Fault diagnosis and on-line monitoring for grid-connected single-phase inverters

• Open circuit fault diagnosis for single-phase inverter is presented in this paper.
• The proposed diagnosis is implemented by adaptive neuro fuzzy inference system.
• The proposed diagnosis is based only on the measurements of inverter output current.
• Graphical User Interface (GUI) is developed to real time monitor the inverter.
• GUI also creates an online database for the inverter data.

The functionality of power electronic converter systems (PECS) is a cornerstone in various industrial applications. One of the key requirements to ensure reliable functions of PECS is the analysis of their behavior during fault conditions. Characterizing the behavior of PECS during the fault conditions can provide a standpoint for enhancing their control and protection algorithms. Moreover, effective solutions for on-line monitoring for PECS are significant in order to improve the system supervision and management. Consequently, this paper presents fault diagnosis and on-line monitoring schemes for grid-connected single-phase inverters in typical commercial PECS utilized for renewable energy distributed generation. The paper provides fault detection, classification and location of the open circuit (O-C) faults which do not trigger the standard protection systems in the single-phase inverters. The proposed fault diagnostic algorithm is implemented by adaptive neuro fuzzy inference system (ANFIS) algorithm and it is based solely on the inverter output current measurements. Therefore, the proposed algorithm requires much fewer inputs compared to the previous research works. Furthermore, the paper implements an on-line monitoring by using a communication interface board which is connected to graphical user interface (GUI) software through transmission control and internet protocols (TCP/IP). The GUI software integrates the on-line monitoring for the electrical signals of the single-phase inverter, as well as incorporates a real time database for these signals.