The multilevel inverter (MLI) finds extensive utilization in applications involving high voltage, and power. In grid-connected PV systems, these MLIs offer significant advantages in terms of scalability. However, as the switches number in the MLI rises, the likelihood of faults also increases. The reliability of MLIs is a paramount concern in power industries, necessitating the development of methods to detect switch faults and enhance overall reliability. This paper specifically concentrates on these faults diagnosis utilizing the enhanced SVM (support vector machine). The SVM along with adopting the exceptional feature extraction ability of DWT (discrete wavelet transform) provides outstanding results, which leads to an accuracy of 98.36%. The simulations are implemented in MATLAB Simulink, and the ML algorithm is implemented using the python coding.


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    Title :

    Enhanced Fault Diagnostic Approach for Multi-Level Inverter in Grid-Connected PV System


    Contributors:


    Publication date :

    2024-07-31


    Size :

    1414624 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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