Abstract
In consideration of the photovoltaic arrays fault characteristics and the limitations of traditional fault diagnosis methods, a intelligent fault diagnosis system for photovoltaic arrays based on BP neural network is proposed.; The faults' consequences of battery cracking, short circuit and the shadow is analyzed. The neural network is trained by appropriate fault samples. The simulation and experimental research on online fault diagnosis of photovoltaic modules in the Matlab environment are performed,and results proved the accuracy,effectiveness and environmental adaptability of the proposed system.
| Original language | English |
|---|---|
| Title of host publication | Materials Science and Engineering Technology |
| Publisher | Trans Tech Publications Ltd |
| Pages | 2201-2206 |
| Number of pages | 6 |
| ISBN (Print) | 9783038351023 |
| DOIs | |
| State | Published - 2014 |
| Event | 2014 International Conference on Materials Science and Engineering Technology, MSET 2014 - Shanghai, China Duration: 28 Jun 2014 → 29 Jun 2014 |
Publication series
| Name | Advanced Materials Research |
|---|---|
| Volume | 936 |
| ISSN (Print) | 1022-6680 |
| ISSN (Electronic) | 1662-8985 |
Conference
| Conference | 2014 International Conference on Materials Science and Engineering Technology, MSET 2014 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 28/06/14 → 29/06/14 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- BP neural network
- Fault diagnosis
- Matlab simulation
- Network training
- Photovoltaic array
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