Multiobjective Power Losses Optimization of MMC Based on Multipopulation Genetic Algorithm for HVdc Transmission System

IF 4.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Emerging and Selected Topics in Power Electronics Pub Date : 2025-02-26 DOI:10.1109/JESTPE.2025.3543385
Jifeng Zhao;Jia Pei;Sitong Wu;Hong Fu;Yutan Li;Hui Liu;Wenhui Zhang;Yun Sun;Rujin Wang
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Abstract

The modular multilevel converter (MMC), with its strengths of efficient and easy to expand, has become one of the core components in high-voltage direct current (HVdc) transmission. The gross power losses of the submodule (SM) and the semiconductor devices with the highest losses in the SM significantly influence the operational cost and service life of MMCs. The losses optimization method based on circulating current control has become an important power losses optimization technique due to its advantage of low system hardware costs and low output current harmonics. To achieve co-optimization of MMC operational cost and service life, this article introduces a multiobjective power losses optimization control based on multipopulation genetic algorithm (MOPLOC-MPGA). Simulation and experimental verification are carried out to prove the applicability of the raised MOPLOC-MPGA in MMCs.
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基于多种群遗传算法的直流输电系统MMC多目标损耗优化
模块化多电平变换器(MMC)以其高效、易于扩展等优点,已成为高压直流输电系统的核心部件之一。子模块和子模块中损耗最高的半导体器件的总功率损耗对子模块的运行成本和使用寿命有重要影响。基于循环电流控制的损耗优化方法具有系统硬件成本低、输出电流谐波小等优点,已成为一种重要的功率损耗优化技术。为实现MMC运行成本和寿命的协同优化,提出了一种基于多种群遗传算法(MOPLOC-MPGA)的多目标功率损耗优化控制方法。通过仿真和实验验证,证明了提出的MOPLOC-MPGA在mmc中的适用性。
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来源期刊
CiteScore
12.50
自引率
9.10%
发文量
547
审稿时长
3 months
期刊介绍: The aim of the journal is to enable the power electronics community to address the emerging and selected topics in power electronics in an agile fashion. It is a forum where multidisciplinary and discriminating technologies and applications are discussed by and for both practitioners and researchers on timely topics in power electronics from components to systems.
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