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电动汽车驱动 多电平 ★ 5.0

基于多群体遗传算法的MMC多目标功率损耗优化控制

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

作者 Jifeng Zhao · Jia Pei · Sitong Wu · Hong Fu · Yutan Li · Hui Liu
期刊 IEEE Journal of Emerging and Selected Topics in Power Electronics
出版日期 2025年2月
技术分类 电动汽车驱动
技术标签 多电平
相关度评分 ★★★★★ 5.0 / 5.0
关键词 模块化多电平换流器 功率损耗 环流控制 多目标优化控制 多群体遗传算法
语言:

中文摘要

模块化多电平换流器(MMC)因效率高、易于扩展,已成为高压直流输电系统的核心部件。子模块及其内部半导体器件的功率损耗显著影响MMC的运行成本与使用寿命。基于环流控制的损耗优化方法因其硬件成本低、输出电流谐波小而备受关注。本文提出一种基于多群体遗传算法的多目标功率损耗优化控制策略(MOPLOC-MPGA),实现MMC运行成本与寿命的协同优化。通过仿真与实验验证了该方法在MMC应用中的有效性与适用性。

English 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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SunView 深度解读

该MMC多目标功率损耗优化技术对阳光电源ST系列储能变流器和大型PowerTitan储能系统具有重要应用价值。文中基于多群体遗传算法的环流控制优化策略,可直接应用于阳光电源多电平拓扑产品中,通过协同优化运行成本与器件寿命,降低IGBT/SiC模块的热应力与开关损耗。该方法无需额外硬件成本且保持低谐波输出的特点,与阳光电源追求高效率、高可靠性的产品理念高度契合。建议将该算法集成到iSolarCloud智能运维平台,结合实时工况数据实现储能系统的预测性维护与全生命周期成本优化,提升ST系列产品在大规模储能电站中的竞争力。