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Found 5 papers, 2 papers with code
Fault Detection for Covered Conductors With High-Frequency Voltage Signals: From Local Patterns to Global Features
The detection and characterization of partial discharge (PD) are crucial for the insulation diagnosis of overhead lines with covered conductors.
Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring
Non-intrusive load monitoring addresses the challenging task of decomposing the aggregate signal of a household's electricity consumption into appliance-level data without installing dedicated meters.
Fault Location in Power Distribution Systems via Deep Graph Convolutional Networks
This paper develops a novel graph convolutional network (GCN) framework for fault location in power distribution networks.
Convolutional Sequence to Sequence Non-intrusive Load Monitoring
A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this paper.
Short-term Load Forecasting with Deep Residual Networks
We present in this paper a model for forecasting short-term power loads based on deep residual networks.
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