基于多目标递阶模型预测理论的MMC能量协同控制研究

doi:10.19912/j.0254-0096.tynxb.2021-0498

摘要/Abstract

摘要： 基于模块化多电平换流器的高压直流输电系统（MMC-HVDC）具有广阔的发展前景,针对常规控制方法在不平衡网压下存在控制复杂且换流器内部能量难以控制等缺陷,提出基于多目标递阶模型预测理论的模块化多电平换流器（MMC）能量协同控制策略。该方法通过优化控制各桥臂的各电流分量来调节MMC功率分布,实现交流侧三相电流与换流器内部能量平衡的协同控制;为简化控制复杂度、降低控制计算量,对传统模型预测控制进行优化,建立相应的预测模型和目标函数,并将控制目标划分为内部和外部特性的分层控制,利用外部特性控制的最优解及内部特性分析结果,优化内部特性控制的寻优范围。最后,通过仿真和实验的结果验证所提出的控制策略能更快实现正常及交流侧不平衡工况下的换流器安全稳定运行。

关键词: 电力电子, 直流输电, 模型预测控制, 模块化多电平换流器, 能量平衡

Abstract: The high-voltage direct current transmission system based on modular multilevel converters has a broad development prospect. In view of the defects of conventional control methods such as complex control and difficult control of converter internal energy under unbalanced network voltage, a cooperative control strategy of modular multilevel converter energy based on multi-objective recursive model prediction theory is proposed. By optimizing the control of arm current, the coordinated control on the AC side and the internal energy balance of the converter are realized. In order to simplify the control complexity, this paper optimizes the predictive control in traditional model, establishs the corresponding predictive model and objective function, and divides the control objectives into hierarchical control of internal and external characteristics. Basically, the optimal solution of external characteristics control and the results of internal characteristics analysis are introduced to optimize the range of internal characteristics control. Finally, the results of simulation and experiment verify that the proposed control strategy is able to quickly realize the safe and stable operation of the converter under normal and unbalanced AC side conditions.

中图分类号:

TM48

夏向阳, 徐雷, 易海淦, 陈凯平, 敬华兵, 刘放平. 基于多目标递阶模型预测理论的MMC能量协同控制研究[J]. 太阳能学报, 2022, 43(10): 472-481.

Xia Xiangyang, Xu Lei, Yi Haigan, Chen Kaiping, Jing Huabing, Liu Fangping. RESEARCH ON ENERGY COOPERATIVE CONTROL OF MMC BASED ON MULTI-OBJECTIVE RECURSIVE MODEL PREDICTION THEORY[J]. Acta Energiae Solaris Sinica, 2022, 43(10): 472-481.

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