A novel power conversion structure for grid-connected photovoltaic applications based on MLI and LeBlanc transformer using IRSA technique

IF 4 4区环境科学与生态学 Q2 ENVIRONMENTAL STUDIES

Energy & Environment Pub Date : 2023-11-08 DOI:10.1177/0958305x231210994

C Sonia, S Tamilselvi

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引用次数: 0

Abstract

This article proposes a new energy conversion structure by employing a hybrid approach for grid-tied photovoltaic (PV) applications. This structure depends on the LeBlanc transformer and multilevel inverter (MLI). The proposed hybrid system combines the honey badger algorithm (HBA) and the reptile search algorithm (RSA). Crocodiles hunting behavior is enhanced by the HBA technique, also known as the IRSA technique. Voltage source inverters (VSI) are used in the proposed multilevel power converter. The MLI output is attached to the LeBlanc transformer. Multi-string technology is essential to the PV system's configuration. This innovative power converter's structural layout allows for an output voltage at the MLI's output. The proposed IRSA approach is utilized to regulate this power converter. This control system permits a fast and robust response from the MLI. This is also ensured by using the IRSA technique. The performance of the proposed hybrid method is run in MATLAB, and the performance is compared with various existing methods. From the simulation, the proposed approach-based efficiency is higher than the existing one. The proposed method shows a high efficiency of 99% compared with other existing methods, such as the salp swarm algorithm (SSA), bee colony optimization (BCO), and grasshopper optimization algorithm (GOA).

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一种基于MLI和LeBlanc变压器的新型并网光伏电源转换结构

本文提出了一种新的能源转换结构，采用混合方法用于并网光伏(PV)应用。这种结构依赖于勒布朗变压器和多电平逆变器(MLI)。该混合系统结合了蜜獾算法(HBA)和爬行动物搜索算法(RSA)。HBA技术(也称为IRSA技术)增强了鳄鱼的狩猎行为。该多电平功率变换器采用电压源逆变器(VSI)。MLI输出连接到勒布朗变压器。多管柱技术对光伏系统的配置至关重要。这种创新的功率转换器的结构布局允许输出电压在MLI的输出。采用IRSA方法对该功率变换器进行了控制。该控制系统允许MLI的快速和鲁棒响应。这也可以通过使用IRSA技术来保证。在MATLAB中运行了所提出的混合方法的性能，并与现有的各种方法进行了性能比较。仿真结果表明，该方法的效率高于现有方法。与salp swarm algorithm (SSA)、bee colony optimization (BCO)、grasshopper optimization algorithm (GOA)等现有算法相比，该方法的效率高达99%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Energy & Environment ENVIRONMENTAL STUDIES-

CiteScore

7.60

自引率

7.10%

发文量

157

期刊介绍： Energy & Environment is an interdisciplinary journal inviting energy policy analysts, natural scientists and engineers, as well as lawyers and economists to contribute to mutual understanding and learning, believing that better communication between experts will enhance the quality of policy, advance social well-being and help to reduce conflict. The journal encourages dialogue between the social sciences as energy demand and supply are observed and analysed with reference to politics of policy-making and implementation. The rapidly evolving social and environmental impacts of energy supply, transport, production and use at all levels require contribution from many disciplines if policy is to be effective. In particular E & E invite contributions from the study of policy delivery, ultimately more important than policy formation. The geopolitics of energy are also important, as are the impacts of environmental regulations and advancing technologies on national and local politics, and even global energy politics. Energy & Environment is a forum for constructive, professional information sharing, as well as debate across disciplines and professions, including the financial sector. Mathematical articles are outside the scope of Energy & Environment. The broader policy implications of submitted research should be addressed and environmental implications, not just emission quantities, be discussed with reference to scientific assumptions. This applies especially to technical papers based on arguments suggested by other disciplines, funding bodies or directly by policy-makers.