Benchmark of machine learning algorithms on transient stability prediction in renewable rich power grids under cyber-attacks
K Aygul, M Mohammadpourfard, M Kesici… - Internet of Things, 2024 - Elsevier
This study addresses the problem of ensuring accurate online transient stability prediction in
modern power systems that are increasingly dependent on smart grid technology and are …
modern power systems that are increasingly dependent on smart grid technology and are …
Physics-informed graphical learning and Bayesian averaging for robust distribution state estimation
This article proposes a robust topology change-aware distribution system state estimation
(DSSE) method based on a physics-informed graph neural network and Bayesian …
(DSSE) method based on a physics-informed graph neural network and Bayesian …
DAE-PINN: a physics-informed neural network model for simulating differential algebraic equations with application to power networks
Deep learning-based surrogate modeling is becoming a promising approach for learning
and simulating dynamical systems. However, deep-learning methods find it very challenging …
and simulating dynamical systems. However, deep-learning methods find it very challenging …
Towards adoption of GNNs for power flow applications in distribution systems
An essential component of smart grid applications is the ability to solve the power flow (PF)
problem in real-time. As numerical methods are too slow, the use of neural networks (NNs) …
problem in real-time. As numerical methods are too slow, the use of neural networks (NNs) …
Discriminative Signal Recognition for Transient Stability Assessment via Discrete Mutual Information Approximation and Eigen Decomposition of Laplacian Matrix
Transient stability assessment (TSA) is of great significance for the security of power
systems. The widely studied postfault TSA based on machine learning methods relies on …
systems. The widely studied postfault TSA based on machine learning methods relies on …
ST-AGNet: Dynamic power system state prediction with spatial–temporal attention graph-based network
Accurate and timely prediction of power system states is one of the most important
challenging tasks in modern power systems. Considering the integration of renewable …
challenging tasks in modern power systems. Considering the integration of renewable …
GraphPMU: Event clustering via graph representation learning using locationally-scarce distribution-level fundamental and harmonic PMU measurements
A Aligholian, H Mohsenian-Rad - IEEE Transactions on Smart …, 2022 - ieeexplore.ieee.org
This paper is concerned with the complex task of identifying the type and cause of the events
that are captured by distribution-level phasor measurement units (D-PMUs) in order to …
that are captured by distribution-level phasor measurement units (D-PMUs) in order to …
A hybrid spatiotemporal distribution forecast methodology for IES vulnerabilities under uncertain and imprecise space-air-ground monitoring data scenarios
S Chenhao, W Yaoding, Z Xiangjun, W Wen, C Chun… - Applied Energy, 2024 - Elsevier
The weak spots in an integrated energy system that may jeopardize the overall reliability call
for timely and efficient Inspection and Maintenance (I&M). One core step is the reasonable …
for timely and efficient Inspection and Maintenance (I&M). One core step is the reasonable …
Advanced Probabilistic Transient Stability Assessment for Operational Planning: A Physics-Informed Graphical Learning Approach
G Lu, S Bu - IEEE Transactions on Power Systems, 2024 - ieeexplore.ieee.org
Existing probabilistic transient stability assessment (PTSA) methods mainly provide an
overall estimation of the probabilistic transient stability index (TSI) but ignore the temporal …
overall estimation of the probabilistic transient stability index (TSI) but ignore the temporal …
Synchrophasor Technology Applications and Optimal Placement of Micro-Phasor Measurement Unit (μPMU): Part II
In the first part of this paper, a comprehensive analysis has been conducted on the utilization
of Synchrophasor Measurement (SM) and distribution SM in enhancing situation awareness …
of Synchrophasor Measurement (SM) and distribution SM in enhancing situation awareness …