Optimizing THD in Modified Multilevel Inverters with IoT-Integrated MPPT Systems for Enhanced Efficiency


Andi Syarifuddin(1*); Hariani Ma’tang Pakka(2); Halit Eren(3); Ahmed Saeed AlGhamdi(4); Nur Fadliah Baso(5);

(1) Universitas Muslim Indonesia
(2) Universitas Muslim Indonesia
(3) Curtin University
(4) Taif University
(5) Universitas Muslim Indonesia
(*) Corresponding Author

  

Abstract


This work proposes a new Modified Multilevel Inverter (MMLI) and provides a comprehensive comparison with Conventional Cascaded H-bridge Inverters. The MMLI features fewer switching devices compared to the conventional H-Bridge Inverter for 9-level voltages and higher. Maximum Power Point Tracking (MPPT) incorporated with a Boost converter ensures a constant output from photovoltaic (PV) arrays, which is then fed to the inverter to achieve the desired number of voltage levels. To enhance the performance and efficiency of the system, IoT technologies were integrated for real-time monitoring and control. Smart sensors and cloud-based platforms were utilized for data collection and analysis, enabling precise control of the MPPT and inverter systems. The integration of IoT resulted in significant improvements in the system's dynamic response, energy conversion efficiency, and overall reliability. The results were validated through simulations in Simulink, with outcomes presented and compared for voltage waveform and harmonic spectrum. The integration of IoT technologies provided substantial benefits, showcasing the interdisciplinary approach of this research in reducing Total Harmonic Distortion (THD) while optimizing inverter operations

Keywords


Boost converters; IOT; Multilevel Inverter; Simulink; Solar Photovoltaic; Total Harmonic Distortion

  
  

Full Text:

PDF
  

Article Metrics

Abstract view: 16 times
PDF view: 20 times
     

Digital Object Identifier

doi  https://doi.org/10.33096/ilkom.v16i2.2092.198-209
  

Cite

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Andi Syarifuddin, Hariani Ma’tang Pakka, Halit Eren, Ahmed Saeed AlGhamdi, Nur Fadliah Baso

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.