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Design of fuzzy probabilistic wavelet neural network controller and its application in power control of grid-connected PV system during grid faults

机译:模糊概率小波神经网络控制器的设计及其在光伏系统并网故障期间的功率控制中的应用

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A controller using fuzzy probabilistic wavelet neural network (FPWNN) for grid-connected photovoltaic (PV) system during grid faults is proposed in this study. The FPWNN controller is developed to control the output reactive and active power of the grid-connected inverter which also considers the ratio of the injected reactive current to meet the low voltage ride through (LVRT) regulations. Moreover, the balance of the active power between the PV panel and the grid-connected inverter during grid faults is controlled by the dc-link bus voltage. Furthermore, to reduce the risk of over-current during LVRT operation, a current limit is predefined for the injection of reactive current. The main contribution of this study is the design of the FPWNN controller for reactive and active power control that provides LVRT operation with power balance under various grid fault conditions. Finally, some experimental tests are realized to validate the effectiveness of the proposed control scheme.
机译:提出了一种基于模糊概率小波神经网络(FPWNN)的光伏并网光伏发电系统控制器。 FPWNN控制器是为控制并网逆变器的输出无功和有功功率而开发的,该控制器还考虑注入的无功电流的比率,以符合低压穿越(LVRT)法规。此外,在电网故障期间,光伏面板和并网逆变器之间的有功功率平衡由直流母线电压控制。此外,为了降低LVRT运行期间过电流的风险,为注入无功电流预定义了电流限制。这项研究的主要贡献是针对无功和有功功率控制的FPWNN控制器的设计,该控制器可在各种​​电网故障条件下为LVRT运行提供功率平衡。最后,通过一些实验测试验证了所提控制方案的有效性。

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