%0 Journal Article
%T 模块化多电平变换器电池储能系统模型预测控制策略<br>Model Predictive Control Strategy for Modular Multilevel Converter-Based Battery Energy Storage Systems
%A 王嘉豪
%J Modeling and Simulation
%P 656-664
%@ 2324-870X
%D 2025
%I Hans Publishing
%R 10.12677/mos.2025.144318
%X 模块化多电平变换器(Modular Multilevel Converter, MMC)与电池储能系统相结合&#65292;既保留了MMC易于扩展&#65292;电压等级高等特性&#65292;也能借助储能单元为系统提供有功和无功功率&#65292;进而改善电能质量。本文以模块化多电平变换器电池储能系统为研究对象&#65292;建立系统输出电流与环流的多目标控制函数&#65292;并结合在线优化方法获取最佳权重因子&#65292;进行寻优计算。然后根据求得的储能模块的投入数&#65292;对桥臂内部储能模块进行SOC值的排序&#65292;最终输出系统当前时刻最佳投切状态。所提方法对系统输出电流与环流有良好的控制效果&#65292;同时可实现电池储能系统三相间、上下桥臂间以及桥臂内模块间的SOC均衡。仿真实验验证了所提控制策略的有效性与可行性。<br>The integration of modular multilevel converter (MMC) with battery energy storage systems (BESS) preserves the inherent advantages of MMC, such as modular scalability and high-voltage capability, while leveraging energy storage units to provide active and reactive power support for enhanced power quality. This study focuses on an MMC-based BESS, establishing a multi-objective control framework to simultaneously regulate output current and circulating current. An online optimization method is employed to dynamically determine optimal weighting factors for Pareto-frontier tracking. Subsequently, the number of activated battery submodules is calculated based on energy requirements, followed by a state-of-charge (SOC)-sorting algorithm to prioritize submodule switching actions within each arm. The proposed strategy demonstrates precise current tracking capability while achieving SOC balancing across three critical dimensions: inter-phase, upper-lower arm, and intra-arm module levels. Simulation studies validate the effectiveness and feasibility of the control methodology in harmonizing power delivery and energy management objectives.
%K 模块化多电平变换器&#65292
%K 电池储能系统&#65292
%K 模型预测控制&#65292
%K 荷电状态<br>Modular Multilevel Converter
%K Battery Energy Storage System
%K Model Predictive Control
%K State of Charge
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=112195