Results 41 to 50 of about 104,321 (158)

Adaptive multi-channel topology-augmented graph neural networks for secure node classification in API-based power systems

Journal of Engineering and Applied Science
Graph neural network models have demonstrated strong effectiveness across a wide range of graph-oriented learning problems. In complex cyber-physical environments like smart grids, component interactions and multi-domain data exchanges are typically ...
Xuhua Ai, Yiting Huang, Qi Meng, Zijian Lin, Yun Dong, Yuan Yin   +5 more
doaj   +1 more source

Reactive Power Optimization of a Distribution Network Based on Graph Security Reinforcement Learning

Applied Sciences
With the increasing integration of renewable energy, the secure operation of distribution networks faces significant challenges, such as voltage limit violations and increased power losses.
Xu Zhang, Xiaolin Gui, Pei Sun, Xing Li, Yuan Zhang, Xiaoyu Wang, Chaoliang Dang, Xinghua Liu   +7 more
doaj   +1 more source

Lambda number of the enhanced power graph of a finite group

Journal of Algebra and Its Applications
The enhanced power graph of a finite group [Formula: see text] is the simple undirected graph whose vertex set is [Formula: see text] and two distinct vertices [Formula: see text] are adjacent if [Formula: see text] for some [Formula: see text]. An [Formula: see text]-labeling of graph [Formula: see text] is an integer labeling of [Formula: see text ...
null Parveen, Sandeep Dalal, Jitender Kumar   +2 more
openaire   +3 more sources

The rainbow connection number of enhanced power graph

, 2017
Let $G$ be a finite group, the enhanced power graph of $G$, denoted by $Γ_G^e$, is the graph with vertex set $G$ and two vertices $x,y$ are edge connected in $Γ_{G}^e$ if there exist $z\in G$ such that $x,y\in\langle z\rangle$. Let $ζ$ be a edge-coloring of $Γ_G^e$. In this article, we calculate the rainbow connection number of the enhanced power graph
Dupont, Luis A., Mendoza, Daniel G., Rodríguez, Miriam   +2 more
openaire   +2 more sources

Optimal performance of a self-healing microgrid

IET Smart Grid, 2019
This study proposes a multi-objective binary differential evolution algorithm to reconfigure the system and restore the loads within the stand-alone microgrid.
Sheetal Chandak, Pravat Kumar Rout
doaj   +1 more source

Shortcut to multipartite entanglement generation: A graph approach to boson subtractions

npj Quantum Information
We propose a graph method for systematically searching for schemes that can generate multipartite entanglement in linear bosonic systems with heralding.
Seungbeom Chin, Yong-Su Kim, Marcin Karczewski   +2 more
doaj   +1 more source

Data-Driven Short-Term Voltage Stability Assessment Framework in Power System Based on Physics-Enhanced Heterogeneous Graph Attention Network

Engineered Science
Rapid and accurate assessment of short-term voltage stability (STVS) is critical for ensuring secure operation of modern power systems. Existing data-driven approaches often model power networks as homogeneous graphs, neglecting the inherent ...
Hailiang Li, Zhuanglin Liang, Zhi Xu, Dexin Ma, Shiyuan Zhang, Jie Shu   +5 more
doaj   +1 more source

SA-GNN: Prediction of material properties using graph neural network based on multi-head self-attention optimization

AIP Advances
With the development of science and technology and the improvement of hardware computing power, the application of large models in the field of artificial intelligence (AI) has become a current research hotspot Among the focal points in the field of deep
Yasen Cui, Jian Zhu, Wei Zhou, Huaijuan Zang, Yongsheng Ren, Jiajia Xu, Shu Zhan, Wenhui Ma   +7 more
doaj   +1 more source

Fast Assessment Method for Transmission-Interface TTC Under N−1 Scenarios

Energies
In practical power system operation, equipment maintenance and line outages may cause changes in network topology and power flow redistribution. Therefore, fast assessment of the total transfer capability (TTC) of transmission interfaces under N−1 line ...
Zhencheng Liang, Qianqi Qin, Qiuquan Deng, Biyun Chen, Yin Wu, Bin Li   +5 more
doaj   +1 more source

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement

2025 IEEE Power & Energy Society General Meeting (PESGM)
The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions.
Xuesong Wang 0007, Shuo Yuan, Sharaf K. Magableh, Oraib Dawaghreh, Caisheng Wang, Le Yi Wang   +5 more
openaire   +3 more sources