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All Journal Mechatronics, Electrical Power, and Vehicular Technology Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC)
Novie Ayub Windarko
Politeknik Elektronika Negeri Surabaya (PENS)
Aerospace Engineering Computer Science & IT Electrical & Electronics Engineering Engineering

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THD Minimization in Seven-Level Packed U-Cell (PUC) Inverter using Particle Swarm Optimization Osamah Abdullah Yahya Amran; Novie Ayub Windarko; Iwan Syarif
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 8, No 1 (2026): February
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v8i1.3352

Abstract

This study presents the modeling and simulation of an asymmetric seven-level Packed U-Cell (PUC) multilevel inverter employing a reduced number of power switches. A Modified Pulse Width Modulation (MPWM) scheme, optimized through the Particle Swarm Optimization (PSO) algorithm, is implemented to determine the optimal switching angles for enhanced harmonic elimination. The primary objective is to improve the output voltage waveform quality while reducing Total Harmonic Distortion (THD) and enhancing switching efficiency. The novelty of this work lies in integrating PSO with MPWM control in an asymmetric seven-level PUC inverter configuration with fewer switches, a combination that has not been previously addressed. Simulation results in Simulink demonstrate that the proposed PSO-optimized MPWM strategy achieves a THD of 17.72%, outperforming conventional modulation techniques. These findings highlight the effectiveness of intelligent optimization methods for multilevel inverter control and their potential contribution to improving power quality in renewable energy applications.
MPPT algorithm based on modified remora optimization algorithm for photovoltaic systems under partial shading conditions Moh. Zaenal Efendi; Akhmad Adnaurrosyid; Muhammad Nizar Habibi; Rachma Prilian Eviningsih; Novie Ayub Windarko; Mentari Putri Jati
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 2 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1257

Abstract

The increasing electricity demand, driven by the growing human population, has led to the need for efficient backup power sources. Solar panels are one of the renewable energy sources that have been widely developed because they only require solar energy as their primary source. However, the phenomenon of partial shading is often a problem in solar panels because it can reduce the output power of the solar panel system, which is caused by shadows from trees or clouds. In this condition, conventional maximum power point tracking (MPPT) algorithms are often limited to the local maximum power point (LMPP). To effectively attain the global maximum power point (GMPP), it is imperative to devise more efficient algorithms. The modified remora optimization algorithm (MROA) has been proposed as a potential solution to this challenge. MROA is an adaptation of the remora optimization algorithm (ROA), inspired by the behavior of remora fish. The results indicate that the algorithm achieves an average accuracy of approximately 99.13 % in both simulation and hardware implementations. Furthermore, when comparing the results of the MROA with those of the original ROA method and particle swarm optimization (PSO), the MROA exhibited superior accuracy, tracking time, and power gain, suggesting that the MROA algorithm effectively circumvents the limitation of the local maximum power point.
Co-Authors Akhmad Adnaurrosyid iwan Syarif Mentari Putri Jati Moh. Zaenal Efendi Muhammad Nizar Habibi Osamah Abdullah Yahya Amran Rachma Prilian Eviningsih