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Introduction <p>Due to the increasing energy crisis, demand for renewable energy sources have risen quickly. In most cases, solar-connected power systems are designed to meet increasing power demand. However, the inherent variability of climatic conditions over time presents a challenge. To mitigate this, Maximum Power Point Tracking (MPPT) strategies are integrated with solar systems.</p> Objectives <p>This study helps to extract maximum power from PV panel and reduced the harmonics in MLI. </p> Methods <p>In this paper, a fuzzy-based MPPT is used to track high power from solar. In this proposed work, the voltage and current from the solar panels are sent to a fuzzy-based controller, which regulates the optimum switching pulses to the buck-boost converter. Furthermore, multi-level inverters (MLI) complicate the power conversion process. One of the major issues with the MLI is the increased number of switches and DC sources. As a result, this paper proposed a novel 127-level MLI with 12 switches and 6 DC sources. The MLI's output voltage reduces harmonics by using the coati optimization algorithm (COA).</p> Results <p>The proposed method is implemented in the Matlab/Simulink tool to show enhanced performance. THD of the Multilevel Inverter (MLI) was compared with existing methods. The proposed inverter achieved a THD of 0.41%. Additionally, the proposed method is compared to existing methods to validate the faster convergence.</p> Conclusion <p>This provided the optimal switching angles for the proposed MLI while reducing total harmonic distortions (THD). </p>

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Control Approach of Solar PV Fed 127 Level Inverter with Minimum Switches using Coati Optimization Algorithm

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Tamilmani Ponnurangam,
  • Visalakshi Selvaraj

摘要

Introduction

Due to the increasing energy crisis, demand for renewable energy sources have risen quickly. In most cases, solar-connected power systems are designed to meet increasing power demand. However, the inherent variability of climatic conditions over time presents a challenge. To mitigate this, Maximum Power Point Tracking (MPPT) strategies are integrated with solar systems.

Objectives

This study helps to extract maximum power from PV panel and reduced the harmonics in MLI.

Methods

In this paper, a fuzzy-based MPPT is used to track high power from solar. In this proposed work, the voltage and current from the solar panels are sent to a fuzzy-based controller, which regulates the optimum switching pulses to the buck-boost converter. Furthermore, multi-level inverters (MLI) complicate the power conversion process. One of the major issues with the MLI is the increased number of switches and DC sources. As a result, this paper proposed a novel 127-level MLI with 12 switches and 6 DC sources. The MLI's output voltage reduces harmonics by using the coati optimization algorithm (COA).

Results

The proposed method is implemented in the Matlab/Simulink tool to show enhanced performance. THD of the Multilevel Inverter (MLI) was compared with existing methods. The proposed inverter achieved a THD of 0.41%. Additionally, the proposed method is compared to existing methods to validate the faster convergence.

Conclusion

This provided the optimal switching angles for the proposed MLI while reducing total harmonic distortions (THD).