cyberattacks on actual power systems is unclear. This paper discusses …