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Modelling and controlling of PV connected quasi Z-source cascaded multilevel inverter system: An HACSNN based control approach

机译:光伏连接准Z源级联多电平逆变器系统的建模与控制:基于HACSNN的控制方法

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摘要

In this paper, the modelling and controller design for quasi-Z source cascaded multilevel inverter (QZS-CMI) based three-phase grid-tie photovoltaic (PV) power system is presented. The control scheme of 3-phase QZS-CMI is designed as two phases and regulates the source PV voltage and output grid current. Here, the first phase utilized Adaptive Cuckoo Search (ACS) algorithm for determining the total PV voltage and the second phase utilized CS algorithm with artificial neural network (ANN) to extract the reference current of grid. In first phase, the ACS algorithm engendered the tuning parameters of the PI controller based on the variation of the PV voltage. The second phase ANN is trained offline manner with the exact dataset prepared by the CS technique and it ensures the grid current control. The proposed method is refined for regulating the DC link voltages and extracting the grid currents. The proposed method based QZS-CMI synchronizes the shoot through duty ratio, reduces the modulation burden, regulates the dc link voltage, current and frequency conditions. By using the proposed method, all presented QZS-H-bridge inverter (HBI) modules achieves the grid-tie current injection and independent maximum power point tracking (MPPT) using system level control. The proposed method based QZS-CMI is designed with MATLAB/Simulink platform and their performances are evaluated with traditional techniques.
机译:提出了基于准Z源级联多电平逆变器(QZS-CMI)的三相并网光伏发电系统的建模和控制器设计。三相QZS-CMI的控制方案设计为两相,并调节电源PV电压和输出电网电流。在此,第一阶段利用自适应杜鹃搜索(ACS)算法确定总PV电压,第二阶段利用CS神经网络算法与人工神经网络(ANN)提取电网参考电流。在第一阶段,ACS算法根据PV电压的变化产生PI控制器的调整参数。第二阶段的人工神经网络采用CS技术准备的精确数据集进行离线训练,从而确保了电网电流的控制。提出的方法经过改进,可调节直流母线电压并提取电网电流。所提出的基于QZS-CMI的方法可以使直通占空比同步,减少调制负担,调节直流链路的电压,电流和频率条件。通过使用所提出的方法,所有提出的QZS-H桥逆变器(HBI)模块都使用系统级控制来实现并网电流注入和独立的最大功率点跟踪(MPPT)。基于MATLAB / Simulink平台设计了基于QZS-CMI的方法,并利用传统技术对其性能进行了评估。

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