基于逆向预测的模块化多电平变流器模型预测控制策略
A Backward Prediction Based Model Predictive Control Strategy for Modular Multilevel Converters
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摘要: 现有模块化多电平变流器(modular multilevel converter,MMC)模型预测控制方法大都基于代价方程,造成计算过程复杂等问题,论文提出一种基于逆向预测的MMC模型预测控制策略,通过综合前向差分法和最近电平近似法,逆向预测最优开关状态,控制相电流及环流;同时,引入环流滞环控制以提升输出电压电能质量,降低开关损耗。最后,通过搭建桥臂子模块数量为20的MMC仿真控制系统对所述理论进行验证。仿真结果表明,与已有控制方法相比,该文方法计算简便,电压输出特性及动态响应特性好,且功率器件开关损耗显著下降。Abstract: Existing model predictive control methods for modular multilevel converters need to establish cost functions and have a complex calculation process. This paper proposed a backward prediction based model predictive control strategy for the MMC, which utilized forward difference method and nearest level approximation to predict the optimal switching state directly, in order to control the phase current and circulating current. Also hysteresis control was introduced in circulating current control to improve the output power quality and reduce the switching loss. An MMC simulation system with 20 submodules in each arm was built to verify the proposed theory. The simulation results show that the proposed strategy is calculating-convenient and has good performance in output characteristics and dynamic response characteristics with significantly lower switching loss.