模块化多电平变换器电池储能系统模型预测控制策略
Model Predictive Control Strategy for Modular Multilevel Converter-Based Battery Energy Storage Systems

模块化多电平变换器(Modular Multilevel Converter, MMC)与电池储能系统相结合，既保留了MMC易于扩展，电压等级高等特性，也能借助储能单元为系统提供有功和无功功率，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，建立系统输出电流与环流的多目标控制函数，并结合在线优化方法获取最佳权重因子，进行寻优计算。然后根据求得的储能模块的投入数，对桥臂内部储能模块进行SOC值的排序，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，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。
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.