Scholarlink

Background <p>Multilevel Inverters (MLIs) are popular in renewable energy systems because they produce high voltage waveforms of good quality with low harmonic distortion, modular design and capabilities of generating very high voltages. Though conventional MLIs have high number of components, complex control strategies and difficulty to maintain optimal harmonic performance under dynamic renewable energy operating conditions.</p> Problem Statement <p>Existing MLI topologies face challenges such as high voltage stress, increased switching losses, circuit complexity, and poor THD reduction under dynamic renewable energy inputs, which affecting system efficiency and reliability.</p> Aim and Objectives <p>In this work, an intelligent hybrid control scheme is developed for a reduced component 31-level MLI to achieve better power quality performance. The goals are to minimize THD, reduce voltage stress, and integrate PV and wind energy resources with a CNN controller optimized by a hybrid Pelican–Pufferfish Optimization (HPFO) algorithm.</p> Working Methodology <p>The paper proposes a new 31-level MLI topology consisting of eight switches and three voltage sources. Switching pulses are generated by the CNN-based controller, and the parameter of CNN is optimized by the HPFO algorithm to achieve good harmonic reduction effect. The proposed MLI is integrated with photovoltaic and wind energy sources to operate efficiently under RES.</p> Results and Discussion <p>The performance of the proposed methodology is verified and implemented with MATLAB/SIMULINK. The outcomes verify that the proposed 31-level inverter topologies has a THD of 0.94% for voltage and 0.79% for current, which results in excellent harmonic suppression. It also helps to minimize the number of components, voltage stress, and enhances the quality of the waveforms, efficiency, and reliability.</p> Conclusion <p>The proposed CNN-controlled 31-level MLI is an effective method to improve the power quality and decrease the harmonic distortion with minimal hardware complexity, which is suitable for future renewable energy and smart grid applications.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Hybrid Pelican Pufferfish Optimization-Based CNN for Harmonic Reduction in 31-Level MLI Microgrids

  • 期刊论文

  • 发表日期：

    2026年5月23日

查看全文
  • Mohandas Ramaiah,
  • Bharath Vaniyambadi Sathyanarayanan

摘要

Background

Multilevel Inverters (MLIs) are popular in renewable energy systems because they produce high voltage waveforms of good quality with low harmonic distortion, modular design and capabilities of generating very high voltages. Though conventional MLIs have high number of components, complex control strategies and difficulty to maintain optimal harmonic performance under dynamic renewable energy operating conditions.

Problem Statement

Existing MLI topologies face challenges such as high voltage stress, increased switching losses, circuit complexity, and poor THD reduction under dynamic renewable energy inputs, which affecting system efficiency and reliability.

Aim and Objectives

In this work, an intelligent hybrid control scheme is developed for a reduced component 31-level MLI to achieve better power quality performance. The goals are to minimize THD, reduce voltage stress, and integrate PV and wind energy resources with a CNN controller optimized by a hybrid Pelican–Pufferfish Optimization (HPFO) algorithm.

Working Methodology

The paper proposes a new 31-level MLI topology consisting of eight switches and three voltage sources. Switching pulses are generated by the CNN-based controller, and the parameter of CNN is optimized by the HPFO algorithm to achieve good harmonic reduction effect. The proposed MLI is integrated with photovoltaic and wind energy sources to operate efficiently under RES.

Results and Discussion

The performance of the proposed methodology is verified and implemented with MATLAB/SIMULINK. The outcomes verify that the proposed 31-level inverter topologies has a THD of 0.94% for voltage and 0.79% for current, which results in excellent harmonic suppression. It also helps to minimize the number of components, voltage stress, and enhances the quality of the waveforms, efficiency, and reliability.

Conclusion

The proposed CNN-controlled 31-level MLI is an effective method to improve the power quality and decrease the harmonic distortion with minimal hardware complexity, which is suitable for future renewable energy and smart grid applications.