赵磊磊,牟伟,宋慧庆,张民,王珊
ZHAO Leilei,MU Wei,SONG Huiqing,ZHANG Min,WANG Shan

• 1:烟台汽车工程职业学院
• 2:国网浙江省电力有限公司东阳市供电公司
• 3:青岛理工大学

摘要(Abstract)：

弱电网下并网逆变器的鲁棒性较差、谐波较大，而模型预测控制十分依赖系统参数，这限制了其在弱电网中的应用。针对以上问题，提出适用于NPC（二极管中点钳位）型三电平并网逆变器的数据驱动型V-MFPC（基于虚拟电压矢量的无模型预测控制）策略。首先通过不同的开关序列构造大量虚拟电压矢量，然后利用代价函数预选降低控制算法的计算负担，最后选择合适的开关序列寻优抑制中性点电压波动。仿真结果表明，所提策略能有效抑制中性点电压波动和并网电流谐波，并具有较好的参数鲁棒性。
In weak power grids, grid-connected inverters often suffer from poor robustness and significant harmonics. Moreover, model predictive control(MPC) heavily relies on system parameters, limiting its applicability in weak grids. To address these issues, a data-driven model-free predictive control(MFPC) strategy base on virtual voltage vectors for neutral-point clamped(NPC) three-level grid-connected inverters is proposed. Firstly, the MFPC based on virtual voltage vectors constructs numerous virtual voltage vectors through different switching sequences.Then, a cost function is utilized to pre-select and reduce the computational burden of the control algorithm. Finally, appropriate switching sequences are chosen for optimization to suppress neutral-point voltage fluctuations. Simulation results demonstrate that the proposed strategy effectively mitigates neutral-point voltage fluctuations and grid current harmonics, while exhibiting robustness to parameter variations.

关键词(KeyWords)： 弱电网;NPC型三电平逆变器;数据驱动型模型预测控制;鲁棒性
weak grid;NPC three-level inverter;data-driven model predictive control;robustness

Abstract:

Keywords:

基金项目(Foundation): 山东省自然科技基金面上项目（ZR2022ME214）;; 烟台汽车工程职业学院规划课题研究项目（YTQC2022ZRKX08）

作者(Author): 赵磊磊,牟伟,宋慧庆,张民,王珊
ZHAO Leilei,MU Wei,SONG Huiqing,ZHANG Min,WANG Shan

DOI: 10.19585/j.zjdl.202406007

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