An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks

S Radhoush, BM Whitaker, H Nehrir - Energies, 2023 - mdpi.com
Distribution grids must be regularly updated to meet the global electricity demand. Some of
these updates result in fundamental changes to the structure of the grid network. Some …

Towards Resilient and Secure Smart Grids against PMU Adversarial Attacks: A Deep Learning-Based Robust Data Engineering Approach

T Berghout, M Benbouzid, Y Amirat - Electronics, 2023 - mdpi.com
In an attempt to provide reliable power distribution, smart grids integrate monitoring,
communication, and control technologies for better energy consumption and management …

An unsupervised adversarial autoencoder for cyber attack detection in power distribution grids

MJ Zideh, MR Khalghani, SK Solanki - Electric Power Systems Research, 2024 - Elsevier
Detection of cyber attacks in smart power distribution grids with unbalanced configurations
poses challenges due to the inherent nonlinear nature of these uncertain and stochastic …

Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters

MEC Bento - Energies, 2024 - mdpi.com
Challenges in the operation of power systems arise from several factors such as the
interconnection of large power systems, integration of new energy sources and the increase …

Detection of False Data Injection Attacks in a Smart Grid Based on WLS and an Adaptive Interpolation Extended Kalman Filter

G Zhang, W Gao, Y Li, X Guo, P Hu, J Zhu - Energies, 2023 - mdpi.com
An accurate power state is the basis of the normal functioning of the smart grid. However,
false data injection attacks (FDIAs) take advantage of the vulnerability in the bad data …

Smart Preventive Maintenance of Hybrid Networks and IoT Systems Using Software Sensing and Future State Prediction

M Minea, VL Minea, A Semenescu - Sensors, 2023 - mdpi.com
At present, IoT and intelligent applications are developed on a large scale. However, these
types of new applications require stable wireless connectivity with sensors, based on …

[PDF][PDF] Detecting false data injection attacks in industrial Internet of Things using an optimized bidirectional gated recurrent unit-swarm optimization algorithm model

NS Divya, R Vatambeti - Acadlore Transactions on AI and …, 2023 - library.acadlore.com
The rapid adoption of the Industrial Internet of Things (IIoT) paradigm has left systems
vulnerable due to insufficient security measures. False data injection attacks (FDIAs) present …

A Novel False Measurement Data Detection Mechanism for Smart Grids

MA Shahid, F Ahmad, R Nawaz, SU Khan, A Wadood… - Energies, 2023 - mdpi.com
With the growing cyber-infrastructure of smart grids, the threat of cyber-attacks has
intensified, posing an increased risk of compromised communication links. Of particular …

Reinforcing smart grid integrity: an enhanced cybersecurity framework for plug-in hybrid electric vehicles

RA Kumar, RS Ganesh - Electrical Engineering, 2024 - Springer
PHEVs offer significant advantages in terms of reducing carbon emissions and reliance on
fossil fuels, making them increasingly popular in the transition towards sustainable energy …

融合无监督和有监督学习的虚假数据注入攻击检测.

黄冬梅, 王一帆, 胡安铎, 周游… - Electric Power …, 2024 - search.ebscohost.com
虚假数据注入攻击(falsedatainjectionattack, FDIA) 是智能电网安全与稳定运行面临的严重威胁.
文中针对FDIA 检测中存在的有标签数据稀少, 正常和攻击样本极不平衡的问题 …