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Fault diagnosis method of solar cell based on inverse inference of I-V curves
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Qingyun Zhu1, Fan Liu2, Wei Zeng3
Renewable Energy Resources | 2024, 42(8) : 1030 - 1035
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Renewable Energy Resources | 2024, 42(8): 1030-1035
Fault diagnosis method of solar cell based on inverse inference of I-V curves
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Qingyun Zhu1, Fan Liu2, Wei Zeng3
Affiliations
  • 1 Qinghai Provincial Product Quality Inspection and Testing Institute Xining 810003 China
  • 2 School of Electrical Engineering Nanchang Institute of Technology Nanchang 330099 China
  • 3 State Grid Jiangxi Electric Power Research Institute Nanchang 330096 China
Published: 2024-08-20
Outline
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In this paper, a fault diagnosis strategy for photovoltaic modules based on IV curve inverse method is proposed. This strategy does not need to monitor the surface irradiance and average temperature of the solar cell in real time. After extracting the model parameters, the IV curve library under different irradiance and solar cell temperature is calculated. The open circuit voltage, short circuit current and maximum power point voltage and current of the photovoltaic module are measured during operation to determine whether the module is faulty. By building experimental equipment to simulate typical faults and using this method to judge, the results show that the method proposed in this paper can effectively monitor the faults of components. Using this method, a singleboard fault monitoring module is developed to realize online fault diagnosis of photovoltaic modules, which improves the accuracy of fault diagnosis of photovoltaic modules and the reliability and economy of photovoltaic power station operation.

solar cell  /  parameter identification  /  maximum power point  /  inverse derivation of I-V curve
Qingyun Zhu, Fan Liu, Wei Zeng. Fault diagnosis method of solar cell based on inverse inference of I-V curves[J]. Renewable Energy Resources, 2024 , 42 (8) : 1030 -1035 .
Year 2024 volume 42 Issue 8
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Article Info
  • Receive Date:2023-11-06
  • Online Date:2025-07-22
  • Published:2024-08-20
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  • Received:2023-11-06
Funding
Affiliations
    1 Qinghai Provincial Product Quality Inspection and Testing Institute Xining 810003 China
    2 School of Electrical Engineering Nanchang Institute of Technology Nanchang 330099 China
    3 State Grid Jiangxi Electric Power Research Institute Nanchang 330096 China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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