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A Control Method of Shunt Active Power Filter for System-wide Harmonic Suppression Based on Complex-valued Neural Network

机译:基于复估值神经网络的系统范围谐波抑制分流有源电力滤波器的控制方法

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At present, the active power filter(APF) is a device that can effectively suppress harmonics. However, in the traditional control method, APF can only eliminate the harmonic voltage of a single node. This makes it difficult to apply to the harmonic suppression of the power grid with distributed harmonic sources. For that, how to effectively suppress the system-wide harmonics has become a topic worth studying. This paper proposes a control method that uses a single APF to suppress the system-wide harmonics of the grid. The method collects data generated during operation of the power grid, and then uses the neural network to fit the data to obtain a model between the compensation current of the APF and the voltage of each node. Based on this model, the optimal compensation current will be calculated and no grid parameters are required. Finally, the effectiveness of the proposed method is verified by simulation results.
机译:目前,有效地抑制谐波的有效电力滤波器(APF)是一种设备。然而,在传统的控制方法中,APF只能消除单个节点的谐波电压。这使得难以应用于具有分布式谐波源的电网的谐波抑制。为此,如何有效地抑制系统范围的谐波已成为一个值得研究的主题。本文提出了一种控制方法,它使用单个APF来抑制网格的系统范围谐波。该方法收集在电网运行期间产生的数据,然后使用神经网络拟合数据以在APF的补偿电流和每个节点的电压之间获得模型。基于该模型,将计算最佳补偿电流,并且不需要网格参数。最后,通过模拟结果验证了所提出的方法的有效性。

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