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Three-phase three-level grid interactive inverter with fuzzy logic based maximum power point tracking controller

机译：基于模糊逻辑的最大功率点跟踪控制器的三相三电平并网逆变器

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摘要

In this study, three-phase single stage grid interactive inverter with maximum power point tracking capability is proposed. The proposed system consists of three-level neutral point clamped inverter, LCL output filter, line frequency transformer, PI current regulator and fuzzy logic based maximum power point tracking algorithm. Rate of change of photovoltaic power and voltage are defined as input variables, and the change in reference current is defined as output variable for the fuzzy logic controller. The proposed maximum power point tracking algorithm is robust with respect to parameter variations of photovoltaic system with adaptive feature of fuzzy logic controller. Maximum power point tracking algorithm determines the inverter current reference depending on the system conditions such as irradiation level and temperature, and PI regulator shapes the inverter output current. Two capacitors' voltages of neutral point clamped inverter are also balanced. Simulation and experimental results show that the proposed inverter system has fast transient response and can track the maximum power point of PV system even if atmospheric condition changes rapidly. Also, the inverter output current is in sinusoidal waveform and in phase with line frequency and phase. In addition, total harmonic distortion level of the inverter output current is in the limits of international standards (<5%) and efficiencies of maximum power point tracking algorithm and total system are measured as 98.78% and 93.12%, respectively.
机译：本文提出了具有最大功率点跟踪能力的三相单级电网交互式逆变器。该系统由三级中性点钳位逆变器，LCL输出滤波器，线路频率变压器，PI电流调节器和基于模糊逻辑的最大功率点跟踪算法组成。光伏功率和电压的变化率定义为输入变量，而参考电流的变化定义为模糊逻辑控制器的输出变量。提出的最大功率点跟踪算法对于具有模糊逻辑控制器自适应特征的光伏系统参数变化具有鲁棒性。最大功率点跟踪算法根据系统条件（例如辐射水平和温度）确定逆变器电流参考，PI调节器对逆变器输出电流进行整形。中性点钳位逆变器的两个电容器电压也达到平衡。仿真和实验结果表明，所提出的逆变器系统具有快速的瞬态响应，即使大气条件迅速变化，也可以跟踪光伏系统的最大功率点。同样，逆变器输出电流为正弦波形，与线路频率和相位同相。此外，逆变器输出电流的总谐波失真水平在国际标准的范围内（<5％），最大功率跟踪算法和整个系统的效率分别为98.78％和93.12％。

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