Survey of security advances in smart grid: A data driven approach
With the integration of advanced computing and communication technologies, smart grid is
considered as the next-generation power system, which promises self healing, resilience …
considered as the next-generation power system, which promises self healing, resilience …
Bayesian state estimation for unobservable distribution systems via deep learning
KR Mestav, J Luengo-Rozas… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The problem of state estimation for unobservable distribution systems is considered. A deep
learning approach to Bayesian state estimation is proposed for real-time applications. The …
learning approach to Bayesian state estimation is proposed for real-time applications. The …
Assessment on power systems non-deterministic state estimation algorithms
I Lopez-Ramirez, JE Rodriguez-Seco… - Electric Power Systems …, 2023 - Elsevier
Power systems are operated in a deterministic way. However, the increase in uncertainties
(caused by measurement and communication errors or the absence of complete knowledge …
(caused by measurement and communication errors or the absence of complete knowledge …
Community detection in complex networks via clique conductance
Network science plays a central role in understanding and modeling complex systems in
many areas including physics, sociology, biology, computer science, economics, politics …
many areas including physics, sociology, biology, computer science, economics, politics …
Consensus-based smart grid state estimation algorithm
The distribution power subsystems are usually interconnected to each other, so the design
of the interconnected optimal filtering algorithm for distributed state estimation is a …
of the interconnected optimal filtering algorithm for distributed state estimation is a …
A secure power system distributed state estimation via a consensus-based mechanism and a cooperative trust management strategy
Future power systems are integrated more and more with digitalized and decentralized
platforms in their cyber and physical domains such as industrial IoT (IIoT) technology and …
platforms in their cyber and physical domains such as industrial IoT (IIoT) technology and …
State estimation for unobservable distribution systems via deep neural networks
KR Mestav, J Luengo-Rozas… - 2018 IEEE Power & …, 2018 - ieeexplore.ieee.org
The problem of state estimation for unobservable three-phase unbalanced distribution
systems is considered. A Bayesian approach is proposed that combines Bayesian inference …
systems is considered. A Bayesian approach is proposed that combines Bayesian inference …
A deep learning framework for simulation and defect prediction applied in microelectronics
The prediction of upcoming events in industrial processes has been a long-standing
research goal since it enables optimization of manufacturing parameters, planning of …
research goal since it enables optimization of manufacturing parameters, planning of …
Smart grid state estimation and stabilisation
This paper proposes a smart grid state estimation and stabilisation algorithm. It relies on the
principle of Bayesian filter structure where the smart grid state information is estimated in an …
principle of Bayesian filter structure where the smart grid state information is estimated in an …
Distributed Kalman filter for large-scale power systems with state inequality constraints
Z Cheng, H Ren, B Zhang, R Lu - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article is concerned with a hybrid distributed dynamic state estimation (DSE) algorithm
for large-scale power grids. Based on the mixed phasor measurement unit (PMU) and …
for large-scale power grids. Based on the mixed phasor measurement unit (PMU) and …