Deep reinforcement learning for smart grid operations: algorithms, applications, and prospects
With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …
more complicated power system with high uncertainty is gradually formed, which brings …
[HTML][HTML] Smart grids: A comprehensive survey of challenges, industry applications, and future trends
With the increasing energy demands of the 21st century, there is a clear need for developing
a more sustainable method of energy generation, distribution, and transmission. Modern …
a more sustainable method of energy generation, distribution, and transmission. Modern …
Generalized graph neural network-based detection of false data injection attacks in smart grids
False data injection attacks (FDIAs) pose a significant threat to smart power grids. Recent
efforts have focused on developing machine learning (ML)-based defense strategies against …
efforts have focused on developing machine learning (ML)-based defense strategies against …
A distributionally robust defender-attacker-defender model for resilience enhancement of power systems against malicious cyberattacks
Z Liu, L Wang - IEEE Transactions on Power Systems, 2022 - ieeexplore.ieee.org
The cybersecurity of electric power grids is emerging as a critical challenge for the power
industry in the transformation of modern power systems towards the future smart grid. It is of …
industry in the transformation of modern power systems towards the future smart grid. It is of …
Robust graph autoencoder-based detection of false data injection attacks against data poisoning in smart grids
Machine learning-based detection of false data injection attacks (FDIAs) in smart grids relies
on labeled measurement data for training and testing. The majority of existing detectors are …
on labeled measurement data for training and testing. The majority of existing detectors are …
Bayesian and stochastic game joint approach for Cross-Layer optimal defensive Decision-Making in industrial Cyber-Physical systems
P Yao, Z Jiang, B Yan, Q Yang, W Wang - Information Sciences, 2024 - Elsevier
The propagation of cyber-attacks targeting modern industrial cyber-physical systems
(ICPSs) is considered a sophisticated and persistent cross-layer penetration process, posing …
(ICPSs) is considered a sophisticated and persistent cross-layer penetration process, posing …
Modeling Load Redistribution Attacks in Integrated Electricity-Gas Systems
As the share of gas-fired power generation continues to increase, it is essential to consider
integrated electricity-gas systems (IEGSs). However, the development of IEGSs has led to an …
integrated electricity-gas systems (IEGSs). However, the development of IEGSs has led to an …
Cyber Vulnerabilities of Energy Systems
In an era characterized by extensive use of and reliance on information and communications
technology (ICT), cyber-physical power systems (CPPS) have emerged as a critical integral …
technology (ICT), cyber-physical power systems (CPPS) have emerged as a critical integral …
Attack–Defense Confrontation Analysis and Optimal Defense Strategy Selection Using Hybrid Game Theoretic Methods
B Jin, X Zhao, D Yuan - Symmetry, 2024 - mdpi.com
False data injection attacks are executed in the electricity markets of smart grid systems for
financial benefits. The attackers can maximize their profits through modifying the estimated …
financial benefits. The attackers can maximize their profits through modifying the estimated …
[HTML][HTML] Detecting and mitigating cyber-attacks in AC microgrid composed of marine current turbine DFIGs to improve energy management system
H Mahvash, SA Taher, JM Guerrero - e-Prime-Advances in Electrical …, 2024 - Elsevier
In this paper the new effective approaches for detecting and mitigating the important cyber-
attacks occurred in an AC microgrid (ACMG) renewable energy, including false data …
attacks occurred in an AC microgrid (ACMG) renewable energy, including false data …