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Hybrid machine learning and deep learning framework for multi-stage fault diagnosis in modern power systems
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DOI：10.1016/j.egyr.2026.109558.png)
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Abstract
En 中文
• HRF-CNN enables multi-stage fault diagnosis for modern smart grids. • Detects faults, operating mode, faulty bus, and fault type. • Validated on a modified IEEE 14-bus smart grid with DERs. • Identifies 11 fault types in grid-connected and islanded modes. • Outperforms conventional ML and DL methods in accuracy and robustness.
Keywords:
Modern power systems
Convolutional neural network
Random forest
Hybrid models
Fault diagnosis
Smart grid smart city
Solar energy
Renewable energy sources
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5.1
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658
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