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Design of modified long short-term memory-based zebra optimization algorithm for limiting the issue of SHEPWM in
G Krithiga1, S Senthilkumar2, Mohammed Alharbi3
1Department of Electrical and Electronics Engineering, Parisutham Institute of Technology and Science, NH 67, Ring Road, Kamaraj Nagar, Nanjikotttai, Thanjavur, 613006, India. krithiga.g2012@gmail.com.
Scientific Reports
|September 28, 2024
Summary
This study introduces MLSTM-ZOA for multi-level inverters (MLI), significantly reducing total harmonic distortion (THD) and harmonic distortion percentage (HDP) compared to other methods.
Area of Science:
- Electrical Engineering
- Power Electronics
- Artificial Intelligence
Background:
- Multi-level inverters (MLI) are crucial for power conversion but suffer from harmonic distortions.
- Optimizing switching angles (SAs) is key to minimizing total harmonic distortion (THD) in MLIs.
- Existing optimization techniques face challenges in efficiency and convergence speed.
Purpose of the Study:
- To propose a novel MLSTM-ZOA method for rapid SA measurement in MLIs.
- To minimize THD by optimizing modulation index (MI), pulse count, and duty cycle.
- To enhance the performance and convergence of MLI control strategies.
Main Methods:
- Development of the MLSTM-ZOA algorithm for SA calculation.
- Optimization of three key parameters: MI, number of pulses per quarter cycle, and duty cycle.
- Comparative analysis against MPA, HHO, MGMPA, and SF-BOA algorithms.
Main Results:
- MLSTM-ZOA achieved superior THD reduction (up to 81.58%) compared to existing methods.
- Significant improvements in HDP were observed, with gains up to 84.01%.
- The proposed method demonstrated faster convergence and better overall performance.
Conclusions:
- MLSTM-ZOA offers a highly effective solution for THD and HDP minimization in MLIs.
- The algorithm provides a robust and efficient approach for optimizing MLI performance.
- Experimental validation confirms the practical applicability and superiority of the MLSTM-ZOA model.
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