Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems
Author:
Affiliation:
1. National Renewable Energy Laboratory, Golden, CO, USA
2. Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY, USA
3. New York Power Authority, White Plains, NY, USA
Funder
U.S. Office of Naval Research
National Science Foundation-Algorithms for Modern Power Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
https://ieeexplore.ieee.org/ielam/6287639/10005208/10119158-aam.pdf
Reference57 articles.
1. Application of Smart Meters in High Impedance Fault Detection on Distribution Systems
2. Intelligent Time-Adaptive Transient Stability Assessment System
3. Data analysis and management for optimal application of an advanced ML-based fault location algorithm for low voltage grids
4. Demystifying Learning Rate Policies for High Accuracy Training of Deep Neural Networks
5. Fault Detection for Low-Voltage Residential Distribution Systems With Low-Frequency Measured Data
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