A compressed sensing and CNN‐based method for fault diagnosis of photovoltaic inverters in edge computing scenarios
Abstract Accurate and real‐time diagnosis of the inverter is crucial for the reliability, safety and generation efficiency of the photovoltaic (PV) system. Recently, deep learning (DL) is widely used for accurate diagnosis, which automatically extracts useful features instead of relying on experts....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-05-01
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| Series: | IET Renewable Power Generation |
| Online Access: | https://doi.org/10.1049/rpg2.12383 |