An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks
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 …
these updates result in fundamental changes to the structure of the grid network. Some …
Experimental validation of a remedial action via Hardware-in-the-Loop System against cyberattacks targeting a lab-scale PV/Wind Microgrid
This paper experimentally validates the effectiveness of a primary/backup framework in
preventing/mitigating the impacts of false data injection (FDI) cyberattacks targeting a lab …
preventing/mitigating the impacts of false data injection (FDI) cyberattacks targeting a lab …
An ANN-entropy-FA model for prediction and optimization of biodiesel-based engine performance
S Chaki, TK Biswas - Applied Soft Computing, 2023 - Elsevier
The present work incorporated full factorial experimentation for performance analysis of
Nahar oil-based biodiesel in a four-stroke diesel engine. The controllable input parameters …
Nahar oil-based biodiesel in a four-stroke diesel engine. The controllable input parameters …
Toward detecting cyberattacks targeting modern power grids: A deep learning framework
Modern power and energy networks include a plethora of distributed control and monitoring
equipment, exchanging data through information and communication technology (ICT) …
equipment, exchanging data through information and communication technology (ICT) …
A privacy-preserving scheme for smart grid using trusted execution environment
The increasing transformation from the legacy power grid to the smart grid brings new
opportunities and challenges to power system operations. Bidirectional communications …
opportunities and challenges to power system operations. Bidirectional communications …
CrowdDCNN: Deep convolution neural network for real-time crowd counting on IoT edge
Ensuring the safety and security of crowded places is a major concern for both the
government and the public. Accurately and quickly estimating the number of people in a …
government and the public. Accurately and quickly estimating the number of people in a …
A coordinated cyberattack targeting load centers and renewable distributed energy resources for undervoltage/overvoltage in the most vulnerable regions of a modern …
An integral step for system operators in protecting modern distribution systems and smart
cities against future cyberattacks is to primarily scrutinize complex cyberattack models …
cities against future cyberattacks is to primarily scrutinize complex cyberattack models …
Trends in Smart Grid Cyber-Physical Security: Components, Threats and Solutions
The increasing focus on cyber-physical security in Smart Grids (SGs) has catalyzed a surge
in research over recent years. This paper comprehensively reviews SG cyber-physical …
in research over recent years. This paper comprehensively reviews SG cyber-physical …
Primal dual algorithm for solving the nonsmooth Twin SVM
In this paper, we propose an improved version of Twin SVM using a non-smooth
optimization method. Twin SVM generally consists in determining two non-parallel planes by …
optimization method. Twin SVM generally consists in determining two non-parallel planes by …
An unsupervised adversarial autoencoder for cyber attack detection in power distribution grids
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 …
poses challenges due to the inherent nonlinear nature of these uncertain and stochastic …