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Fault Monitoring Strategy for PV System Based on I-V Feature Library

Huaxing Zhao1, Yanbo Che1,*, Gang Wen2, Yijing Chen3

1 School of Electrical and Information Engineering, Tianjin University, Tianjin, 300000, China
2 State Grid Shuozhou Electric Power Supply Company, Shuozhou, 036000, China
3 China Huaneng Clean Energy Research lnstitute Technology Co., Ltd., Beijing, 102209, China

* Corresponding Author: Yanbo Che. Email: email

Energy Engineering 2024, 121(3), 643-660. https://doi.org/10.32604/ee.2023.045204

Abstract

Long-term use in challenging natural conditions is possible for photovoltaic modules, which are extremely prone to failure. Failure to diagnose and address faults in Photovoltaic (PV) power systems in a timely manner can cause permanent damage to PV modules and, in more serious cases, fires. Therefore, research into photovoltaic module defect detection techniques is crucial for the growth of the photovoltaic sector as well as for maintaining national economic prosperity and ensuring public safety. Considering the drawbacks of the current real-time and historical data-based methods for monitoring distributed PV systems, this paper proposes a method for monitoring PV systems at the module or string level that can be achieved by monitoring only electrical signals. The approach doesn’t need a lot of tests to get the operational data of PV modules beforehand and only requires theoretical feature libraries of PV modules through panel parameter calculations. The present operating conditions and the open-circuit and short-circuit faults can be precisely identified by comparing the observed open-circuit voltage and short-circuit current with the corresponding data in the theoretical feature library. After that, by comparing the measured maximum power point voltage and current with the corresponding data in the theoretical feature library through the threshold method, aging and shadowing faults can be accurately determined. Experimental testing was done to see whether the suggested method was effective. The results show that the proposed technique is able to diagnose open-circuit faults, short-circuit faults, aging faults, and shadowing faults with shadow occlusion above 20%.

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APA Style
Zhao, H., Che, Y., Wen, G., Chen, Y. (2024). Fault monitoring strategy for PV system based on I-V feature library. Energy Engineering, 121(3), 643-660. https://doi.org/10.32604/ee.2023.045204
Vancouver Style
Zhao H, Che Y, Wen G, Chen Y. Fault monitoring strategy for PV system based on I-V feature library. Energ Eng. 2024;121(3):643-660 https://doi.org/10.32604/ee.2023.045204
IEEE Style
H. Zhao, Y. Che, G. Wen, and Y. Chen "Fault Monitoring Strategy for PV System Based on I-V Feature Library," Energ. Eng., vol. 121, no. 3, pp. 643-660. 2024. https://doi.org/10.32604/ee.2023.045204



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