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Harmonic and reactive currents estimation with adaptive neural network and their compensation with DSP control in single-phase shunt active power filter

机译:单相并联有源电力滤波器的自适应神经网络谐波和无功电流估计及其DSP控制补偿

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This paper presents an adaptive neural network (ADNN) method which can estimate harmonic current as well as reactive current in single-phase rectifier-fed inductive and capacitive loads in real time. This estimation technique is utilized in single-phase shunt active power filter to improve the power factor in the utility ac power side and make the supply current free from harmonic. The main feature of this method is that it can determine the fundamental and other harmonic current components that exist in the nonlinear distorted load current by sensing of the load current only. The feasibility of the method is substantiated with both simulation result and experimental one applying digital signal processing controlled hardware implementation.
机译:本文提出了一种自适应神经网络(ADNN)方法,该方法可以实时估计单相整流器馈入的电感性和电容性负载中的谐波电流以及无功电流。这种估计技术被用于单相并联有源功率滤波器中,以提高市电交流功率侧的功率因数,并使电源电流免受谐波影响。该方法的主要特征在于,它可以仅通过感测负载电流来确定非线性失真负载电流中存在的基波和其他谐波电流分量。仿真结果和实验结果均证实了该方法的可行性,并采用了数字信号处理控制的硬件实现。

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