Deep learning in electrical utility industry: A comprehensive review of a decade of research

M Mishra, J Nayak, B Naik, A Abraham - Engineering Applications of …, 2020 - Elsevier
Smart-grid (SG) is a new revolution in the electrical utility industry (EUI) over the past
decade. With each moving day, some new advanced technologies are coming into the …

Smart energy meters for smart grids, an internet of things perspective

YM Rind, MH Raza, M Zubair, MQ Mehmood… - Energies, 2023 - mdpi.com
Smart energy has evolved over the years to include multiple domains integrated across
multiple technology themes, such as electricity, smart grid, and logistics, linked through …

Two-timescale voltage control in distribution grids using deep reinforcement learning

Q Yang, G Wang, A Sadeghi… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Modern distribution grids are currently being challenged by frequent and sizable voltage
fluctuations, due mainly to the increasing deployment of electric vehicles and renewable …

Real-time power system state estimation and forecasting via deep unrolled neural networks

L Zhang, G Wang, GB Giannakis - IEEE Transactions on Signal …, 2019 - ieeexplore.ieee.org
Contemporary power grids are being challenged by rapid and sizeable voltage fluctuations
that are caused by large-scale deployment of renewable generators, electric vehicles, and …

Data-driven learning-based optimization for distribution system state estimation

AS Zamzam, X Fu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Distribution system state estimation (DSSE) is a core task for monitoring and control of
distribution networks. Widely used algorithms such as Gauss-Newton perform poorly with …

A review on distribution system state estimation algorithms

M Fotopoulou, S Petridis, I Karachalios… - Applied Sciences, 2022 - mdpi.com
The modern energy requirements and the orientation towards Renewable Energy Sources
(RES) integration promote the transition of distribution grids from passive, unidirectional …

A survey of power system state estimation using multiple data sources: PMUs, SCADA, AMI, and beyond

G Cheng, Y Lin, A Abur… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
State estimation (SE) is indispensable for the situational awareness of power systems.
Conventional SE is fed by measurements collected from the supervisory control and data …

[LIVRE][B] Smart Grid Sensors: Principles and Applications

H Mohsenian-Rad - 2022 - books.google.com
Discover the ever-growing field of smart grid sensors, covering traditional and state-of-the-
art sensor technologies, as well as data-driven and intelligent methods for using sensor …

Optimal partial feedback attacks in cyber-physical power systems

G Wu, G Wang, J Sun, J Chen - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article considers false data injection attacks constructed based on partial feedback of
generator frequencies in a cyber-physical power system. The goal of the attacker is to …

Graph multiview canonical correlation analysis

J Chen, G Wang, GB Giannakis - IEEE Transactions on Signal …, 2019 - ieeexplore.ieee.org
Multiview canonical correlation analysis (MCCA) seeks latent low-dimensional
representations encountered with multiview data of shared entities (aka common sources) …