Abstract
Introduction. Cascaded H-bridge multilevel inverters (CHB-MLI) are becoming increasingly used in applications such as distribution systems, electrical traction systems, high voltage direct conversion systems, and many others. Despite the fact that multilevel inverters contain a large number of control switches, detecting a malfunction takes a significant amount of time. In the fault switch configurations diode included for freewheeling operation during open-fault condition. During short circuit fault conditions are carried out by the fuse, which can reveal the freewheeling current direction. The fault category can be identified independently and also failure of power switches harmed by the functioning and reliability of CHB-MLI. This paper investigates the effects and performance of open and short switching faults of multilevel inverters. Output voltage characteristics of 5 level MLI are frequently determined from distinctive switch faults with modulation index value of 0.85 is used during simulation analysis. In the simulation experiment for the modulation index value of 0.85, one second open and short circuit faults are created for the place of faulty switch. Fault is identified automatically by means of artificial neural network (ANN) technique using sinusoidal pulse width modulation based on distorted total harmonic distortion (THD) and managed by its own. The novelty of the proposed work consists of a fast Fourier transform (FFT) and ANN to identify faulty switch. Purpose. The proposed architecture is to identify faulty switch during open and short failures, which has to be reduced THD and make the system in reliable operation. Methods. The proposed topology is to be design and evaluate using MATLAB/Simulink platform. Results. Using the FFT and ANN approaches, the normal and faulty conditions of the MLI are explored, and the faulty switch is detected based on voltage changing patterns in the output. Practical value. The proposed topology has been very supportive for implementing non-conventional energy sources based multilevel inverter, which is connected to large demand in grid.
Publisher
National Technical University Kharkiv Polytechnic Institute
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Energy Engineering and Power Technology
Cited by
27 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhancing off-grid wind energy systems with controlled inverter integration for improved power quality;Electrical Engineering & Electromechanics;2024-08-19
2. Analysis of Nine Level Single-Phase Cascaded H-Bridge Inverters for EVs;2024 Third International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN);2024-07-18
3. Advanced detection and localization of open circuit faults in two-level three-phase IGBT-based inverters using machine learning approaches and discrete wavelet transform;International Journal of Information Technology;2024-05-28
4. RC4 Cipher Based Securing of Data Exchange in Smart Grid;2024 Second International Conference on Smart Technologies for Power and Renewable Energy (SPECon);2024-04-02
5. Hybrid Fuzzy-Neuro System for Electrical Load Forecasting;2024 Second International Conference on Smart Technologies for Power and Renewable Energy (SPECon);2024-04-02