Premature Breakdown Identification in Photovoltaic Array Fed IGBT-based Voltage Source Converter

Authors S.S. Ghosh1, S. Mukherjee2, S. Chattopadhyay3, A. Das1

1Department of Electrical Engineering, Jadavpur University, Kolkata, West Bengal, India

2Department of Electrical Engineering, IMPS College of Engineering and Technology, Malda, West Bengal, India

3Department of Electrical Engineering, GKCIET, Malda, West Bengal, India

Issue Volume 15, Year 2023, Number 3
Dates Received 15 May 2023; revised manuscript received 23 June 2023; published online 30 June 2023
Citation S.S. Ghosh, S. Mukherjee, S. Chattopadhyay, A. Das, J. Nano- Electron. Phys. 15 No 3, 03016 (2023)
PACS Number(s) 84.70. + p, 88.80.hj
Keywords Fast Fourier Transform (FFT), Fault Diagnosis, IGBT (2) , PV array, Voltage Source Converter (VSC).

Insulated gate bipolar transistor (IGBT) modern power electronics converters. The ability of the IGBT transistor, which is utilised in power converter circuits, to block high voltages, is one of its most crucial features. Large-scale solar power generations are incorporated into the AC grid via voltage-source converters (VSC). Many other applications also utilise voltage-source converters (VSCs). IGBTs are an integral part of voltage-source converters. Fault in IGBT-based VSCs has an impact on the functionality of all VSC-based systems. So, the fault-proof operation of IGBT is highly desirable. This article presents a methodology to detect the premature IGBT breakdown fault (PIBDF) in a photovoltaic (PV)-grid-connected three-phase three-level Voltage Source Converter (VSC). The work has been done using an analysis that is based on the Fast Fourier Transform (FFT) technique applied to the output phase voltage of VSC. Then for different fault percentage values, the effects on the DC as well as the fundamental frequency component and harmonic distortions have been investigated. Some specific features of the subharmonic components have been studied under the normal and faulty conditions of the IGBT. Further study shows that there are few features suitable for fault identification.

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