Topology-Aware Reliability Assessment by Graph Neural Networks
Author:
Affiliation:
1. Texas A&M University,Electrical and Computer Engineering,College Station,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9813728/9814709/09814806.pdf?arnumber=9814806
Reference15 articles.
1. Inductive Representation Learning on Large Graphs;hamilton;NIPS,2017
2. Convolutional Graph Autoencoder: A Generative Deep Neural Network for Probabilistic Spatio-Temporal Solar Irradiance Forecasting
3. Predicting Cascading Failures in Power Systems using Graph Convolutional Networks;ahmad,2021
4. Fast Grid Splitting Detection for N-1 Contingency Analysis by Graph Computing
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1. Reliability Assessment of Distribution System With Distributed Generation: A Case Study;2023 International Conference on Power, Instrumentation, Energy and Control (PIECON);2023-02-10
2. Assessing Bulk Power System Reliability by End-to-End Line Maintenance-Aware Learning;IEEE Access;2023
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