An open-circuit fault diagnosis method for photovoltaic grid-connected inverter IGBT

Wenchao Jia; Fangren Liu

doi:10.1117/12.3011051

2 November 2023 An open-circuit fault diagnosis method for photovoltaic grid-connected inverter IGBT

Wenchao Jia, Fangren Liu

Proceedings Volume 12919, International Conference on Electronic Materials and Information Engineering (EMIE 2023); 1291906 (2023) https://doi.org/10.1117/12.3011051
Event: 3rd International Conference on Electronic Materials and Information Engineering (EMIE 2023), 2023, Guangzhou,, China

Abstract

Photovoltaic grid-connected inverter is the hub equipment for photovoltaic power generation. Its operation has an important impact on the normal operation of the entire photovoltaic power generation system, and the reliability of the photovoltaic grid-connected inverter is closely related to its normal operation. The main circuit of a grid-connected inverter is composed of several switching devices, which have two kinds of failures, short circuit failure and open circuit failure. According to its characteristics, an open circuit fault diagnosis method for three-phase photovoltaic grid-connected inverter switch devices is studied. The photovoltaic grid-connected inverter model is established using Matlab/Simulink to simulate 22 open circuit failures of IGBT, and the three-phase current waveform output on the AC side is analyzed. The extraction method of the eigenvalue ratio fault eigen is used to reduce the dimension of the eigenvalue. Then, SVM is applied to photovoltaic inverter fault diagnosis, and the superior optimization classification characteristics of SVM are used to diagnose and classify the features extracted by 22 types of IGBT open circuit faults.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wenchao Jia and Fangren Liu "An open-circuit fault diagnosis method for photovoltaic grid-connected inverter IGBT", Proc. SPIE 12919, International Conference on Electronic Materials and Information Engineering (EMIE 2023), 1291906 (2 November 2023); https://doi.org/10.1117/12.3011051

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