Multilayer inverter with DQZ and neuro-fuzzy control for single maximum power point tracking of hybrid renewable sources
Multilayer inverters (MLIs) play an important role in their efficiency and effec-tiveness. This study proposes a new MLI that is optimally adapted using DQZcontrol and a vague neurological approach for tracking the single maximumpower point of a hybrid renewable energy source. This MLI has a bidirec...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Electronics and Telecommunications Research Institute (ETRI)
2025-08-01
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| Series: | ETRI Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.4218/etrij.2024-0170 |
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| Summary: | Multilayer inverters (MLIs) play an important role in their efficiency and effec-tiveness. This study proposes a new MLI that is optimally adapted using DQZcontrol and a vague neurological approach for tracking the single maximumpower point of a hybrid renewable energy source. This MLI has a bidirectionalfixed switch, the purpose of which is to reduce harmonics and increase thevoltage level. The maximum power point tracking (MPPT) method proposedhere is the only MPPT method that uses neuro-fuzzy control algorithms, mak-ing it superior to other methods. The proposed inverter consists of 12 powersemiconductor switches (IGBTs) connected to three DC power sources—thatis, photovoltaic, wind, and tidal energy power sources. The switching angle forpulse-width modulation can be calculated using the DQZ principle in the pro-posed MLI. Evaluation of the effectiveness of the proposed method usesMATLAB/Simulink simulations, the results being compared to those of theprototype mechanism. We also compare the performance of the MPPT algo-rithm and prototype mechanism, which is connected to a single-phase micro-grid. The proposed method achieves total harmonic distortion (THD)efficiency with a satisfactory performance increase. |
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| ISSN: | 1225-6463 2233-7326 |