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首页> 外文期刊>International Journal of Electrical and Computer Engineering >Artificial neural network based unity power factor corrector for single phase DC-DC converters
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Artificial neural network based unity power factor corrector for single phase DC-DC converters

机译:单相直流转换器的人工神经网络基统一功率因数校正

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Due to the negative effects of the non-linear semiconductor devices and the passive electrical components (inductor and capacitor) in the converter circuits, and that are deteriorating the power factor (PF) and total harmonics distortion (THD) of grid current, this study proposes a novel unity PF correction controller based on a new algorithm of neural network to improve the performance of a single phase boost DC-DC converter with respect to the mentioned concerns. The controller guarantees stable load voltage. The PF corrector, firstly measures the phase shift between grid voltage and grid current waveforms, then through a new artificial neural network (ANN) algorithm, a suitable duty cycle is predicted to guide and control the converter to reduce the phase shift between grid voltage and grid current as possible to have maximum PF which is unity PF, and to improve the THD level of grid current. The proposed system is simulated and evaluated via Simulink of MATLAB, the simulation results are collected at constant duty cycle and at controlled duty cycle through the proposed PF controller using different loads. The presented PF controller guarantees the unity power factor, and enhances the grid alternating current THD.
机译:由于转换器电路中的非线性半导体器件和无源电气部件(电感器和电容器)的负面影响,并且该研究劣化了电力因数(PF)和总谐波失真(THD),这项研究基于新的神经网络算法提出了一种新颖的UNICE PF校正控制器,以提高单相提升DC-DC转换器关于所提到的问题的性能。控制器保证稳定的负载电压。 PF校正器首先测量电网电压和电网电流波形之间的相移,然后通过新的人工神经网络(ANN)算法,预测合适的占空比,以引导和控制转换器以减小电网电压之间的相移和电网电流尽可能具有最大PF,其是Unity PF,并提高电流电流的THD水平。通过MATLAB的Simulink模拟和评估所提出的系统,模拟结果在恒定占空比和受控占空比下通过所提出的PF控制器采用不同负载。所呈现的PF控制器可确保Unity功率因数,并增强电网交流电流THD。

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