State Estimation in Electric Power Systems Leveraging Graph Neural Networks

Author:

Kundacina Ognjen1,Cosovic Mirsad2,Vukobratovic Dejan3

Affiliation:

1. The Institute for Artificial Intelligence Research and Development of Serbia,Novi Sad,Serbia

2. University of Sarajevo,Faculty of Electrical Engineering,Sarajevo,Bosnia and Herzegovina

3. University of Novi Sad,Faculty of Technical Sciences,Novi Sad,Serbia

Publisher

IEEE

Reference14 articles.

1. On the use of PMUs in power system state estimation;gomez-exposito;Proceedings of the 17th PSCC,2011

2. Distributed Gauss–Newton Method for State Estimation Using Belief Propagation

3. Graph Attention Networks;veli?kovi?,0

4. Optimal Placement of PMUs by Integer Linear Programming

5. IGNNITION: Bridging the Gap between Graph Neural Networks and Networking Systems

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1. Graph Neural Network-Based Distribution System State Estimators;IEEE Transactions on Industrial Informatics;2023-12

2. Time-Synchronized State Estimation Using Graph Neural Networks in Presence of Topology Changes;2023 North American Power Symposium (NAPS);2023-10-15

3. Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms;IEEE Transactions on Smart Grid;2023-09

4. Anomaly Detection in In-Vehicle Networks with Graph Neural Networks;2023 31st Signal Processing and Communications Applications Conference (SIU);2023-07-05

5. Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation;2023 International Balkan Conference on Communications and Networking (BalkanCom);2023-06-05

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